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Ladakis DC, Pedrini E, Reyes-Mantilla MI, Sanjayan M, Smith MD, Fitzgerald KC, Pardo CA, Reich DS, Absinta M, Bhargava P. Metabolomics of Multiple Sclerosis Lesions Demonstrates Lipid Changes Linked to Alterations in Transcriptomics-Based Cellular Profiles. Neurol Neuroimmunol Neuroinflamm 2024; 11:e200219. [PMID: 38547430 DOI: 10.1212/nxi.0000000000200219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/19/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND AND OBJECTIVES People with multiple sclerosis (MS) have a dysregulated circulating metabolome, but the metabolome of MS brain lesions has not been studied. The aims of this study were to identify differences in the brain tissue metabolome in MS compared with controls and to assess its association with the cellular profile of corresponding tissue. METHODS MS tissues included samples from the edge and core of chronic active or inactive lesions and periplaque white matter (WM). Control specimens were obtained from normal WM. Metabolomic analysis was performed using mass-spectrometry coupled with liquid/gas chromatography and subsequently integrated with single-nucleus RNA-sequencing data by correlating metabolite abundances with relative cell counts, as well as individual genes using Multiomics Factor Analysis (MOFA). RESULTS Seventeen samples from 5 people with secondary progressive MS and 8 samples from 6 controls underwent metabolomic profiling identifying 783 metabolites. MS lesions had higher levels of sphingosines (false discovery rate-adjusted p-value[q] = 2.88E-05) and sphingomyelins and ceramides (q = 2.15E-07), but lower nucleotide (q = 0.05), energy (q = 0.001), lysophospholipid (q = 1.86E-07), and monoacylglycerol (q = 0.04) metabolite levels compared with control WM. Periplaque WM had elevated sphingomyelins and ceramides (q = 0.05) and decreased energy metabolites (q = 0.01) and lysophospholipids (q = 0.05) compared with control WM. Sphingolipids and membrane lipid metabolites were positively correlated with astrocyte and immune cell abundances and negatively correlated with oligodendrocytes. On the other hand, long-chain fatty acid, endocannabinoid, and monoacylglycerol pathways were negatively correlated with astrocyte and immune cell populations and positively correlated with oligodendrocytes. MOFA demonstrated associations between differentially expressed metabolites and genes involved in myelination and lipid biosynthesis. DISCUSSION MS lesions and perilesional WM demonstrated a significantly altered metabolome compared with control WM. Many of the altered metabolites were associated with altered cellular composition and gene expression, indicating an important role of lipid metabolism in chronic neuroinflammation in MS.
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Affiliation(s)
- Dimitrios C Ladakis
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Edoardo Pedrini
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Maria I Reyes-Mantilla
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Muraleetharan Sanjayan
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Matthew D Smith
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Kathryn C Fitzgerald
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Carlos A Pardo
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Daniel S Reich
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Martina Absinta
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pavan Bhargava
- From the Department of Neurology (D.C.L., M.I.R.-M., M.S., M.D.S., K.C.F., C.A.P., D.S.R., M.A., P.B.), Johns Hopkins University School of Medicine, Baltimore, MD; Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy and Translational Neuroradiology Section (D.S.R., M.A.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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Makhani N, Lebrun-Frenay C, Siva A, Shabanova V, Wassmer E, Santoro JD, Narula S, Brenton JN, Mar S, Durand-Dubief F, Zephir H, Mathey G, Rojas JI, de Seze J, Tenembaum S, Stone RT, Casez O, Carra-Dallière C, Neuteboom RF, Ahsan N, Arroyo HA, Cabre P, Gombolay G, Inglese M, Louapre C, Margoni M, Palavra F, Pohl D, Reich DS, Ruet A, Thouvenot E, Timby N, Tintore M, Uygunoglu U, Vargas W, Venkateswaran S, Verhelst H, Wickstrom R, Azevedo CJ, Kantarci O, Shapiro ED, Okuda DT, Pelletier D. The diagnostic workup of children with the radiologically isolated syndrome differs by age and by sex. J Neurol 2024:10.1007/s00415-024-12289-1. [PMID: 38564056 DOI: 10.1007/s00415-024-12289-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/19/2024] [Accepted: 02/29/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Cerebrospinal fluid (CSF) and spinal MRIs are often obtained in children with the radiologically isolated syndrome (RIS) for diagnosis and prognosis. Factors affecting the frequency and timing of these tests are unknown. OBJECTIVE To determine whether age or sex were associated with (1) having CSF or spinal MRI obtained or (2) the timing of these tests. METHODS We analyzed children (≤ 18 y) with RIS enrolled in an international longitudinal study. Index scans met 2010/2017 multiple sclerosis (MS) MRI criteria for dissemination in space (DIS). We used Fisher's exact test and multivariable logistic regression (covariates = age, sex, MRI date, MRI indication, 2005 MRI DIS criteria met, and race). RESULTS We included 103 children with RIS (67% girls, median age = 14.9 y). Children ≥ 12 y were more likely than children < 12 y to have CSF obtained (58% vs. 21%, adjusted odds ratio [AOR] = 4.9, p = 0.03). Pre-2017, girls were more likely than boys to have CSF obtained (n = 70, 79% vs. 52%, AOR = 4.6, p = 0.01), but not more recently (n = 30, 75% vs. 80%, AOR = 0.2, p = 0.1; p = 0.004 for interaction). Spinal MRIs were obtained sooner in children ≥ 12 y (median 11d vs. 159d, p = 0.03). CONCLUSIONS Younger children with RIS may be at continued risk for misdiagnosis and misclassification of MS risk. Consensus guidelines are needed.
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Affiliation(s)
- Naila Makhani
- Department of Pediatrics, Yale University, LMP 3088, 333 Cedar Street, New Haven, CT, 06520, USA.
- Department of Neurology, Yale University, New Haven, CT, USA.
| | - Christine Lebrun-Frenay
- CRCSEP Neurologie Pasteur 2, CHU de Nice, Université Cote d'Azur, UMR2CA (URRIS), Nice, France
| | - Aksel Siva
- Neuroimmunology Unit, Neurology Department, Istanbul University Cerrahpasa School of Medicine, Istanbul, Turkey
| | - Veronika Shabanova
- Department of Pediatrics, Yale University, LMP 3088, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Evangeline Wassmer
- Neurology Department, Birmingham Children's Hospital, Aston University, Birmingham, UK
| | - Jonathan D Santoro
- Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, USA
- Division of Neurology, Department of Pediatrics, Children's Hospital of Los Angeles, Los Angeles, USA
| | - Sona Narula
- Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, USA
| | | | - Soe Mar
- Department of Neurology, Washington University School of Medicine, St. Louis, USA
| | - Francoise Durand-Dubief
- Service de sclérose en plaques, Pathologies de la myéline et Neuro-Inflammation, Hôpital Neurologique, Groupement Hospitalier Est, 59 Bd Pinel, 69677, BRON Cedex, France
| | - Helene Zephir
- Inserm UMR-S 1172 LilNcog, Lille University Hospital FHU Precise, Lille University, Lille, France
| | - Guillaume Mathey
- Department of Neurology, Nancy University Hospital, 54035, Nancy, France
| | - Juan I Rojas
- Hospital Universitario de CEMIC, Buenos Aires, Argentina
| | - Jerome de Seze
- Department of Neurology, Hospital Hautepierre, CHU de Strasbourg and Clinical Investigation Center (CIC) INSERM 1434, Strasbourg, France
| | - Silvia Tenembaum
- Department of Neurology, National Pediatric Hospital Dr. Juan P Garrahan, Buenos Aires, Argentina
| | | | - Olivier Casez
- Neurology MS Clinic Grenoble, Grenoble Alpes University Hospital, Grenoble, France
- T-RAIG, TIMC-IMAG, Grenoble Alpes University, Grenoble, France
| | - Clarisse Carra-Dallière
- Neurology MS Clinic, Montpellier University Hospital, 34295, Montpellier, France
- University of Montpellier (MUSE), 34295, Montpellier, France
| | - Rinze F Neuteboom
- Department of Neurology, Erasmus MC Rotterdam, Sophia's Children's Hospital, Rotterdam, The Netherlands
| | - Nusrat Ahsan
- Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, USA
- Division of Neurology, Department of Pediatrics, Children's Hospital of Los Angeles, Los Angeles, USA
| | - Hugo A Arroyo
- Department of Neurology, Hospital de Pediatría SAMIC. Prof. Dr. J.P. Garrahan, Buenos Aires, Argentina
| | - Philippe Cabre
- Centre Hospitalo Universitaire, Fort-de-France, Martinique
| | - Grace Gombolay
- Division of Neurology, Department of Pediatrics, Emory University and Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health Department of Neuroscience (DINOGMI), University of Genova, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Celine Louapre
- Assistance Publique Hôpitaux de Paris, Inserm, CNRS, Hôpital de la Pitié Salpêtrière, CIC Neurosciences, Sorbonne Université, Paris Brain Institute - ICM, Paris, France
| | - Monica Margoni
- Department of Neurosciences, Multiple Sclerosis Center of the Veneto Region, University Hospital-School of Medicine, Padua, Italy
| | - Filipe Palavra
- Center for Child Development - Neuropaediatrics Unit, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Daniela Pohl
- Division of Neurology, Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, USA
| | - Aurélie Ruet
- Department of Neurology, CHU Bordeaux, Bordeaux, France
- INSERM, Neurocentre Magendie, University of Bordeaux, U1215, Bordeaux, France
| | - Eric Thouvenot
- Department of Neurology, Nîmes University Hospital, Nîmes, France
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Niklas Timby
- Department of Clinical Sciences/Pediatrics, Umeå University, Umeå, Sweden
| | - Mar Tintore
- Neurology Department, MS Center of Catalunya Cemcat, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona (UAB), UVIC-Universitat Central de Catalunya, Barcelona, Spain
| | - Ugur Uygunoglu
- Neuroimmunology Unit, Neurology Department, Istanbul University Cerrahpasa School of Medicine, Istanbul, Turkey
| | - Wendy Vargas
- Department of Neurology, Columbia University Medical Center, New York, USA
| | | | - Helene Verhelst
- Division of Pediatric Neurology, Department of Pediatrics, University Hospital Ghent, Ghent, Belgium
| | - Ronny Wickstrom
- Neuropaediatric Unit, Department of Women's and Children's Health, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Christina J Azevedo
- Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Orhun Kantarci
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Eugene D Shapiro
- Department of Pediatrics, Yale University, LMP 3088, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Darin T Okuda
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, USA
| | - Daniel Pelletier
- Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, USA
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Reich DS. In Memoriam: Henry F. McFarland (1940-2024). Ann Neurol 2024; 95:419-420. [PMID: 38421031 DOI: 10.1002/ana.26887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 01/22/2024] [Accepted: 01/26/2024] [Indexed: 03/02/2024]
Affiliation(s)
- Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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Smyth LCD, Xu D, Okar SV, Dykstra T, Rustenhoven J, Papadopoulos Z, Bhasiin K, Kim MW, Drieu A, Mamuladze T, Blackburn S, Gu X, Gaitán MI, Nair G, Storck SE, Du S, White MA, Bayguinov P, Smirnov I, Dikranian K, Reich DS, Kipnis J. Identification of direct connections between the dura and the brain. Nature 2024; 627:165-173. [PMID: 38326613 DOI: 10.1038/s41586-023-06993-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 12/18/2023] [Indexed: 02/09/2024]
Abstract
The arachnoid barrier delineates the border between the central nervous system and dura mater. Although the arachnoid barrier creates a partition, communication between the central nervous system and the dura mater is crucial for waste clearance and immune surveillance1,2. How the arachnoid barrier balances separation and communication is poorly understood. Here, using transcriptomic data, we developed transgenic mice to examine specific anatomical structures that function as routes across the arachnoid barrier. Bridging veins create discontinuities where they cross the arachnoid barrier, forming structures that we termed arachnoid cuff exit (ACE) points. The openings that ACE points create allow the exchange of fluids and molecules between the subarachnoid space and the dura, enabling the drainage of cerebrospinal fluid and limited entry of molecules from the dura to the subarachnoid space. In healthy human volunteers, magnetic resonance imaging tracers transit along bridging veins in a similar manner to access the subarachnoid space. Notably, in neuroinflammatory conditions such as experimental autoimmune encephalomyelitis, ACE points also enable cellular trafficking, representing a route for immune cells to directly enter the subarachnoid space from the dura mater. Collectively, our results indicate that ACE points are a critical part of the anatomy of neuroimmune communication in both mice and humans that link the central nervous system with the dura and its immunological diversity and waste clearance systems.
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Affiliation(s)
- Leon C D Smyth
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA.
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
| | - Di Xu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Taitea Dykstra
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Justin Rustenhoven
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Department of Pharmacology and Clinical Pharmacology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Zachary Papadopoulos
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Neuroscience Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Kesshni Bhasiin
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Min Woo Kim
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Antoine Drieu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Tornike Mamuladze
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Susan Blackburn
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Xingxing Gu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - María I Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Steffen E Storck
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Siling Du
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Michael A White
- Department of Genetics, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Peter Bayguinov
- Washington University Center for Cellular Imaging, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Igor Smirnov
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Krikor Dikranian
- Department of Neuroscience, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jonathan Kipnis
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA.
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
- Neuroscience Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
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Okar SV, Dieckhaus H, Beck ES, Gaitán MI, Norato G, Pham DL, Absinta M, Cortese IC, Fletcher A, Jacobson S, Nair G, Reich DS. Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis. Invest Radiol 2024; 59:243-251. [PMID: 37493285 PMCID: PMC10818009 DOI: 10.1097/rli.0000000000001011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
BACKGROUND Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. PURPOSE To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. MATERIALS AND METHODS We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. RESULTS We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. CONCLUSIONS Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.
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Affiliation(s)
- Serhat Vahip Okar
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (S.V.O., E.S.B., M.I.G., M.A., D.S.R.); qMRI Core facility, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (H.D., G.N.); Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA (E.S.B.); Office of Biostatistics, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (G.N.); Department of Radiology and Radiological Sciences, Uniformed Services University of the Health Sciences, Bethesda, MD, USA (D.L.P.); Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy (M.A.); Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA (M.A.); Experimental Immunotherapeutics Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (I.C.M.C.); Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (A.F.); and Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD20814, USA (S.J.)
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Seddighi S, Qi YA, Brown AL, Wilkins OG, Bereda C, Belair C, Zhang YJ, Prudencio M, Keuss MJ, Khandeshi A, Pickles S, Kargbo-Hill SE, Hawrot J, Ramos DM, Yuan H, Roberts J, Sacramento EK, Shah SI, Nalls MA, Colón-Mercado JM, Reyes JF, Ryan VH, Nelson MP, Cook CN, Li Z, Screven L, Kwan JY, Mehta PR, Zanovello M, Hallegger M, Shantaraman A, Ping L, Koike Y, Oskarsson B, Staff NP, Duong DM, Ahmed A, Secrier M, Ule J, Jacobson S, Reich DS, Rohrer JD, Malaspina A, Dickson DW, Glass JD, Ori A, Seyfried NT, Maragkakis M, Petrucelli L, Fratta P, Ward ME. Mis-spliced transcripts generate de novo proteins in TDP-43-related ALS/FTD. Sci Transl Med 2024; 16:eadg7162. [PMID: 38277467 DOI: 10.1126/scitranslmed.adg7162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 01/23/2024] [Indexed: 01/28/2024]
Abstract
Functional loss of TDP-43, an RNA binding protein genetically and pathologically linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), leads to the inclusion of cryptic exons in hundreds of transcripts during disease. Cryptic exons can promote the degradation of affected transcripts, deleteriously altering cellular function through loss-of-function mechanisms. Here, we show that mRNA transcripts harboring cryptic exons generated de novo proteins in TDP-43-depleted human iPSC-derived neurons in vitro, and de novo peptides were found in cerebrospinal fluid (CSF) samples from patients with ALS or FTD. Using coordinated transcriptomic and proteomic studies of TDP-43-depleted human iPSC-derived neurons, we identified 65 peptides that mapped to 12 cryptic exons. Cryptic exons identified in TDP-43-depleted human iPSC-derived neurons were predictive of cryptic exons expressed in postmortem brain tissue from patients with TDP-43 proteinopathy. These cryptic exons produced transcript variants that generated de novo proteins. We found that the inclusion of cryptic peptide sequences in proteins altered their interactions with other proteins, thereby likely altering their function. Last, we showed that 18 de novo peptides across 13 genes were present in CSF samples from patients with ALS/FTD spectrum disorders. The demonstration of cryptic exon translation suggests new mechanisms for ALS/FTD pathophysiology downstream of TDP-43 dysfunction and may provide a potential strategy to assay TDP-43 function in patient CSF.
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Affiliation(s)
- Sahba Seddighi
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yue A Qi
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Anna-Leigh Brown
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Oscar G Wilkins
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
- Francis Crick Institute, London, UK
| | - Colleen Bereda
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cedric Belair
- Laboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Yong-Jie Zhang
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Mercedes Prudencio
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Matthew J Keuss
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Aditya Khandeshi
- Laboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Sarah Pickles
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Sarah E Kargbo-Hill
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - James Hawrot
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel M Ramos
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Hebao Yuan
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jessica Roberts
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Erika Kelmer Sacramento
- Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Beutenbergstrasse 11, 07745 Jena, Germany
| | - Syed I Shah
- Data Tecnica International, Washington, DC, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
| | - Jennifer M Colón-Mercado
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Joel F Reyes
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Veronica H Ryan
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Matthew P Nelson
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Casey N Cook
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Ziyi Li
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Washington, DC, USA
| | - Laurel Screven
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Justin Y Kwan
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Puja R Mehta
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Matteo Zanovello
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Martina Hallegger
- Francis Crick Institute, London, UK
- UK Dementia Research Institute at King's College London, London, UK
| | | | - Lingyan Ping
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Yuka Koike
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Björn Oskarsson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Nathan P Staff
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Duc M Duong
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Aisha Ahmed
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Maria Secrier
- Department of Genetics, Evolution and Environment, UCL Genetics Institute, UCL, London, UK
| | - Jernej Ule
- Francis Crick Institute, London, UK
- UK Dementia Research Institute at King's College London, London, UK
| | - Steven Jacobson
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jonathan D Rohrer
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Andrea Malaspina
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Jonathan D Glass
- Department of Neurology, Center for Neurodegenerative Diseases, Emory University, Atlanta, GA, USA
| | - Alessandro Ori
- Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Beutenbergstrasse 11, 07745 Jena, Germany
| | - Nicholas T Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Manolis Maragkakis
- Laboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Leonard Petrucelli
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Pietro Fratta
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
- Francis Crick Institute, London, UK
| | - Michael E Ward
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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7
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Bagnato F, Sati P, Hemond CC, Elliott C, Gauthier SA, Harrison DM, Mainero C, Oh J, Pitt D, Shinohara RT, Smith SA, Trapp B, Azevedo CJ, Calabresi PA, Henry RG, Laule C, Ontaneda D, Rooney WD, Sicotte NL, Reich DS, Absinta M. Imaging chronic active lesions in multiple sclerosis: a consensus statement. Brain 2024:awae013. [PMID: 38226694 DOI: 10.1093/brain/awae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 11/21/2023] [Accepted: 12/08/2023] [Indexed: 01/17/2024] Open
Abstract
Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis (MS) and have implications for non-relapsing biological progression. In recent years, the discovery of innovative magnetic resonance imaging (MRI) and PET derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with MS, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted (T1-w) and T2-w scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification, and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a Consensus Statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this Consensus Statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.
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Affiliation(s)
- Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Neurology, Nashville VA Medical Center, Tennessee Valley Healthcare System, Nashville, TN 37212, USA
| | - Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048 USA
| | | | | | - Susan A Gauthier
- Department of Neurology, Weill Cornell Medicine, NYC, NY 10021, USA
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
- Department of Neurology, Baltimore VA Medical Center, VA Maryland Healthcare System; Baltimore, MD 21201, USA
| | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jiwon Oh
- Division of Neurology, St. Michael's Hospital, University of Toronto, Toronto, ON M5S, Canada
| | - David Pitt
- Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Endeavor, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Bruce Trapp
- Department on Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Christina J Azevedo
- Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90007, USA
| | - Peter A Calabresi
- Departments of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Roland G Henry
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA 94158, USA
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH 44195, USA
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Martina Absinta
- Departments of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Translational Neuropathology Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, 20132, Italy
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8
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Szczupak D, Schaeffer DJ, Tian X, Choi SH, Fang-Cheng, Iack PM, Campos VP, Mayo JP, Patsch J, Mitter C, Haboosheh A, Kwon HS, Vieira MAC, Reich DS, Jacobson S, Kasprian G, Tovar-Moll F, Lent R, Silva AC. Direct interhemispheric cortical communication via thalamic commissures: a new white matter pathway in the primate brain. Cereb Cortex 2024; 34:bhad394. [PMID: 37950874 PMCID: PMC10793074 DOI: 10.1093/cercor/bhad394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 11/13/2023] Open
Abstract
Cortical neurons of eutherian mammals project to the contralateral hemisphere, crossing the midline primarily via the corpus callosum and the anterior, posterior, and hippocampal commissures. We recently reported and named the thalamic commissures (TCs) as an additional interhemispheric axonal fiber pathway connecting the cortex to the contralateral thalamus in the rodent brain. Here, we demonstrate that TCs also exist in primates and characterize the connectivity of these pathways with high-resolution diffusion-weighted MRI, viral axonal tracing, and fMRI. We present evidence of TCs in both New World (Callithrix jacchus and Cebus apella) and Old World primates (Macaca mulatta). Further, like rodents, we show that the TCs in primates develop during the embryonic period, forming anatomical and functionally active connections of the cortex with the contralateral thalamus. We also searched for TCs in the human brain, showing their presence in humans with brain malformations, although we could not identify TCs in healthy subjects. These results pose the TCs as a vital fiber pathway in the primate brain, allowing for more robust interhemispheric connectivity and synchrony and serving as an alternative commissural route in developmental brain malformations.
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Affiliation(s)
- Diego Szczupak
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
| | - David J Schaeffer
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
| | - Xiaoguang Tian
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
| | - Sang-Ho Choi
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
| | - Fang-Cheng
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15261, USA
| | - Pamela Meneses Iack
- Biomedical Sciences Institute, Federal University of Rio de Janeiro, 373 Carlos Chagas Filho Avenue, Rio de Janeiro, Rio de Janeiro 21941-853, Brazil
| | - Vinicius P Campos
- Department of Electrical and Computer Engineering, 400 Trabalhador São-Carlense Avenue, University of São Paulo, São Carlos, SP 13565-905, Brazil
| | - J Patrick Mayo
- Department of Ophthalmology, University of Pittsburgh, 1622 Locust Street, Pittsburgh, PA 15261, USA
| | - Janina Patsch
- Department of Biomedical Imaging and Image-Guided Therapy of the Medical University of Vienna, 18-20 Währinger Gürtel, 1090, Vienna, Austria
| | - Christian Mitter
- Department of Biomedical Imaging and Image-Guided Therapy of the Medical University of Vienna, 18-20 Währinger Gürtel, 1090, Vienna, Austria
| | - Amit Haboosheh
- Department of Radiology Hadassah Ein Karem Hospital, Kalman Ya'akov Man St, Jerusalem 9112001, Israel
| | - Ha Seung Kwon
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
| | - Marcelo A C Vieira
- Department of Electrical and Computer Engineering, 400 Trabalhador São-Carlense Avenue, University of São Paulo, São Carlos, SP 13565-905, Brazil
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Drive, Bethesda, MD 20814, USA
| | - Steve Jacobson
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Drive, Bethesda, MD 20814, USA
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-Guided Therapy of the Medical University of Vienna, 18-20 Währinger Gürtel, 1090, Vienna, Austria
| | - Fernanda Tovar-Moll
- D’Or Institute of Research and Education, 30 Rua Diniz Cordeiro Street, Rio de Janeiro, Rio de Janeiro 22281-100, Brazil
| | - Roberto Lent
- Biomedical Sciences Institute, Federal University of Rio de Janeiro, 373 Carlos Chagas Filho Avenue, Rio de Janeiro, Rio de Janeiro 21941-853, Brazil
- D’Or Institute of Research and Education, 30 Rua Diniz Cordeiro Street, Rio de Janeiro, Rio de Janeiro 22281-100, Brazil
| | - Afonso C Silva
- University of Pittsburgh Brain Institute, Department of Neurobiology, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15261, USA
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9
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Okar SV, Fagiani F, Absinta M, Reich DS. Imaging of brain barrier inflammation and brain fluid drainage in human neurological diseases. Cell Mol Life Sci 2024; 81:31. [PMID: 38212566 PMCID: PMC10838199 DOI: 10.1007/s00018-023-05073-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 11/22/2023] [Accepted: 11/29/2023] [Indexed: 01/13/2024]
Abstract
The intricate relationship between the central nervous system (CNS) and the immune system plays a crucial role in the pathogenesis of various neurological diseases. Understanding the interactions among the immunopathological processes at the brain borders is essential for advancing our knowledge of disease mechanisms and developing novel diagnostic and therapeutic approaches. In this review, we explore the emerging role of neuroimaging in providing valuable insights into brain barrier inflammation and brain fluid drainage in human neurological diseases. Neuroimaging techniques have enabled us not only to visualize and assess brain structures, but also to study the dynamics of the CNS in health and disease in vivo. By analyzing imaging findings, we can gain a deeper understanding of the immunopathology observed at the brain-immune interface barriers, which serve as critical gatekeepers that regulate immune cell trafficking, cytokine release, and clearance of waste products from the brain. This review explores the integration of neuroimaging data with immunopathological findings, providing valuable insights into brain barrier integrity and immune responses in neurological diseases. Such integration may lead to the development of novel diagnostic markers and targeted therapeutic approaches that can benefit patients with neurological disorders.
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Affiliation(s)
- Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Francesca Fagiani
- Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy
| | - Martina Absinta
- Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132, Milan, Italy.
- Division of Neuroscience, Vita-Salute San Raffaele University, 20132, Milan, Italy.
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
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10
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Daboul L, O’Donnell CM, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi PA, Cree BA, Freeman L, Henry RG, Longbrake EE, Oh J, Papinutto N, Pelletier D, Prchkovska V, Raza P, Ramos M, Samudralwar RD, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Sati P, Ontaneda D. A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis. Mult Scler 2024; 30:25-34. [PMID: 38088067 PMCID: PMC11037932 DOI: 10.1177/13524585231214360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
BACKGROUND The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.
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Affiliation(s)
- Lynn Daboul
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Carly M. O’Donnell
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Moein Amin
- Neurological Institute, Cleveland Clinic, Cleveland, OH
| | | | - John Derbyshire
- Functional MRI Facility, NIMH, National Institutes of Health, Bethesda, MD
| | - Christina Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eduardo Caverzasi
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Bruce A.C. Cree
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas, Austin, TX
| | - Roland G. Henry
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Jiwon Oh
- Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, ON, CANADA
| | - Nico Papinutto
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
| | | | - Praneeta Raza
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Marc Ramos
- QMENTA Cloud Platform, QMENTA Inc., Boston, MA, USA
| | | | - Matthew K. Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Nancy L. Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Andrew J. Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH
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11
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Lucas A, Campbell Arnold T, Okar SV, Vadali C, Kawatra KD, Ren Z, Cao Q, Shinohara RT, Schindler MK, Davis KA, Litt B, Reich DS, Stein JM. Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data. medRxiv 2023:2023.12.28.23300409. [PMID: 38234785 PMCID: PMC10793526 DOI: 10.1101/2023.12.28.23300409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Introduction Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T. Methods A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions. Results Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume. Conclusions LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
| | - T Campbell Arnold
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
| | - Serhat V Okar
- National Institute of Neurological Disorders and Stroke, National Institutes of Health
| | - Chetan Vadali
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
- Department of Radiology, University of Pennsylvania
| | - Karan D Kawatra
- National Institute of Neurological Disorders and Stroke, National Institutes of Health
| | - Zheng Ren
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania
| | - Quy Cao
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania
| | - Matthew K Schindler
- Perelman School of Medicine, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Kathryn A Davis
- Perelman School of Medicine, University of Pennsylvania
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Brian Litt
- Perelman School of Medicine, University of Pennsylvania
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
- Department of Neurology, University of Pennsylvania
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health
| | - Joel M Stein
- Perelman School of Medicine, University of Pennsylvania
- Center for Neuroengineering and Therapeutics, Departments of Bioengineering and Neurology, University of Pennsylvania
- Department of Radiology, University of Pennsylvania
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12
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Donnay C, Dieckhaus H, Tsagkas C, Gaitán MI, Beck ES, Mullins A, Reich DS, Nair G. Pseudo-Label Assisted nnU-Net enables automatic segmentation of 7T MRI from a single acquisition. Front Neuroimaging 2023; 2:1252261. [PMID: 38107773 PMCID: PMC10722186 DOI: 10.3389/fnimg.2023.1252261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023]
Abstract
Introduction Automatic whole brain and lesion segmentation at 7T presents challenges, primarily from bias fields, susceptibility artifacts including distortions, and registration errors. Here, we sought to use deep learning algorithms (D/L) to do both skull stripping and whole brain segmentation on multiple imaging contrasts generated in a single Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) acquisition on participants clinically diagnosed with multiple sclerosis (MS), bypassing registration errors. Methods Brain scans Segmentation from 3T and 7T scanners were analyzed with software packages such as FreeSurfer, Classification using Derivative-based Features (C-DEF), nnU-net, and a novel 3T-to-7T transfer learning method, Pseudo-Label Assisted nnU-Net (PLAn). 3T and 7T MRIs acquired within 9 months from 25 study participants with MS (Cohort 1) were used for training and optimizing. Eight MS patients (Cohort 2) scanned only at 7T, but with expert annotated lesion segmentation, was used to further validate the algorithm on a completely unseen dataset. Segmentation results were rated visually by experts in a blinded fashion and quantitatively using Dice Similarity Coefficient (DSC). Results Of the methods explored here, nnU-Net and PLAn produced the best tissue segmentation at 7T for all tissue classes. In both quantitative and qualitative analysis, PLAn significantly outperformed nnU-Net (and other methods) in lesion detection in both cohorts. PLAn's lesion DSC improved by 16% compared to nnU-Net. Discussion Limited availability of labeled data makes transfer learning an attractive option, and pre-training a nnUNet model using readily obtained 3T pseudo-labels was shown to boost lesion detection capabilities at 7T.
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Affiliation(s)
- Corinne Donnay
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Henry Dieckhaus
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
| | - Charidimos Tsagkas
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - María Inés Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andrew Mullins
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Govind Nair
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
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13
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Stillman JM, Mendes Lopes F, Lin JP, Hu K, Reich DS, Schafer DP. Lipofuscin-like autofluorescence within microglia and its impact on studying microglial engulfment. Nat Commun 2023; 14:7060. [PMID: 37923732 PMCID: PMC10624656 DOI: 10.1038/s41467-023-42809-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 10/23/2023] [Indexed: 11/06/2023] Open
Abstract
Engulfment of cellular material and proteins is a key function for microglia, a resident macrophage of the central nervous system (CNS). Among the techniques used to measure microglial engulfment, confocal light microscopy has been used the most extensively. Here, we show that autofluorescence (AF) likely due to lipofuscin (lipo-AF) and typically associated with aging, can also be detected within microglial lysosomes in the young mouse brain by light microscopy. This lipo-AF signal accumulates first within microglia and it occurs earliest in white versus gray matter. Importantly, in gray matter, lipo-AF signal can confound the interpretation of antibody-labeled synaptic material within microglia in young adult mice. We further show that there is an age-dependent accumulation of lipo-AF inside and outside of microglia, which is not affected by amyloid plaques. We finally implement a robust and cost-effective strategy to quench AF in mouse, marmoset, and human brain tissue.
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Affiliation(s)
- Jacob M Stillman
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
- University of Massachusetts Chan Morningside Graduate School of Biomedical Sciences, Neuroscience Program, Worcester, MA, USA
| | - Francisco Mendes Lopes
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
| | - Jing-Ping Lin
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Kevin Hu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Dorothy P Schafer
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA.
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14
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Galbusera R, Bahn E, Weigel M, Schaedelin S, Franz J, Lu P, Barakovic M, Melie‐Garcia L, Dechent P, Lutti A, Sati P, Reich DS, Nair G, Brück W, Kappos L, Stadelmann C, Granziera C. Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis. Brain Pathol 2023; 33:e13136. [PMID: 36480267 PMCID: PMC10580009 DOI: 10.1111/bpa.13136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022] Open
Abstract
Quantitative MRI (qMRI) probes the microstructural properties of the central nervous system (CNS) by providing biophysical measures of tissue characteristics. In this work, we aimed to (i) identify qMRI measures that distinguish histological lesion types in postmortem multiple sclerosis (MS) brains, especially the remyelinated ones; and to (ii) investigate the relationship between those measures and quantitative histological markers of myelin, axons, and astrocytes in the same experimental setting. Three fixed MS whole brains were imaged with qMRI at 3T to obtain magnetization transfer ratio (MTR), myelin water fraction (MWF), quantitative T1 (qT1), quantitative susceptibility mapping (QSM), fractional anisotropy (FA) and radial diffusivity (RD) maps. The identification of lesion types (active, inactive, chronic active, or remyelinated) and quantification of tissue components were performed using histological staining methods as well as immunohistochemistry and immunofluorescence. Pairwise logistic and LASSO regression models were used to identify the best qMRI discriminators of lesion types. The association between qMRI and quantitative histological measures was performed using Spearman's correlations and linear mixed-effect models. We identified a total of 65 lesions. MTR and MWF best predicted the chance of a lesion to be remyelinated, whereas RD and QSM were useful in the discrimination of active lesions. The measurement of microstructural properties through qMRI did not show any difference between chronic active and inactive lesions. MWF and RD were associated with myelin content in both lesions and normal-appearing white matter (NAWM), FA was the measure most associated with axon content in both locations, while MWF was associated with astrocyte immunoreactivity only in lesions. Moreover, we provided evidence of extensive astrogliosis in remyelinated lesions. Our study provides new information on the discriminative power of qMRI in differentiating MS lesions -especially remyelinated ones- as well as on the relative association between multiple qMRI measures and myelin, axon and astrocytes.
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Affiliation(s)
- Riccardo Galbusera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Erik Bahn
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
| | - Sabine Schaedelin
- Clinical Trial Unit, Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
| | - Jonas Franz
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Campus Institute for Dynamics of Biological NetworksUniversity of GöttingenGöttingenGermany
- Max Planck Institute for Experimental MedicineGöttingenGermany
| | - Po‐Jui Lu
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Lester Melie‐Garcia
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Peter Dechent
- Department of Cognitive NeurologyMR‐Research in Neurosciences, University Medical Center GöttingenGöttingenGermany
| | - Antoine Lutti
- Centre for Research in Neuroscience, Department of Clinical NeurosciencesLaboratoire de Recherche en Neuroimagerie (LREN) University Hospital and University of LausanneLausanneSwitzerland
| | - Pascal Sati
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMarylandUSA
| | - Govind Nair
- National Institute of Neurological Disorders and StrokeBethesdaMarylandUSA
| | - Wolfgang Brück
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Christine Stadelmann
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Network of Excitable Cells (MBExC) ”University of GoettingenGermany
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
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15
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Clark KA, O’Donnell CM, Elliott MA, Tauhid S, Dewey BE, Chu R, Khalil S, Nair G, Sati P, DuVal A, Pellegrini N, Bar-Or A, Markowitz C, Schindler MK, Zurawski J, Calabresi PA, Reich DS, Bakshi R, Shinohara RT. Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis. J Neuroimaging 2023; 33:941-952. [PMID: 37587544 PMCID: PMC10981935 DOI: 10.1111/jon.13147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND AND PURPOSE Multicenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites. METHODS Images were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole-brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization-prepared rapid acquisition gradient echo and T2 fluid-attenuated inversion recovery lesions. Random-effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. RESULTS Random-effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. CONCLUSION Differences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.
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Affiliation(s)
- Kelly A. Clark
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Carly M. O’Donnell
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Mark A. Elliott
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | - Shahamat Tauhid
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Blake E. Dewey
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Renxin Chu
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Samar Khalil
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Govind Nair
- Quantitative MRI core facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Anna DuVal
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nicole Pellegrini
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Amit Bar-Or
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Clyde Markowitz
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Matthew K. Schindler
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jonathan Zurawski
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Peter A. Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Rohit Bakshi
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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16
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Lin JP, Brake A, Donadieu M, Lee A, Kawaguchi R, Sati P, Geschwind DH, Jacobson S, Schafer DP, Reich DS. A 4D transcriptomic map for the evolution of multiple sclerosis-like lesions in the marmoset brain. bioRxiv 2023:2023.09.25.559371. [PMID: 37808784 PMCID: PMC10557631 DOI: 10.1101/2023.09.25.559371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Single-time-point histopathological studies on postmortem multiple sclerosis (MS) tissue fail to capture lesion evolution dynamics, posing challenges for therapy development targeting development and repair of focal inflammatory demyelination. To close this gap, we studied experimental autoimmune encephalitis (EAE) in the common marmoset, the most faithful animal model of these processes. Using MRI-informed RNA profiling, we analyzed ~600,000 single-nucleus and ~55,000 spatial transcriptomes, comparing them against EAE inoculation status, longitudinal radiological signals, and histopathological features. We categorized 5 groups of microenvironments pertinent to neural function, immune and glial responses, tissue destruction and repair, and regulatory network at brain borders. Exploring perilesional microenvironment diversity, we uncovered central roles of EAE-associated astrocytes, oligodendrocyte precursor cells, and ependyma in lesion formation and resolution. We pinpointed imaging and molecular features capturing the pathological trajectory of WM, offering potential for assessing treatment outcomes using marmoset as a platform.
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Affiliation(s)
- Jing-Ping Lin
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Alexis Brake
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Maxime Donadieu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Amanda Lee
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Riki Kawaguchi
- Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Department of Neurology, Cedars Sinai Medical Center, Los Angeles, CA
| | - Daniel H Geschwind
- Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA
- Psychiatry, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Dorothy P Schafer
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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17
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Beck ES, Mullins WA, Dos Santos Silva J, Filippini S, Parvathaneni P, Maranzano J, Morrison M, Suto DJ, Donnay C, Dieckhaus H, Luciano NJ, Sharma K, Gaitán MI, Liu J, de Zwart JA, van Gelderen P, Cortese I, Narayanan S, Duyn JH, Nair G, Sati P, Reich DS. Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis. medRxiv 2023:2023.09.22.23295974. [PMID: 37886541 PMCID: PMC10602044 DOI: 10.1101/2023.09.22.23295974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background and objectives Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL. Methods A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2. Results 59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010μl, range 13-9888 vs median 267μl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183μl, range 270-9888 vs median 321μl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS. Discussion CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.
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Affiliation(s)
- Erin S Beck
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - W Andrew Mullins
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | | | - Stefano Filippini
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurosciences, Drug, and Child Health, University of Florence, Florence, Italy
| | - Prasanna Parvathaneni
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Anatomy, University of Quebec, Trois-Rivieres, QC, Canada
| | - Mark Morrison
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel J Suto
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Corinne Donnay
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Henry Dieckhaus
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Nicholas J Luciano
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Kanika Sharma
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - María Ines Gaitán
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jiaen Liu
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jacco A de Zwart
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Peter van Gelderen
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Irene Cortese
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jeff H Duyn
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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Pleet ML, Welsh JA, Stack EH, Cook S, Johnson DA, Killingsworth B, Traynor T, Clauze A, Hughes R, Monaco MC, Ngouth N, Ohayon J, Enose-Akahata Y, Nath A, Cortese I, Reich DS, Jones JC, Jacobson S. Viral Immune signatures from cerebrospinal fluid extracellular vesicles and particles in HAM and other chronic neurological diseases. Front Immunol 2023; 14:1235791. [PMID: 37622115 PMCID: PMC10446883 DOI: 10.3389/fimmu.2023.1235791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 07/24/2023] [Indexed: 08/26/2023] Open
Abstract
Background and objectives Extracellular vesicles and particles (EVPs) are released from virtually all cell types, and may package many inflammatory factors and, in the case of infection, viral components. As such, EVPs can play not only a direct role in the development and progression of disease but can also be used as biomarkers. Here, we characterized immune signatures of EVPs from the cerebrospinal fluid (CSF) of individuals with HTLV-1-associated myelopathy (HAM), other chronic neurologic diseases, and healthy volunteers (HVs) to determine potential indicators of viral involvement and mechanisms of disease. Methods We analyzed the EVPs from the CSF of HVs, individuals with HAM, HTLV-1-infected asymptomatic carriers (ACs), and from patients with a variety of chronic neurologic diseases of both known viral and non-viral etiologies to investigate the surface repertoires of CSF EVPs during disease. Results Significant increases in CD8+ and CD2+ EVPs were found in HAM patient CSF samples compared to other clinical groups (p = 0.0002 and p = 0.0003 compared to HVs, respectively, and p = 0.001 and p = 0.0228 compared to MS, respectively), consistent with the immunopathologically-mediated disease associated with CD8+ T-cells in the central nervous system (CNS) of HAM patients. Furthermore, CD8+ (p < 0.0001), CD2+ (p < 0.0001), CD44+ (p = 0.0176), and CD40+ (p = 0.0413) EVP signals were significantly increased in the CSF from individuals with viral infections compared to those without. Discussion These data suggest that CD8+ and CD2+ CSF EVPs may be important as: 1) potential biomarkers and indicators of disease pathways for viral-mediated neurological diseases, particularly HAM, and 2) as possible meditators of the disease process in infected individuals.
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Affiliation(s)
- Michelle L. Pleet
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Joshua A. Welsh
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Emily H. Stack
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Sean Cook
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Dove-Anna Johnson
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Bryce Killingsworth
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Tim Traynor
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Annaliese Clauze
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Randall Hughes
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Maria Chiara Monaco
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Nyater Ngouth
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Joan Ohayon
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Yoshimi Enose-Akahata
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Avindra Nath
- Section of Infections of the Nervous System, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Irene Cortese
- Experimental Immunotherapeutics Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Jennifer C. Jones
- Translational Nanobiology Section, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Steven Jacobson
- Viral Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
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19
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Maggi P, Bulcke CV, Pedrini E, Bugli C, Sellimi A, Wynen M, Stölting A, Mullins WA, Kalaitzidis G, Lolli V, Perrotta G, El Sankari S, Duprez T, Li X, Calabresi PA, van Pesch V, Reich DS, Absinta M. B cell depletion therapy does not resolve chronic active multiple sclerosis lesions. EBioMedicine 2023; 94:104701. [PMID: 37437310 PMCID: PMC10436266 DOI: 10.1016/j.ebiom.2023.104701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/23/2023] [Accepted: 06/23/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Chronic active lesions (CAL) in multiple sclerosis (MS) have been observed even in patients taking high-efficacy disease-modifying therapy, including B-cell depletion. Given that CAL are a major determinant of clinical progression, including progression independent of relapse activity (PIRA), understanding the predicted activity and real-world effects of targeting specific lymphocyte populations is critical for designing next-generation treatments to mitigate chronic inflammation in MS. METHODS We analyzed published lymphocyte single-cell transcriptomes from MS lesions and bioinformatically predicted the effects of depleting lymphocyte subpopulations (including CD20 B-cells) from CAL via gene-regulatory-network machine-learning analysis. Motivated by the results, we performed in vivo MRI assessment of PRL changes in 72 adults with MS, 46 treated with anti-CD20 antibodies and 26 untreated, over ∼2 years. FINDINGS Although only 4.3% of lymphocytes in CAL were CD20 B-cells, their depletion is predicted to affect microglial genes involved in iron/heme metabolism, hypoxia, and antigen presentation. In vivo, tracking 202 PRL (150 treated) and 175 non-PRL (124 treated), none of the treated paramagnetic rims disappeared at follow-up, nor was there a treatment effect on PRL for lesion volume, magnetic susceptibility, or T1 time. PIRA occurred in 20% of treated patients, more frequently in those with ≥4 PRL (p = 0.027). INTERPRETATION Despite predicted effects on microglia-mediated inflammatory networks in CAL and iron metabolism, anti-CD20 therapies do not fully resolve PRL after 2-year MRI follow up. Limited tissue turnover of B-cells, inefficient passage of anti-CD20 antibodies across the blood-brain-barrier, and a paucity of B-cells in CAL could explain our findings. FUNDING Intramural Research Program of NINDS, NIH; NINDS grants R01NS082347 and R01NS082347; Dr. Miriam and Sheldon G. Adelson Medical Research Foundation; Cariplo Foundation (grant #1677), FRRB Early Career Award (grant #1750327); Fund for Scientific Research (FNRS).
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Affiliation(s)
- Pietro Maggi
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium; Neuroinflammation Imaging Lab (NIL), Université Catholique de Louvain, Brussels, Belgium; Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland.
| | - Colin Vanden Bulcke
- Neuroinflammation Imaging Lab (NIL), Université Catholique de Louvain, Brussels, Belgium
| | - Edoardo Pedrini
- Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and IRCCS San Raffaele Hospital, Milan, Italy
| | - Céline Bugli
- Plateforme Technologique de Support en Méthodologie et Calcul Statistique, Université Catholique de Louvain, Brussels, Belgium
| | - Amina Sellimi
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Maxence Wynen
- Neuroinflammation Imaging Lab (NIL), Université Catholique de Louvain, Brussels, Belgium
| | - Anna Stölting
- Neuroinflammation Imaging Lab (NIL), Université Catholique de Louvain, Brussels, Belgium
| | - William A Mullins
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Grigorios Kalaitzidis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Valentina Lolli
- Hôpital Erasme, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Gaetano Perrotta
- Hôpital Erasme, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Souraya El Sankari
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Thierry Duprez
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Xu Li
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vincent van Pesch
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Martina Absinta
- Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and IRCCS San Raffaele Hospital, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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20
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Schäffner E, Bosch-Queralt M, Edgar JM, Lehning M, Strauß J, Fleischer N, Kungl T, Wieghofer P, Berghoff SA, Reinert T, Krueger M, Morawski M, Möbius W, Barrantes-Freer A, Stieler J, Sun T, Saher G, Schwab MH, Wrede C, Frosch M, Prinz M, Reich DS, Flügel A, Stadelmann C, Fledrich R, Nave KA, Stassart RM. Myelin insulation as a risk factor for axonal degeneration in autoimmune demyelinating disease. Nat Neurosci 2023; 26:1218-1228. [PMID: 37386131 PMCID: PMC10322724 DOI: 10.1038/s41593-023-01366-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 05/17/2023] [Indexed: 07/01/2023]
Abstract
Axonal degeneration determines the clinical outcome of multiple sclerosis and is thought to result from exposure of denuded axons to immune-mediated damage. Therefore, myelin is widely considered to be a protective structure for axons in multiple sclerosis. Myelinated axons also depend on oligodendrocytes, which provide metabolic and structural support to the axonal compartment. Given that axonal pathology in multiple sclerosis is already visible at early disease stages, before overt demyelination, we reasoned that autoimmune inflammation may disrupt oligodendroglial support mechanisms and hence primarily affect axons insulated by myelin. Here, we studied axonal pathology as a function of myelination in human multiple sclerosis and mouse models of autoimmune encephalomyelitis with genetically altered myelination. We demonstrate that myelin ensheathment itself becomes detrimental for axonal survival and increases the risk of axons degenerating in an autoimmune environment. This challenges the view of myelin as a solely protective structure and suggests that axonal dependence on oligodendroglial support can become fatal when myelin is under inflammatory attack.
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Affiliation(s)
- Erik Schäffner
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Mar Bosch-Queralt
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Julia M Edgar
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Institute of Infection, Immunity and Inflammation, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Maria Lehning
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Judith Strauß
- Institute of Neuroimmunology and Multiple Sclerosis Research, University Medical Center Göttingen, Göttingen, Germany
| | - Niko Fleischer
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Theresa Kungl
- Institute of Anatomy, Leipzig University, Leipzig, Germany
| | - Peter Wieghofer
- Institute of Anatomy, Leipzig University, Leipzig, Germany
- Cellular Neuroanatomy, Institute of Theoretical Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Stefan A Berghoff
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Tilo Reinert
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Martin Krueger
- Institute of Anatomy, Leipzig University, Leipzig, Germany
| | - Markus Morawski
- Paul Flechsig Institute of Brain Research, Leipzig University, Leipzig, Germany
| | - Wiebke Möbius
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | | | - Jens Stieler
- Paul Flechsig Institute of Brain Research, Leipzig University, Leipzig, Germany
| | - Ting Sun
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Gesine Saher
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Markus H Schwab
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany
| | - Christoph Wrede
- Institute of Functional and Applied Anatomy, Research Core Unit Electron Microscopy, Hannover Medical School, Hannover, Germany
| | - Maximilian Frosch
- Institute of Neuropathology, Medical Faculty, University of Freiburg, Freiburg, Germany
| | - Marco Prinz
- Institute of Neuropathology, Medical Faculty, University of Freiburg, Freiburg, Germany
- Centre for NeuroModulation (NeuroModBasics), University of Freiburg, Freiburg, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Alexander Flügel
- Institute of Neuroimmunology and Multiple Sclerosis Research, University Medical Center Göttingen, Göttingen, Germany
| | - Christine Stadelmann
- Institute of Neuropathology, University Medical Center Göttingen, Göttingen, Germany
| | - Robert Fledrich
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
- Institute of Anatomy, Leipzig University, Leipzig, Germany.
| | - Klaus-Armin Nave
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
| | - Ruth M Stassart
- Department of Neurogenetics, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
- Paul Flechsig Institute of Neuropathology, University Clinic Leipzig, Leipzig, Germany.
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21
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Ineichen BV, Cananau C, Plattén M, Ouellette R, Moridi T, Frauenknecht KBM, Okar SV, Kulcsar Z, Kockum I, Piehl F, Reich DS, Granberg T. Dilated Virchow-Robin spaces are a marker for arterial disease in multiple sclerosis. EBioMedicine 2023; 92:104631. [PMID: 37253317 DOI: 10.1016/j.ebiom.2023.104631] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/28/2023] [Accepted: 05/11/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. METHODS In a cohort study comprising 142 MS patients and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) outcomes. Findings were corroborated in a validation cohort comprising 63 MS patients. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. FINDINGS In our actively treated clinical cohort, the count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, in our ex vivo cohort comprising mostly progressive MS patients, dilated VRS in MS were associated with signs of small vessel disease. INTERPRETATION Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with an accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature. FUNDING NIH, Swedish Society for Medical Research, Swiss National Science Foundation and University of Zurich.
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Affiliation(s)
- Benjamin V Ineichen
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden; Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Center for Reproducible Science, University of Zurich, Zurich, Switzerland; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA.
| | - Carmen Cananau
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Michael Plattén
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Thomas Moridi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Katrin B M Frauenknecht
- National Centre for Pathology (NCP), Laboratoire National de Santé, Dudelange, Luxembourg; Luxembourg Centre for Neuropathology (LCNP), Laboratoire National de Santé, Dudelange, Luxembourg
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ingrid Kockum
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Health (NIH), Bethesda, MA, USA
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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22
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Abstract
This article reviews recent developments in the application of cell-free DNA-based liquid biopsies to neurological diseases. Over the past few decades, an explosion of interest in the use of accessible biofluids to identify and track molecular disease has revolutionized the fields of oncology, prenatal medicine and others. More recently, technological advances in signal detection have allowed for informative analysis of biofluids that are typically sparse in cells and other circulating components, such as CSF. In parallel, advancements in epigenetic profiling have allowed for novel applications of liquid biopsies to diseases without characteristic mutational profiles, including many degenerative, autoimmune, inflammatory, ischaemic and infectious disorders. These events have paved the way for a wide array of neurological conditions to benefit from enhanced diagnostic, prognostic, and treatment abilities through the use of liquid biomarkers: a 'liquid biopsy' approach. This review includes an overview of types of liquid biopsy targets with a focus on circulating cell-free DNA, methods used to identify and probe potential liquid biomarkers, and recent applications of such biomarkers to a variety of complex neurological conditions including CNS tumours, stroke, traumatic brain injury, Alzheimer's disease, epilepsy, multiple sclerosis and neuroinfectious disease. Finally, the challenges of translating liquid biopsies to use in clinical neurology settings-and the opportunities for improvement in disease management that such translation may provide-are discussed.
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Affiliation(s)
- Hallie Gaitsch
- NIH-Oxford-Cambridge Scholars Program, Wellcome-MRC Cambridge Stem Cell Institute and Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 1TN, UK
| | | | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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23
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McMahan C, Dietrich DK, Horne EF, Kelly E, Geannopoulos K, Siyahhan Julnes PS, Ham L, Santamaria U, Lau CY, Wu T, Hsieh HC, Ganesan A, Berjohn C, Kapetanovic S, Reich DS, Nair G, Snow J, Agan BK, Nath A, Smith BR. Neurocognitive Dysfunction With Neuronal Injury in People With HIV on Long-Duration Antiretroviral Therapy. Neurology 2023:WNL.0000000000207339. [PMID: 37105760 DOI: 10.1212/wnl.0000000000207339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 03/09/2023] [Indexed: 04/29/2023] Open
Abstract
BackgroundNeurologic outcomes in people with HIV (PWH) on long-duration antiretroviral therapy (ART) are not fully understood and the underlying pathophysiology is unclear. To address this, we established a cohort of such individuals and compared them to HIV-negative controls using a novel matching technique. Both groups underwent extensive cognitive testing, evaluation for psychiatric measures, and MRI and cerebrospinal fluid (CSF) analyses.MethodsParticipants underwent comprehensive neuropsychological (NP) testing and completed standardized questionnaires measuring depressive symptoms, perceptions of own functioning, and activities of daily living as part of an observational study. Brain MRI and lumbar puncture were optional. Coarsened Exact Matching (CEM) was used to reduce between-group differences in age and sex, and weighted linear/logistic regression models were used to assess the effect of HIV on outcomes.ResultsData were analyzed from 155 PWH on ART for at least 15 years and 100 HIV-negative controls. Compared to controls, PWH scored lower in the domains of attention/working memory (PWH Least Square Mean [LSM]=50.4 vs. controls LSM=53.1, p=0.008) and motor function (44.6 vs. 47.7, p=0.009), and a test of information processing speed (symbol search 30.3 vs. 32.2, p=0.003). They were more likely to self-report a higher number of cognitive difficulties in everyday life (p=0.011). PWH also reported more depressive symptoms, general anxiety, and use of psychiatric medications (all with p<0.05). PWH had reduced proportions of subcortical gray matter on MRI (β=-0.001, p<0.001) and CSF showed elevated levels of neurofilament-light chain (664 vs. 529 pg/mL, p=0.01) and TNF-α (0.229 vs. 0.156 ng/mL, p=0.0008).ConclusionsPWH, despite effective ART for over a decade, displayed neurocognitive deficits and mood abnormalities. MRI and CSF analyses revealed reduced brain volume and signs of ongoing neuronal injury and neuroinflammation. As the already large proportion of virologically controlled PWH continues to grow, longitudinal studies should be conducted to elucidate the implications of cognitive, psychiatric, MRI, and CSF abnormalities in this group.
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Affiliation(s)
- Cynthia McMahan
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Devon K Dietrich
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
| | - Elizabeth F Horne
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Duke University School of Medicine, Durham, NC
| | - Erin Kelly
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Virginia Commonwealth University School of Medicine, Richmond, VA
| | - Katrina Geannopoulos
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Department of Neurology, Case Western Reserve University/University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Peter Selim Siyahhan Julnes
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Lillian Ham
- Office of the Clinical Director, NIMH, NIH, Bethesda, MD
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA
| | | | - Chuen-Yen Lau
- HIV Dynamics and Replication Program, NCI, NIH, Bethesda, MD
| | - Tianxia Wu
- Office of the Clinical Director, NINDS, NIH, Bethesda, MD
| | - Hsing-Chuan Hsieh
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Anuradha Ganesan
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
- Department of Medicine, Uniformed Services University, Bethesda, MD
| | - Catherine Berjohn
- Division of Infectious Diseases, Naval Medical Center San Diego, San Diego, CA
| | - Suad Kapetanovic
- Department of Psychiatry and the Behavioral Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA
| | - Daniel S Reich
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD
| | - Govind Nair
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD
| | - Joseph Snow
- Office of the Clinical Director, NIMH, NIH, Bethesda, MD
| | - Brian K Agan
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
- Department of Medicine, Uniformed Services University, Bethesda, MD
| | - Avindra Nath
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
| | - Bryan R Smith
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
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Donadieu M, Lee NJ, Gaitán MI, Ha SK, Luciano NJ, Roy S, Ineichen BV, Leibovitch EC, Yen CC, Pham DL, Silva AC, Johnson M, Jacobson S, Sati P, Reich DS. In vivo MRI is sensitive to remyelination in a nonhuman primate model of multiple sclerosis. eLife 2023; 12:73786. [PMID: 37083540 PMCID: PMC10171859 DOI: 10.7554/elife.73786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 04/12/2023] [Indexed: 04/22/2023] Open
Abstract
Remyelination is crucial to recover from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral inflammatory demyelinating lesions, we investigated whether MRI is sensitive to, and can characterize, remyelination. In 6 animals followed with multisequence 7-tesla MRI, 31 focal lesions, predicted to be demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in 4 of 6 marmosets and 45% of lesions. Radiological-pathological comparison showed that MRI had high statistical sensitivity (100%) and specificity (90%) for detecting remyelination. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents.
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Affiliation(s)
- Maxime Donadieu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Nathanael J Lee
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - María I Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Seung-Kwon Ha
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
| | - Nicholas J Luciano
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Snehashis Roy
- Section on Neural Function, National Institute of Mental Health, Bethesda, United States
| | - Benjamin V Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Emily C Leibovitch
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Cecil C Yen
- Cerebral Microcirculation Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Dzung L Pham
- Cerebral Microcirculation Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Afonso C Silva
- Cerebral Microcirculation Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Mac Johnson
- Vertex Phamaceuticals Inc, Boston, United States
| | - Steve Jacobson
- Viral immunology section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
| | - Pascal Sati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, United States
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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26
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Fox RJ, Oh J, Arnold D, Turner TJ, Traboulsee A, Reich DS. Données IRM, efficacité et sécurité d’emploi du tolébrutinib chez des patients atteints d’une SEP très active : données à 2 ans de l’étude de sécurité d’emploi à long terme de phase 2b (LTS, Long-Term Safety). Rev Neurol (Paris) 2023. [DOI: 10.1016/j.neurol.2023.01.705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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27
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Bouman PM, Noteboom S, Nobrega Santos FA, Beck ES, Bliault G, Castellaro M, Calabrese M, Chard DT, Eichinger P, Filippi M, Inglese M, Lapucci C, Marciniak A, Moraal B, Morales Pinzon A, Mühlau M, Preziosa P, Reich DS, Rocca MA, Schoonheim MM, Twisk JWR, Wiestler B, Jonkman LE, Guttmann CRG, Geurts JJG, Steenwijk MD. Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection. Radiology 2023; 307:e221425. [PMID: 36749211 PMCID: PMC10102645 DOI: 10.1148/radiol.221425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/18/2022] [Accepted: 11/28/2022] [Indexed: 02/08/2023]
Abstract
Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.
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Affiliation(s)
- Piet M. Bouman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Samantha Noteboom
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Fernando A. Nobrega Santos
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Erin S. Beck
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Gregory Bliault
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Marco Castellaro
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimiliano Calabrese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Declan T. Chard
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paul Eichinger
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Massimo Filippi
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Matilde Inglese
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Caterina Lapucci
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Andrzej Marciniak
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Bastiaan Moraal
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Alfredo Morales Pinzon
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Mark Mühlau
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Paolo Preziosa
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Daniel S. Reich
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Maria A. Rocca
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Menno M. Schoonheim
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jos W. R. Twisk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Benedict Wiestler
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Laura E. Jonkman
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Charles R. G. Guttmann
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Jeroen J. G. Geurts
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
| | - Martijn D. Steenwijk
- From the MS Center Amsterdam, Anatomy & Neurosciences,
Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De
Boelelaan 1117, Amsterdam, the Netherlands (P.M.B., S.N., F.A.N.S., M.M.S.,
J.J.G.G., M.D.S.); Translational Neuroradiology Section, National Institute of
Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Md
(E.S.B., D.S.R.); Department of Neurology, Icahn School of Medicine at Mount
Sinai, New York, NY (E.S.B.); Bio-imaging Institute, University of Bordeaux,
Bordeaux, France (G.B.); Neurology Section, Department of Neuroscience,
Biomedicine and Movement Sciences, University of Verona, Verona, Italy (M.
Castellaro, M. Calabrese); Department of Information Engineering, University of
Padova, Padova, Italy (M. Castellaro); NMR Research Unit, Queen Square MS
Centre, Department of Neuroinflammation, UCL Queen Square Institute of
Neurology, Faculty of Brain Sciences, University College London, London, UK
(D.T.C.); National Institute for Health Research University College London
Hospitals Biomedical Research Centre, London, UK (D.T.C.); Departments of
Neuroradiology (P.E., B.W.) and Neurology (M.M.), School of Medicine, Klinikum
Rechts der Isar, Technical University of Munich, Munich, Germany; Neuroimaging
Research Unit, Division of Neuroscience Neurology Unit, IRCCS San Raffaele
Scientific Institute Vita-Salute San Raffaele University, Milan, Italy (M.F.,
P.P., M.A.R.); Department of Neuroscience, Rehabilitation, Ophthalmology,
Genetics, Maternal and Child Health, University of Genova, Genoa, Italy (M.I.,
C.L.); IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi, Genoa, Italy
(M.I., C.L.); Center for Neurologic Imaging, Department of Radiology, Brigham
and Women’s Hospital, Harvard Medical School, Boston, Mass (A.M., A.M.P.,
C.R.G.G.); Department of Radiology and Nuclear Medicine, MS Center Amsterdam,
Amsterdam Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (B.M.); Department of Epidemiology and Data Science, Amsterdam
University Medical Center, Amsterdam, the Netherlands (J.W.R.T.); Anatomy
& Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands (L.E.J.); and Amsterdam Neuroscience, Brain Imaging and
Neurodegeneration, Amsterdam, the Netherlands (L.E.J.)
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28
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Okar SV, Hu F, Shinohara RT, Beck ES, Reich DS, Ineichen BV. The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis. Front Neurosci 2023; 17:1038011. [PMID: 37065926 PMCID: PMC10098201 DOI: 10.3389/fnins.2023.1038011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
ObjectivesPerivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS.MethodsIn a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy.ResultsFour overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: −0.15 (95%-CI −0.40–0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow.ConclusionCollectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.
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Affiliation(s)
- Serhat V. Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Benjamin V. Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
- *Correspondence: Benjamin V. Ineichen, , ; orcid.org/0000-0003-1362-4819
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29
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Stillman JM, Lopes FM, Lin JP, Hu K, Reich DS, Schafer DP. Lipofuscin-like autofluorescence within microglia and its impact on studying microglial engulfment. bioRxiv 2023:2023.02.28.530224. [PMID: 36909485 PMCID: PMC10002639 DOI: 10.1101/2023.02.28.530224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Engulfment of cellular material and proteins is a key function for microglia, a resident macrophage of the central nervous system (CNS). Among the techniques used to measure microglial engulfment, confocal light microscopy has been used the most extensively. Here, we show that autofluorescence (AF), likely due to lipofuscin and typically associated with aging, can also be detected within microglial lysosomes in the young mouse brain by light microscopy. This lipofuscin-AF signal accumulates first within microglia and increases with age, but it is not exacerbated by amyloid beta-related neurodegeneration. We further show that this lipofuscin-AF signal within microglia can confound the interpretation of antibody-labeled synaptic material within microglia in young adult mice. Finally, we implement a robust strategy to quench AF in mouse, marmoset, and human brain tissue.
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Affiliation(s)
- Jacob M. Stillman
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, Brudnik Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA; University of Massachusetts Chan Morningside Graduate School of Biomedical Sciences, Neuroscience Program, Worcester, MA, USA
| | - Francisco M. Lopes
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Jing-Ping Lin
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kevin Hu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Dorothy P. Schafer
- Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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30
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Ineichen BV, Cananau C, Platt N M, Ouellette R, Moridi T, Frauenknecht KBM, Okar SV, Kulcsar Z, Kockum I, Piehl F, Reich DS, Granberg T. Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis. bioRxiv 2023:2023.02.24.529871. [PMID: 36945422 PMCID: PMC10028816 DOI: 10.1101/2023.02.24.529871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.
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Zurrer WE, Cannon AE, Ewing E, Rosso M, Reich DS, Ineichen BV. Auto-STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications. bioRxiv 2023:2023.02.24.529867. [PMID: 37205453 PMCID: PMC10187249 DOI: 10.1101/2023.02.24.529867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background Systematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain systematic review steps such as data extraction are labour-intensive which hampers their applicability, not least with the rapidly expanding body of biomedical literature. Objective To bridge this gap, we aimed at developing a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n=45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n=31 publications; multiple sclerosis, n=244 publications). Results Our data mining tool Auto-STEED (Automated and STructured Extraction of Experimental Data) was able to extract key experimental parameters such as animal models and species as well as risk of bias items such as randomization or blinding from in vivo studies. Sensitivity and specificity were over 85 and 80%, respectively, for most items in both validation corpora. Accuracy and F-scores were above 90% and 0.9 for most items in the validation corpora. Time savings were above 99%. Conclusions Our developed text mining tool Auto-STEED is able to extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. With this, the tool can be deployed to probe a field in a research improvement context or to replace one human reader during data extraction resulting in substantial time-savings and contribute towards automation of systematic reviews. The function is available on Github.
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Manning AR, Beck ES, Schindler MK, Nair G, Clark KA, Parvathaneni P, Reich DS, Shinohara RT, Solomon AJ. T 1 /T 2 ratio from 3T MRI improves multiple sclerosis cortical lesion contrast. J Neuroimaging 2023; 33:434-445. [PMID: 36715449 PMCID: PMC10175128 DOI: 10.1111/jon.13088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND AND PURPOSE Cortical demyelinated lesions are prevalent in multiple sclerosis (MS), associated with disability, and have recently been incorporated into MS diagnostic criteria. Presently, advanced and ultrahigh-field MRIs-not routinely available in clinical practice-are the most sensitive methods for detection of cortical lesions. Approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need. We plan to assess the sensitivity of the ratio of T1 -weighted and T2 -weighted (T1 /T2 ) signal intensity for focal cortical lesions in comparison to other high-field imaging methods. METHODS 3-Tesla and 7-Tesla MRI collected from 10 adults with MS were included in the study. T1 /T2 images were calculated by dividing 3T T1 -weighted (T1 w) images by 3T T2 -weighted (T2 w) fluid-attenuated inversion recovery images for each participant. A total of 614 cortical lesions were identified using 7T T2 *w and T1 w images and corresponding voxels were assessed on registered 3T images. Signal intensities were compared across 3T imaging sequences, including T1 /T2 , T1 w, T2 w, and inversion recovery susceptibility-weighted imaging with enhanced T2 weighting (IR-SWIET) images. RESULTS T1 /T2 images demonstrated a larger contrast between median lesional and nonlesional cortical signal intensity (median ratio = 1.29, range: 1.19-1.38) when compared to T1 w (1.01, 0.97-1.10, p < .002), T2 w (1.17, 1.07-1.26, p < .002), and IR-SWIET (1.21, 1.01-1.29, p < .03). CONCLUSION T1 /T2 images are sensitive to cortical lesions. Approaches incorporating T1 /T2 could improve the accessibility of cortical lesion detection in research settings and clinical practice.
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Affiliation(s)
- Abigail R Manning
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Matthew K Schindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Kelly A Clark
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Prasanna Parvathaneni
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at The University of Vermont, Burlington, Vermont, USA
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Kuhlmann T, Moccia M, Coetzee T, Cohen JA, Correale J, Graves J, Marrie RA, Montalban X, Yong VW, Thompson AJ, Reich DS. Multiple sclerosis progression: time for a new mechanism-driven framework. Lancet Neurol 2023; 22:78-88. [PMID: 36410373 PMCID: PMC10463558 DOI: 10.1016/s1474-4422(22)00289-7] [Citation(s) in RCA: 99] [Impact Index Per Article: 99.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 05/29/2022] [Accepted: 06/29/2022] [Indexed: 11/20/2022]
Abstract
Traditionally, multiple sclerosis has been categorised by distinct clinical descriptors-relapsing-remitting, secondary progressive, and primary progressive-for patient care, research, and regulatory approval of medications. Accumulating evidence suggests that the clinical course of multiple sclerosis is better considered as a continuum, with contributions from concurrent pathophysiological processes that vary across individuals and over time. The apparent evolution to a progressive course reflects a partial shift from predominantly localised acute injury to widespread inflammation and neurodegeneration, coupled with failure of compensatory mechanisms, such as neuroplasticity and remyelination. Ageing increases neural susceptibility to injury and decreases resilience. These observations encourage a new consideration of the course of multiple sclerosis as a spectrum defined by the relative contributions of overlapping pathological and reparative or compensatory processes. New understanding of key mechanisms underlying progression and measures to quantify progressive pathology will potentially have important and beneficial implications for clinical care, treatment targets, and regulatory decision-making.
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Affiliation(s)
- Tanja Kuhlmann
- Institute of Neuropathology, University Hospital Münster, Münster, Germany; Neuroimmunology Unit, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Marcello Moccia
- Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences, Federico II University of Naples, Naples, Italy
| | - Timothy Coetzee
- National Multiple Sclerosis Society (USA), New York, NY, USA
| | - Jeffrey A Cohen
- Department of Neurology, Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jorge Correale
- Fleni, Department of Neurology, Buenos Aires, Argentina; Institute of Biological Chemistry and Biophysics (IQUIFIB), CONICET/UBA, Buenos Aires, Argentina
| | - Jennifer Graves
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Ruth Ann Marrie
- Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia and Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - V Wee Yong
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Alan J Thompson
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, NIHR University College London Hospitals Biomedical Research Centre, Faculty of Brain Sciences, University College London, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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Daboul L, O'Donnell CM, Cao Q, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi P, Cree BAC, Freeman L, Henry RG, Longbrake EE, Nakamura K, Oh J, Papinutto N, Pelletier D, Samudralwar RD, Suthiphosuwan S, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Ontaneda D, Sati P. Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis. AJR Am J Roentgenol 2023; 220:115-125. [PMID: 35975888 PMCID: PMC10016223 DOI: 10.2214/ajr.22.27731] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.
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Affiliation(s)
- Lynn Daboul
- Department of Neurology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH
| | - Carly M O'Donnell
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Quy Cao
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Moein Amin
- Neurological Institute, Cleveland Clinic, Cleveland, OH
| | | | | | - Christina Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eduardo Caverzasi
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Peter Calabresi
- Department of Neurology, Johns Hopkins University, Baltimore, MD
| | - Bruce A C Cree
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Roland G Henry
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | | | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
| | - Jiwon Oh
- Division of Neurology, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Nico Papinutto
- Department of Neurology, University of California at San Francisco, San Francisco, CA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA
| | - Rohini D Samudralwar
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX
| | - Suradech Suthiphosuwan
- Department of Medical Imaging, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Matthew K Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | | | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
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Ineichen BV, Okar SV, Proulx ST, Engelhardt B, Lassmann H, Reich DS. Perivascular spaces and their role in neuroinflammation. Neuron 2022; 110:3566-3581. [PMID: 36327898 PMCID: PMC9905791 DOI: 10.1016/j.neuron.2022.10.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/17/2022] [Accepted: 10/13/2022] [Indexed: 11/19/2022]
Abstract
It is uncontested that perivascular spaces play critical roles in maintaining homeostasis and priming neuroinflammation. However, despite more than a century of intense research on perivascular spaces, many open questions remain about the anatomical compartment surrounding blood vessels within the CNS. The goal of this comprehensive review is to summarize the literature on perivascular spaces in human neuroinflammation and associated animal disease models. We describe the cell types taking part in the morphological and functional aspects of perivascular spaces and how those spaces can be visualized. Based on this, we propose a model of the cascade of events occurring during neuroinflammatory pathology. We also discuss current knowledge gaps and limitations of the available evidence. An improved understanding of perivascular spaces could advance our comprehension of the pathophysiology of neuroinflammation and open a new therapeutic window for neuroinflammatory diseases such as multiple sclerosis.
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Affiliation(s)
- Benjamin V Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA; Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Center for Reproducible Science, University of Zurich, Zurich, Switzerland.
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven T Proulx
- Theodor Kocher Institute, University of Bern, Bern, Switzerland
| | | | - Hans Lassmann
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Spitalgasse 4, 1090 Vienna, Austria
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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36
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Hemond CC, Baek J, Ionete C, Reich DS. Paramagnetic rim lesions are associated with pathogenic CSF profiles and worse clinical status in multiple sclerosis: A retrospective cross-sectional study. Mult Scler 2022; 28:2046-2056. [PMID: 35748669 PMCID: PMC9588517 DOI: 10.1177/13524585221102921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Paramagnetic rims have been observed as a feature of some multiple sclerosis (MS) lesions on susceptibility-sensitive magnetic resonance imaging (MRI) and indicate compartmentalized inflammation. OBJECTIVE To investigate clinical, MRI, and intrathecal (cerebrospinal fluid, CSF) associations of paramagnetic rim lesions (PRLs) using 3T MRI in MS. METHODS This is a retrospective, cross-sectional analysis. All patients underwent 3T MRI using a T2*-weighted sequence with susceptibility postprocessing (susceptibility-weighted angiography (SWAN) protocol, GE). SWAN-derived filtered-phase maps and corresponding T2-FLAIR images were manually reviewed to determine PRL. Descriptive statistics, t-tests, and regression determined demographic, clinical, MRI, and CSF associations with PRL. RESULTS A total of 147 MS patients were included; 79 of whom had available CSF. Forty-three percent had at least one PRL. PRL status (presence/absence) did not vary by sex or Expanded Disability Status Scale (EDSS) but was associated with younger age, shorter disease duration, worse disease severity, high-efficacy therapy use, and poorer dexterity, as well as lower age-adjusted brain volumes and cognitive processing speeds. PRL status was moreover associated with blood-brain barrier disruption as determined by pathologically elevated albumin quotient. Sensitivity analyses remained supportive of these findings. CONCLUSION PRLs, an emerging noninvasive biomarker of chronic neuroinflammation, are confirmed to be associated with greater disease severity and newly shown to be preliminarily associated with blood-brain barrier disruption.
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Affiliation(s)
- Christopher C. Hemond
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Jonggyu Baek
- Department of Population and Quantitative Health, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Carolina Ionete
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Daniel S. Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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Lin JP, Kelly HM, Song Y, Kawaguchi R, Geschwind DH, Jacobson S, Reich DS. Transcriptomic architecture of nuclei in the marmoset CNS. Nat Commun 2022; 13:5531. [PMID: 36130924 PMCID: PMC9492672 DOI: 10.1038/s41467-022-33140-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/02/2022] [Indexed: 11/11/2022] Open
Abstract
To understand the cellular composition and region-specific specialization of white matter — a disease-relevant, glia-rich tissue highly expanded in primates relative to rodents — we profiled transcriptomes of ~500,000 nuclei from 19 tissue types of the central nervous system of healthy common marmoset and mapped 87 subclusters spatially onto a 3D MRI atlas. We performed cross-species comparison, explored regulatory pathways, modeled regional intercellular communication, and surveyed cellular determinants of neurological disorders. Here, we analyze this resource and find strong spatial segregation of microglia, oligodendrocyte progenitor cells, and astrocytes. White matter glia are diverse, enriched with genes involved in stimulus-response and biomolecule modification, and predicted to interact with other resident cells more extensively than their gray matter counterparts. Conversely, gray matter glia preserve the expression of neural tube patterning genes into adulthood and share six transcription factors that restrict transcriptome complexity. A companion Callithrix jacchus Primate Cell Atlas (CjPCA) is available through https://cjpca.ninds.nih.gov. Studies of cell heterogeneity in white matter in primates have been limited to date. Here the authors describe a marmoset brain cell atlas that bridges rodent and human data, revealing strong gray-white matter glial segregation.
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Affiliation(s)
- Jing-Ping Lin
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Hannah M Kelly
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Yeajin Song
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Riki Kawaguchi
- Psychiatry, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H Geschwind
- Psychiatry, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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Kolb H, Al-Louzi O, Beck ES, Sati P, Absinta M, Reich DS. From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions. Neuroimage Clin 2022; 36:103194. [PMID: 36170753 PMCID: PMC9668624 DOI: 10.1016/j.nicl.2022.103194] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 12/14/2022]
Abstract
Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.
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Affiliation(s)
- Hadar Kolb
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel,Corresponding author at: Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel.
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Institute of Experimental Neurology (INSPE), IRCSS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy,Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
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Arnold TC, Tu D, Okar SV, Nair G, By S, Kawatra KD, Robert-Fitzgerald TE, Desiderio LM, Schindler MK, Shinohara RT, Reich DS, Stein JM. Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions. Neuroimage Clin 2022; 35:103101. [PMID: 35792417 PMCID: PMC9421456 DOI: 10.1016/j.nicl.2022.103101] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 12/25/2022]
Abstract
Paired, same-day, 3T and 64mT MRI studies were analyzed in 33 MS patients. 64mT MRI showed 94% sensitivity for detecting any lesions in 3T confirmed cases. The diameter of the smallest detected lesion was larger at 64mT compared to 3T. Total lesion volume estimates were strongly correlated between 3T and 64mT scans. Portable low-field MRI detects white matter lesions, but smaller lesions may be missed.
Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34–0.5 × 0.34–0.5 × 3–5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = –19.0–15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.
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Affiliation(s)
- T Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danni Tu
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Serhat V Okar
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | | | - Karan D Kawatra
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Timothy E Robert-Fitzgerald
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lisa M Desiderio
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew K Schindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA.
| | - Joel M Stein
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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La Rosa F, Beck ES, Maranzano J, Todea R, van Gelderen P, de Zwart JA, Luciano NJ, Duyn JH, Thiran J, Granziera C, Reich DS, Sati P, Bach Cuadra M. Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI. NMR Biomed 2022; 35:e4730. [PMID: 35297114 PMCID: PMC9539569 DOI: 10.1002/nbm.4730] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/23/2022] [Accepted: 03/14/2022] [Indexed: 05/16/2023]
Abstract
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical Lesion AI-Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5 mm isotropic MP2RAGE acquired four times (MP2RAGE×4), 0.7 mm MP2RAGE, 0.5 mm T2 *-weighted GRE, and 0.5 mm T2 *-weighted EPI. The second dataset consisted of 20 scans including only 0.75 × 0.75 × 0.9 mm3 MP2RAGE. CLAIMS was first evaluated using sixfold cross-validation with single and multi-contrast 0.5 mm MRI input. Second, the performance of the model was tested on 0.7 mm MP2RAGE images after training with either 0.5 mm MP2RAGE×4, 0.7 mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state-of-the-art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGE×4 achieved results comparable to those of the multi-contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain-scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6 μL (lesion-wise detection rate of 71% versus 48%). The proposed framework outperforms previous state-of-the-art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7 T MRI, especially in the field of diagnosis and differential diagnosis of MS patients.
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Erin S. Beck
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Josefina Maranzano
- Department of AnatomyUniversity of Quebec in Trois‐RivièresTrois‐RivièresQuebecCanada
- McConnell Brain Imaging Center, Department of Neurology and NeurosurgeryMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
| | - Ramona‐Alexandra Todea
- Department of Neuroradiology, Clinic of Radiology and Nuclear MedicineUniversity Hospital of BaselBaselSwitzerland
| | - Peter van Gelderen
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jacco A. de Zwart
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Nicholas J. Luciano
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Jeff H. Duyn
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jean‐Philippe Thiran
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Pascal Sati
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCAUSA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
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Abstract
BACKGROUND. Multiple sclerosis (MS) is characterized by both acute and chronic intrathecal inflammation. A subset of MS lesions show paramagnetic rims on susceptibility-weighted MRI sequences, reflecting iron accumulation in microglia. These para-magnetic rim lesions have been proposed as a marker of compartmentalized smoldering disease. Paramagnetic rim lesions have been shown at 7 T and, more recently, at 3 T. As susceptibility effects are weaker at lower field strength, it remains unclear if paramagnetic rim lesions are visible at 1.5 T. OBJECTIVE. The purpose of our study was to compare visualization of paramagnetic rim lesions using susceptibility-weighted imaging at 1.5-T and 3-T MRI in patients with MS. METHODS. This retrospective study included nine patients (five women, four men; mean age, 46.8 years) with MS who underwent both 1.5-T and 3-T MRI using a comparable susceptibility-weighted angiography (SWAN) sequence from the same manufacturer. Lesions measuring greater than 3 mm were annotated. Two reviewers independently assessed images at each field strength in separate sessions and classified the annotated lesions as isointense, diffusely paramagnetic, or paramagnetic rim lesions. Discrepancies were discussed at consensus sessions including a third reviewer. Agreement was assessed using kappa coefficients. RESULTS. Based on the 3-T consensus readings, 115 of 140 annotated lesions (82%) were isointense lesions, 16 (11%) were diffusely paramagnetic lesions, and nine (6%) were paramagnetic rim lesions; based on the 1.5-T consensus readings, 115 (82%) were isointense lesions, 14 (10%) were diffusely paramagnetic lesions, and 11 (8%) were para-magnetic rim lesions. The mean lesion diameter was 11.9 mm for paramagnetic rim lesions versus 6.4 mm for diffusely paramagnetic lesions (p = .006) and 7.8 mm for iso-intense lesions (p = .003). Interrater agreement for lesion classification as a paramagnetic rim lesion was substantial at 1.5 T (κ = 0.65) and 3 T (κ = 0.70). Agreement for paramagnetic rim lesions was also substantial between the consensus readings at the two field strengths (κ = 0.79). CONCLUSION. We show comparable identification of paramagnetic rim lesions at 1.5-T and 3-T MRI with substantial interrater agreement at both field strengths and substantial consensus agreement between the field strengths. CLINICAL IMPACT. Paramagnetic rim lesions may be an emerging marker of chronic neuroinflammation in MS. Their visibility at 1.5 T supports the translational potential of paramagnetic rim lesion identification to more widespread clinical settings, where 1.5-T scanners are prevalent.
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Affiliation(s)
- Christopher C Hemond
- Department of Neurology, University of Massachusetts Medical Center, 55 Lake Ave N, Worcester, MA 01655
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD
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Rahmanzadeh R, Galbusera R, Lu PJ, Bahn E, Weigel M, Barakovic M, Franz J, Nguyen TD, Spincemaille P, Schiavi S, Daducci A, La Rosa F, Absinta M, Sati P, Cuadra MB, Radue EW, Leppert D, Kuhle J, Kappos L, Brück W, Reich DS, Stadelmann C, Wang Y, Granziera C. A new advanced MRI biomarker for remyelinated lesions in Multiple Sclerosis. Ann Neurol 2022; 92:486-502. [PMID: 35713309 PMCID: PMC9527017 DOI: 10.1002/ana.26441] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/12/2022] [Accepted: 06/14/2022] [Indexed: 11/28/2022]
Abstract
Objectives Neuropathological studies have shown that multiple sclerosis (MS) lesions are heterogeneous in terms of myelin/axon damage and repair as well as iron content. However, it remains a challenge to identify specific chronic lesion types, especially remyelinated lesions, in vivo in patients with MS. Methods We performed 3 studies: (1) a cross‐sectional study in a prospective cohort of 115 patients with MS and 76 healthy controls, who underwent 3 T magnetic resonance imaging (MRI) for quantitative susceptibility mapping (QSM), myelin water fraction (MWF), and neurite density index (NDI) maps. White matter (WM) lesions in QSM were classified into 5 QSM lesion types (iso‐intense, hypo‐intense, hyperintense, lesions with hypo‐intense rims, and lesions with paramagnetic rim legions [PRLs]); (2) a longitudinal study of 40 patients with MS to study the evolution of lesions over 2 years; (3) a postmortem histopathology‐QSM validation study in 3 brains of patients with MS to assess the accuracy of QSM classification to identify neuropathological lesion types in 63 WM lesions. Results At baseline, hypo‐ and isointense lesions showed higher mean MWF and NDI values compared to other QSM lesion types (p < 0.0001). Further, at 2‐year follow‐up, hypo‐/iso‐intense lesions showed an increase in MWF. Postmortem analyses revealed that QSM highly accurately identifies (1) fully remyelinated areas as hypo‐/iso‐intense (sensitivity = 88.89% and specificity = 100%), (2) chronic inactive lesions as hyperintense (sensitivity = 71.43% and specificity = 92.00%), and (3) chronic active/smoldering lesions as PRLs (sensitivity = 92.86% and specificity = 86.36%). Interpretation These results provide the first evidence that it is possible to distinguish chronic MS lesions in a clinical setting, hereby supporting with new biomarkers to develop and assess remyelinating treatments. ANN NEUROL 2022;92:486–502
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Affiliation(s)
- Reza Rahmanzadeh
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Erik Bahn
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Matthias Weigel
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jonas Franz
- Institute of Neuropathology, University Medical Center, Göttingen, Germany.,Max Planck Institute for Experimental Medicine, Göttingen, Germany.,Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - David Leppert
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Wolfgang Brück
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA
| | | | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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Al-Louzi O, Manukyan S, Donadieu M, Absinta M, Letchuman V, Calabresi B, Desai P, Beck ES, Roy S, Ohayon J, Pham DL, Thomas A, Jacobson S, Cortese I, Auluck PK, Nair G, Sati P, Reich DS. Lesion size and shape in central vein sign assessment for multiple sclerosis diagnosis: An in vivo and postmortem MRI study. Mult Scler 2022; 28:1891-1902. [PMID: 35674284 DOI: 10.1177/13524585221097560] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied. OBJECTIVE Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis. METHODS Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated. RESULTS CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm3, p = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives). CONCLUSION Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.
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Affiliation(s)
- Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sargis Manukyan
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Maxime Donadieu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD; USA/IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy
| | - Vijay Letchuman
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Brent Calabresi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Parth Desai
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Erin S Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Snehashis Roy
- Section on Neural Function, National Institute of Mental Health, Bethesda, MD, USA
| | - Joan Ohayon
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Dzung L Pham
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Anish Thomas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Irene Cortese
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pavan K Auluck
- Human Brain Collection Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
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Solomon AJ, Arrambide G, Brownlee W, Cross AH, Gaitan MI, Lublin FD, Makhani N, Mowry EM, Reich DS, Rovira À, Weinshenker BG, Cohen JA. Confirming a Historical Diagnosis of Multiple Sclerosis: Challenges and Recommendations. Neurol Clin Pract 2022; 12:263-269. [PMID: 35747540 PMCID: PMC9208427 DOI: 10.1212/cpj.0000000000001149] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 12/14/2021] [Indexed: 11/15/2022]
Abstract
Patients with a historical diagnosis of multiple sclerosis (MS)-a patient presenting with a diagnosis of MS made previously and by a different clinician-present specific diagnostic and therapeutic challenges in clinical practice. Application of the McDonald criteria is most straightforward when applied contemporaneously with a syndrome typical of an MS attack or relapse; however, retrospective application of the criteria in some patients with a historical diagnosis of MS can be problematic. Limited patient recollection of symptoms and evolution of neurologic examination and MRI findings complicate confirmation of an earlier MS diagnosis and assessment of subsequent disease activity or clinical progression. Adequate records for review of prior clinical examinations, laboratory results, and/or MRI scans obtained at the time of diagnosis or during ensuing care may be inadequate or unavailable. This article provides recommendations for a clinical approach to the evaluation of patients with a historical diagnosis of MS to aid diagnostic confirmation, avoid misdiagnosis, and inform therapeutic decision making.
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Affiliation(s)
- Andrew J Solomon
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Georgina Arrambide
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Wallace Brownlee
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Anne H Cross
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - María I Gaitan
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Fred D Lublin
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Naila Makhani
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Ellen M Mowry
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Daniel S Reich
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Àlex Rovira
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Brian G Weinshenker
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
| | - Jeffrey A Cohen
- Department of Neurological Sciences (AJS), Larner College of Medicine at the University of Vermont, University Health Center - Arnold 2, Burlington, VT; Servei de Neurologia-Neuroimmunologia (GA), Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain; National Hospital for Neurology and Neurosurgery (WB), London, United Kingdom; Department of Neurology (AHC), Washington University School of Medicine, St. Louis, MO; Department of Neurology (MIG), Neuroimmunology Section, FLENI, Buenos Aires City, Argentina; The Corinne Goldsmith Dickinson Center for Multiple Sclerosis (FDL), Icahn School of Medicine at Mount Sinai, New York, NY; Departments of Pediatrics and Neurology (NM), Yale School of Medicine, New Haven, CT; Multiple Sclerosis Precision Medicine Center of Excellence (EMM), Johns Hopkins University, Baltimore, MD; Translational Neuroradiology Section (DSR), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD; Section of Neuroradiology (ÀR), Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Department of Neurology (BGW), Mayo Clinic, Rochester, MN; and Mellen Center for MS Treatment and Research (JAC), Neurological Institute, Cleveland Clinic, Cleveland, OH
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Dieckhaus H, Meijboom R, Okar S, Wu T, Parvathaneni P, Mina Y, Chandran S, Waldman AD, Reich DS, Nair G. Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation. Top Magn Reson Imaging 2022; 31:31-39. [PMID: 35767314 PMCID: PMC9258518 DOI: 10.1097/rmr.0000000000000296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 05/24/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data. MATERIALS AND METHODS C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison. RESULTS C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class. CONCLUSIONS These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF.
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Affiliation(s)
- Henry Dieckhaus
- qMRI Core Facility, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Serhat Okar
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Tianxia Wu
- Clinical Trials Unit, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Prasanna Parvathaneni
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Yair Mina
- Viral Immunology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
- Sackler Faculty of Medicine, Tel Aviv University, Israel
| | | | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Daniel S. Reich
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- qMRI Core Facility, NINDS, National Institutes of Health, Bethesda, MD, USA
- Corresponding Author: Govind Nair, Room 5C440, 10 Center Drive, Bethesda MD 20892, ; 301-402-6391
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Rovira À, Traboulsee A, Reich DS, Wattjes MP. The reality of multiple sclerosis assessment in middle-income countries – Authors' reply. Lancet Neurol 2022; 21:215-216. [DOI: 10.1016/s1474-4422(22)00041-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/20/2022] [Accepted: 01/27/2022] [Indexed: 10/19/2022]
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Ma Z, Reich DS, Dembling S, Duyn JH, Koretsky AP. Cover Image. Hum Brain Mapp 2022. [DOI: 10.1002/hbm.25488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Al-Louzi O, Letchuman V, Manukyan S, Beck ES, Roy S, Ohayon J, Pham DL, Cortese I, Sati P, Reich DS. Central Vein Sign Profile of Newly Developing Lesions in Multiple Sclerosis: A 3-Year Longitudinal Study. Neurol Neuroimmunol Neuroinflamm 2022; 9:9/2/e1120. [PMID: 35027474 PMCID: PMC8759076 DOI: 10.1212/nxi.0000000000001120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 10/22/2021] [Indexed: 12/28/2022]
Abstract
BACKGROUND AND OBJECTIVES The central vein sign (CVS), a central linear hypointensity within lesions on T2*-weighted imaging, has been established as a sensitive and specific biomarker for the diagnosis of multiple sclerosis (MS). However, the CVS has not yet been comprehensively studied in newly developing MS lesions. We aimed to identify the CVS profiles of new white matter lesions in patients with MS followed over time and investigate demographic and clinical risk factors associated with new CVS+ or CVS- lesion development. METHODS In this retrospective longitudinal cohort study, adults from the NIH MS Natural History Study were considered for inclusion. Participants with new T2 or enhancing lesions were identified through review of the radiology report and/or longitudinal subtraction imaging. Each new lesion was evaluated for the CVS. Clinical characteristics were identified through chart review. RESULTS A total of 153 adults (95 relapsing-remitting MS, 27 secondary progressive MS, 16 primary progressive MS, 5 clinically isolated syndrome, and 10 healthy; 67% female) were included. Of this cohort, 96 had at least 1 new T2 or contrast-enhancing lesion during median 3.1 years (Q1-Q3: 0.7-6.3) of follow-up; lesions eligible for CVS evaluation were found in 62 (65%). Of 233 new CVS-eligible lesions, 159 (68%) were CVS+, with 30 (48%) individuals having only CVS+, 12 (19%) only CVS-, and 20 (32%) both CVS+ and CVS- lesions. In gadolinium-enhancing (Gd+) lesions, the CVS+ percentage increased from 102/152 (67%) at the first time point where the lesion was observed, to 92/114 (82%) after a median follow-up of 2.8 years. Younger age (OR = 0.5 per 10-year increase, 95% CI = 0.3-0.8) and higher CVS+ percentage at baseline (OR = 1.4 per 10% increase, 95% CI = 1.1-1.9) were associated with increased likelihood of new CVS+ lesion development. DISCUSSION In a cohort of adults with MS followed over a median duration of 3 years, most newly developing T2 or enhancing lesions were CVS+ (68%), and nearly half (48%) developed new CVS+ lesions only. Importantly, the effects of edema and T2 signal changes can obscure small veins in Gd+ lesions; therefore, caution and follow-up is necessary when determining their CVS status. TRIAL REGISTRATION INFORMATION Clinical trial registration number NCT00001248. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that younger age and higher CVS+ percentage at baseline are associated with new CVS+ lesion development.
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Affiliation(s)
- Omar Al-Louzi
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Vijay Letchuman
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Sargis Manukyan
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Erin S Beck
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Snehashis Roy
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Joan Ohayon
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Dzung L Pham
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Irene Cortese
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Pascal Sati
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Daniel S Reich
- From the Translational Neuroradiology Section (O.A.-L., V.L., S.M., E.S.B., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; Department of Neurology (O.A.-L., P.S.), Cedars-Sinai Medical Center, Los Angeles, CA; Section on Neural Function (S.R.), National Institute of Mental Health, NIH, Bethesda, MD; Neuroimmunology Clinic (J.O., I.C.), National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD; and Center for Neuroscience and Regenerative Medicine (D.L.P.), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD.
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Beck ES, Maranzano J, Luciano NJ, Parvathaneni P, Filippini S, Morrison M, Suto DJ, Wu T, van Gelderen P, de Zwart JA, Antel S, Fetco D, Ohayon J, Andrada F, Mina Y, Thomas C, Jacobson S, Duyn J, Cortese I, Narayanan S, Nair G, Sati P, Reich DS. Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis. Mult Scler 2022; 28:1351-1363. [PMID: 35142571 DOI: 10.1177/13524585211069167] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course. OBJECTIVE Characterize cortical lesions by 7 tesla (T) T2*-/T1-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability. METHODS Sixty-four adults with MS (45 relapsing-remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing. RESULTS Cortical lesions were found in 94% (progressive: median 56/range 2-203; relapsing-remitting: 15/0-168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform (p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated (r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated (r = 0.30, p = 0.002). Leukocortical (p = 0.02) but not subpial lesions (p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions (p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores. CONCLUSION Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.
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Affiliation(s)
- Erin S Beck
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Department of Anatomy, University of Quebec in Trois-Rivières, Trois-Rivières, QC, Canada
| | - Nicholas J Luciano
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Prasanna Parvathaneni
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Stefano Filippini
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Department of Neurosciences, Drug and Child Health, University of Florence, Florence, Italy
| | - Mark Morrison
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel J Suto
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Tianxia Wu
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Peter van Gelderen
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jacco A de Zwart
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Samson Antel
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Dumitru Fetco
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Joan Ohayon
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Frances Andrada
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Yair Mina
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Chevaz Thomas
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Steve Jacobson
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jeff Duyn
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Irene Cortese
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Pascal Sati
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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