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Nguyen P, Rempe T, Forghani R. Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting. Magn Reson Imaging Clin N Am 2024; 32:363-374. [PMID: 38555146 DOI: 10.1016/j.mric.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.
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Affiliation(s)
- Phuong Nguyen
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA
| | - Torge Rempe
- Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA
| | - Reza Forghani
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Division of Movement Disorders, Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA; Division of Medical Physics, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Room 221.1, 3011 SW Williston Road, Gainesville, FL 32608, USA.
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2
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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 : THE PREPRINT SERVER FOR HEALTH SCIENCES 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] [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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Gill AJ, Schorr EM, Gadani SP, Calabresi PA. Emerging imaging and liquid biomarkers in multiple sclerosis. Eur J Immunol 2023; 53:e2250228. [PMID: 37194443 PMCID: PMC10524168 DOI: 10.1002/eji.202250228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/10/2023] [Accepted: 05/12/2023] [Indexed: 05/18/2023]
Abstract
The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.
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Affiliation(s)
- Alexander J. Gill
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Emily M. Schorr
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Sachin P. Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
- Department of Neuroscience, Baltimore, MD, US
- Department of Ophthalmology, Baltimore, MD, US
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Homssi M, Sweeney EM, Demmon E, Mannheim W, Sakirsky M, Wang Y, Gauthier SA, Gupta A, Nguyen TD. Evaluation of the Statistical Detection of Change Algorithm for Screening Patients with MS with New Lesion Activity on Longitudinal Brain MRI. AJNR Am J Neuroradiol 2023; 44:649-655. [PMID: 37142431 PMCID: PMC10249703 DOI: 10.3174/ajnr.a7858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 04/03/2023] [Indexed: 05/06/2023]
Abstract
BACKGROUND AND PURPOSE Identification of new MS lesions on longitudinal MR imaging by human readers is time-consuming and prone to error. Our objective was to evaluate the improvement in the performance of subject-level detection by readers when assisted by the automated statistical detection of change algorithm. MATERIALS AND METHODS A total of 200 patients with MS with a mean interscan interval of 13.2 (SD, 2.4) months were included. Statistical detection of change was applied to the baseline and follow-up FLAIR images to detect potential new lesions for confirmation by readers (Reader + statistical detection of change method). This method was compared with readers operating in the clinical workflow (Reader method) for a subject-level detection of new lesions. RESULTS Reader + statistical detection of change found 30 subjects (15.0%) with at least 1 new lesion, while Reader detected 16 subjects (8.0%). As a subject-level screening tool, statistical detection of change achieved a perfect sensitivity of 1.00 (95% CI, 0.88-1.00) and a moderate specificity of 0.67 (95% CI, 0.59-0.74). The agreement on a subject level was 0.91 (95% CI, 0.87-0.95) between Reader + statistical detection of change and Reader, and 0.72 (95% CI, 0.66-0.78) between Reader + statistical detection of change and statistical detection of change. CONCLUSIONS The statistical detection of change algorithm can serve as a time-saving screening tool to assist human readers in verifying 3D FLAIR images of patients with MS with suspected new lesions. Our promising results warrant further evaluation of statistical detection of change in prospective multireader clinical studies.
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Affiliation(s)
- M Homssi
- From the Department of Radiology (M.H., Y.W., A.G., T.D.N.)
| | - E M Sweeney
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center, Department of Biostatistics, Epidemiology, and Informatics (E.M.S.), University of Pennsylvania, Philadelphia, Pennsylvania
| | - E Demmon
- Department of Neurology (E.D., W.M., M.S., S.A.G.)
| | - W Mannheim
- Department of Neurology (E.D., W.M., M.S., S.A.G.)
| | - M Sakirsky
- Department of Neurology (E.D., W.M., M.S., S.A.G.)
| | - Y Wang
- From the Department of Radiology (M.H., Y.W., A.G., T.D.N.)
| | - S A Gauthier
- Department of Neurology (E.D., W.M., M.S., S.A.G.)
- The Feil Family Brain & Mind Institute (S.A.G.), Weill Cornell Medicine, New York, New York
| | - A Gupta
- From the Department of Radiology (M.H., Y.W., A.G., T.D.N.)
| | - T D Nguyen
- From the Department of Radiology (M.H., Y.W., A.G., T.D.N.)
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5
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Mainero C, Treaba CA, Barbuti E. Imaging cortical lesions in multiple sclerosis. Curr Opin Neurol 2023; 36:222-228. [PMID: 37078649 DOI: 10.1097/wco.0000000000001152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
PURPOSE OF REVIEW Cortical lesions are an established pathological feature of multiple sclerosis, develop from the earliest disease stages and contribute to disease progression. Here, we discuss current imaging approaches for detecting cortical lesions in vivo and their contribution for improving our understanding of cortical lesion pathogenesis as well as their clinical significance. RECENT FINDINGS Although a variable portion of cortical lesions goes undetected at clinical field strength and even at ultra-high field MRI, their evaluation is still clinically relevant. Cortical lesions are important for differential multiple sclerosis (MS) diagnosis, have relevant prognostic value and independently predict disease progression. Some studies also show that cortical lesion assessment could be used as a therapeutic outcome target in clinical trials. Advances in ultra-high field MRI not only allow increased cortical lesion detection in vivo but also the disclosing of some interesting features of cortical lesions related to their pattern of development and evolution as well to the nature of associated pathological changes, which might prove relevant for better understanding the pathogenesis of these lesions. SUMMARY Despite some limitations, imaging of cortical lesions is of paramount importance in MS for elucidating disease mechanisms as well as for improving patient management in clinic.
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Affiliation(s)
- Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elena Barbuti
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Ospedale Sant'Andrea, University "La Sapienza", Rome, Italy
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Accelerated Simultaneous T 2 and T 2* Mapping of Multiple Sclerosis Lesions Using Compressed Sensing Reconstruction of Radial RARE-EPI MRI. Tomography 2023; 9:299-314. [PMID: 36828376 PMCID: PMC9960840 DOI: 10.3390/tomography9010024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 02/04/2023] Open
Abstract
(1) Background: Radial RARE-EPI MRI facilitates simultaneous T2 and T2* mapping (2in1-RARE-EPI). With modest undersampling (R = 2), the speed gain of 2in1-RARE-EPI relative to Multi-Spin-Echo and Multi-Gradient-Recalled-Echo references is limited. Further reduction in scan time is crucial for clinical studies investigating T2 and T2* as imaging biomarkers. We demonstrate the feasibility of further acceleration, utilizing compressed sensing (CS) reconstruction of highly undersampled 2in1-RARE-EPI. (2) Methods: Two-fold radially-undersampled 2in1-RARE-EPI data from phantoms, healthy volunteers (n = 3), and multiple sclerosis patients (n = 4) were used as references, and undersampled (Rextra = 1-12, effective undersampling Reff = 2-24). For each echo time, images were reconstructed using CS-reconstruction. For T2 (RARE module) and T2* mapping (EPI module), a linear least-square fit was applied to the images. T2 and T2* from CS-reconstruction of undersampled data were benchmarked against values from CS-reconstruction of the reference data. (3) Results: We demonstrate accelerated simultaneous T2 and T2* mapping using undersampled 2in1-RARE-EPI with CS-reconstruction is feasible. For Rextra = 6 (TA = 01:39 min), the overall MAPE was ≤8% (T2*) and ≤4% (T2); for Rextra = 12 (TA = 01:06 min), the overall MAPE was <13% (T2*) and <5% (T2). (4) Conclusion: Substantial reductions in scan time are achievable for simultaneous T2 and T2* mapping of the brain using highly undersampled 2in1-RARE-EPI with CS-reconstruction.
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Conti A, Treaba CA, Mehndiratta A, Barletta VT, Mainero C, Toschi N. An Interpretable Machine Learning Model to Predict Cortical Atrophy in Multiple Sclerosis. Brain Sci 2023; 13:brainsci13020198. [PMID: 36831740 PMCID: PMC9954500 DOI: 10.3390/brainsci13020198] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/14/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
To date, the relationship between central hallmarks of multiple sclerosis (MS), such as white matter (WM)/cortical demyelinated lesions and cortical gray matter atrophy, remains unclear. We investigated the interplay between cortical atrophy and individual lesion-type patterns that have recently emerged as new radiological markers of MS disease progression. We employed a machine learning model to predict mean cortical thinning in whole-brain and single hemispheres in 150 cortical regions using demographic and lesion-related characteristics, evaluated via an ultrahigh field (7 Tesla) MRI. We found that (i) volume and rimless (i.e., without a "rim" of iron-laden immune cells) WM lesions, patient age, and volume of intracortical lesions have the most predictive power; (ii) WM lesions are more important for prediction when their load is small, while cortical lesion load becomes more important as it increases; (iii) WM lesions play a greater role in the progression of atrophy during the latest stages of the disease. Our results highlight the intricacy of MS pathology across the whole brain. In turn, this calls for multivariate statistical analyses and mechanistic modeling techniques to understand the etiopathogenesis of lesions.
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Affiliation(s)
- Allegra Conti
- Department of Biomedicine and Prevention, University of Rome ‘Tor Vergata’, Via Montpellier 1, 00133 Rome, Italy
- Correspondence: ; Tel.: +39-06-72596393
| | - Constantina Andrada Treaba
- Massachusetts General Hospital, Boston, MA 02114, USA
- A. A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
| | - Ambica Mehndiratta
- Massachusetts General Hospital, Boston, MA 02114, USA
- A. A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
| | - Valeria Teresa Barletta
- Massachusetts General Hospital, Boston, MA 02114, USA
- A. A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
| | - Caterina Mainero
- Massachusetts General Hospital, Boston, MA 02114, USA
- A. A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome ‘Tor Vergata’, Via Montpellier 1, 00133 Rome, Italy
- Massachusetts General Hospital, Boston, MA 02114, USA
- A. A. Martinos Center for Biomedical Imaging, Boston, MA 02129, USA
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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] [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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9
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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] [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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10
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Tagge IJ, Leppert IR, Fetco D, Campbell JS, Rudko DA, Brown RA, Stikov N, Pike GB, Giacomini PS, Arnold DL, Narayanan S. Permanent tissue damage in multiple sclerosis lesions is associated with reduced pre-lesion myelin and axon volume fractions. Mult Scler 2022; 28:2027-2037. [PMID: 35903888 PMCID: PMC9574230 DOI: 10.1177/13524585221110585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND The use of advanced magnetic resonance imaging (MRI) techniques in MS research has led to new insights in lesion evolution and disease outcomes. It has not yet been determined if, or how, pre-lesional abnormalities in normal-appearing white matter (NAWM) relate to the long-term evolution of new lesions. OBJECTIVE To investigate the relationship between abnormalities in MRI measures of axonal and myelin volume fractions (AVF and MVF) in NAWM preceding development of black-hole (BH) and non-BH lesions in people with MS. METHODS We obtained magnetization transfer and diffusion MRI at 6-month intervals in patients with MS to estimate MVF and AVF during lesion evolution. Lesions were classified as either BH or non-BH on the final imaging visit using T1 maps. RESULTS Longitudinal data from 97 new T2 lesions from 9 participants were analyzed; 25 lesions in 8 participants were classified as BH 6-12 months after initial appearance. Pre-lesion MVF, AVF, and MVF/AVF were significantly lower, and T1 was significantly higher, in the lesions that later became BHs (p < 0.001) compared to those that did not. No significant pre-lesion abnormalities were found in non-BH lesions (p > 0.05). CONCLUSION The present work demonstrated that pre-lesion abnormalities are associated with worse long-term lesion-level outcome.
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Affiliation(s)
- Ian J Tagge
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Dumitru Fetco
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Jennifer Sw Campbell
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - David A Rudko
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Robert A Brown
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Nikola Stikov
- Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Paul S Giacomini
- Neurology and Neurosurgery, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Center, Montreal Neurological Institute & Hospital, Montreal, QC, Canada
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11
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York EN, Thrippleton MJ, Meijboom R, Hunt DPJ, Waldman AD. Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis. Brain Commun 2022; 4:fcac088. [PMID: 35652121 PMCID: PMC9149789 DOI: 10.1093/braincomms/fcac088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/17/2021] [Accepted: 03/31/2022] [Indexed: 11/28/2022] Open
Abstract
Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.
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Affiliation(s)
- Elizabeth N. York
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | | | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic,
University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
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12
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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: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [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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13
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Runge VM, Heverhagen JT. The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T. Invest Radiol 2022; 57:1-12. [PMID: 34510100 DOI: 10.1097/rli.0000000000000824] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
ABSTRACT This review provides a balanced perspective regarding the clinical utility of magnetic resonance systems across the range of field strengths for which current state-of-the-art units exist (0.55 T, 1.5 T, 3 T, and 7 T). Guidance regarding this issue is critical to appropriate purchasing, usage, and further dissemination of this important imaging modality, both in the industrial world and in developing nations. The review serves to provide an important update, although to a large extent this information has never previously been openly presented. In that sense, it serves also as a position paper, with statements and recommendations as appropriate.
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Affiliation(s)
- Val M Runge
- From the Department of Diagnostic, Interventional, and Pediatric Radiology, University Hospital of Bern, Inselspital, University of Bern, Bern, Switzerland
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14
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Boshkovski T, Cohen-Adad J, Misic B, Arnulf I, Corvol JC, Vidailhet M, Lehéricy S, Stikov N, Mancini M. The Myelin-Weighted Connectome in Parkinson's Disease. Mov Disord 2021; 37:724-733. [PMID: 34936123 PMCID: PMC9303520 DOI: 10.1002/mds.28891] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 01/26/2023] Open
Abstract
Background Even though Parkinson's disease (PD) is typically viewed as largely affecting gray matter, there is growing evidence that there are also structural changes in the white matter. Traditional connectomics methods that study PD may not be specific to underlying microstructural changes, such as myelin loss. Objective The primary objective of this study is to investigate the PD‐induced changes in myelin content in the connections emerging from the basal ganglia and the brainstem. For the weighting of the connectome, we used the longitudinal relaxation rate as a biologically grounded myelin‐sensitive metric. Methods We computed the myelin‐weighted connectome in 35 healthy control subjects and 81 patients with PD. We used partial least squares to highlight the differences between patients with PD and healthy control subjects. Then, a ring analysis was performed on selected brainstem and subcortical regions to evaluate each node's potential role as an epicenter for disease propagation. Then, we used behavioral partial least squares to relate the myelin alterations with clinical scores. Results Most connections (~80%) emerging from the basal ganglia showed a reduced myelin content. The connections emerging from potential epicentral nodes (substantia nigra, nucleus basalis of Meynert, amygdala, hippocampus, and midbrain) showed significant decrease in the longitudinal relaxation rate (P < 0.05). This effect was not seen for the medulla and the pons. Conclusions The myelin‐weighted connectome was able to identify alteration of the myelin content in PD in basal ganglia connections. This could provide a different view on the importance of myelination in neurodegeneration and disease progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
| | - Julien Cohen-Adad
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada.,Mila - Quebec AI Institute, Montréal, Quebec, Canada.,Functional Neuroimaging Unit, Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada
| | | | - Isabelle Arnulf
- Sorbonne Université, Paris Brain Institute - ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Paris Brain Institute - ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Marie Vidailhet
- Sorbonne Université, Paris Brain Institute - ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Stéphane Lehéricy
- Sorbonne Université, Paris Brain Institute - ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Hôpital Pitié-Salpêtrière, Paris, France
| | - Nikola Stikov
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada.,Montreal Heart Institute, Montréal, Quebec, Canada
| | - Matteo Mancini
- NeuroPoly Lab, Polytechnique Montréal, Montréal, Quebec, Canada.,Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom.,Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
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15
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Ineichen BV, Beck ES, Piccirelli M, Reich DS. New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis. Invest Radiol 2021; 56:773-784. [PMID: 34120128 PMCID: PMC8505164 DOI: 10.1097/rli.0000000000000804] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 05/09/2021] [Accepted: 05/09/2021] [Indexed: 11/26/2022]
Abstract
ABSTRACT There is growing interest in imaging multiple sclerosis (MS) through the ultra-high-field (UHF) lens, which currently means a static magnetic field strength of 7 T or higher. Because of higher signal-to-noise ratio and enhanced susceptibility effects, UHF magnetic resonance imaging improves conspicuity of MS pathological hallmarks, among them cortical demyelination and the central vein sign. This could, in turn, improve confidence in MS diagnosis and might also facilitate therapeutic monitoring of MS patients. Furthermore, UHF imaging offers unique insight into iron-related pathology, leptomeningeal inflammation, and spinal cord pathologies in neuroinflammation. Yet, limitations such as the longer scanning times to achieve improved resolution and incipient safety data on implanted medical devices need to be considered. In this review, we discuss applications of UHF imaging in MS, its advantages and limitations, and practical aspects of UHF in the clinical setting.
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Affiliation(s)
- Benjamin V. Ineichen
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Erin S. Beck
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Daniel S. Reich
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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16
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Treaba CA, Conti A, Klawiter EC, Barletta VT, Herranz E, Mehndiratta A, Russo AW, Sloane JA, Kinkel RP, Toschi N, Mainero C. Cortical and phase rim lesions on 7 T MRI as markers of multiple sclerosis disease progression. Brain Commun 2021; 3:fcab134. [PMID: 34704024 DOI: 10.1093/braincomms/fcab134] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Indexed: 11/14/2022] Open
Abstract
In multiple sclerosis, individual lesion-type patterns on magnetic resonance imaging might be valuable for predicting clinical outcome and monitoring treatment effects. Neuropathological and imaging studies consistently show that cortical lesions contribute to disease progression. The presence of chronic active white matter lesions harbouring a paramagnetic rim on susceptibility-weighted magnetic resonance imaging has also been associated with an aggressive form of multiple sclerosis. It is, however, still uncertain how these two types of lesions relate to each other, or which one plays a greater role in disability progression. In this prospective, longitudinal study in 100 multiple sclerosis patients (74 relapsing-remitting, 26 secondary progressive), we used ultra-high field 7-T susceptibility imaging to characterize cortical and rim lesion presence and evolution. Clinical evaluations were obtained over a mean period of 3.2 years in 71 patients, 46 of which had a follow-up magnetic resonance imaging. At baseline, cortical and rim lesions were identified in 96% and 63% of patients, respectively. Rim lesion prevalence was similar across disease stages. Patients with rim lesions had higher cortical and overall white matter lesion load than subjects without rim lesions (P = 0.018-0.05). Altogether, cortical lesions increased by both count and volume (P = 0.004) over time, while rim lesions expanded their volume (P = 0.023) whilst lacking new rim lesions; rimless white matter lesions increased their count but decreased their volume (P = 0.016). We used a modern machine learning algorithm based on extreme gradient boosting techniques to assess the cumulative power as well as the individual importance of cortical and rim lesion types in predicting disease stage and disability progression, alongside with more traditional imaging markers. The most influential imaging features that discriminated between multiple sclerosis stages (area under the curve±standard deviation = 0.82 ± 0.08) included, as expected, the normalized white matter and thalamic volume, white matter lesion volume, but also leukocortical lesion volume. Subarachnoid cerebrospinal fluid and leukocortical lesion volumes, along with rim lesion volume were the most important predictors of Expanded Disability Status Scale progression (area under the curve±standard deviation = 0.69 ± 0.12). Taken together, these results indicate that while cortical lesions are extremely frequent in multiple sclerosis, rim lesion development occurs only in a subset of patients. Both, however, persist over time and relate to disease progression. Their combined assessment is needed to improve the ability of identifying multiple sclerosis patients at risk of progressing disease.
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Affiliation(s)
- Constantina A Treaba
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Allegra Conti
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome 00133, Italy
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Valeria T Barletta
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Elena Herranz
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Ambica Mehndiratta
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
| | - Andrew W Russo
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Jacob A Sloane
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | | | - Nicola Toschi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA.,Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome 00133, Italy
| | - Caterina Mainero
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA.,Harvard Medical School, Boston, MA 02115, USA
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17
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Madsen MAJ, Wiggermann V, Bramow S, Christensen JR, Sellebjerg F, Siebner HR. Imaging cortical multiple sclerosis lesions with ultra-high field MRI. NEUROIMAGE-CLINICAL 2021; 32:102847. [PMID: 34653837 PMCID: PMC8517925 DOI: 10.1016/j.nicl.2021.102847] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/19/2021] [Accepted: 08/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Cortical lesions are abundant in multiple sclerosis (MS), yet difficult to visualize in vivo. Ultra-high field (UHF) MRI at 7 T and above provides technological advances suited to optimize the detection of cortical lesions in MS. PURPOSE To provide a narrative and quantitative systematic review of the literature on UHF MRI of cortical lesions in MS. METHODS A systematic search of all literature on UHF MRI of cortical lesions in MS published before September 2020. Quantitative outcome measures included cortical lesion numbers reported using 3 T and 7 T MRI and between 7 T MRI sequences, along with sensitivity of UHF MRI towards cortical lesions verified by histopathology. RESULTS 7 T MRI detected on average 52 ± 26% (mean ± 95% confidence interval) more cortical lesions than the best performing image contrast at 3 T, with the largest increase in type II-IV intracortical lesion detection. Across all studies, the mean cortical lesion number was 17 ± 6 per patient. In progressive MS cohorts, approximately four times more cortical lesions were reported than in CIS/early RRMS, and RRMS. Yet, there was no difference in lesion type ratio between these MS subtypes. Furthermore, superiority of one MRI sequence over another could not be established from available data. Post-mortem lesion detection with UHF MRI agreed only modestly with pathological examinations. Mean pro- and retrospective sensitivity was 33 ± 6% and 71 ± 10%, respectively, with the highest sensitivity towards type I and type IV lesions. CONCLUSION UHF MRI improves cortical lesion detection in MS considerably compared to 3 T MRI, particularly for type II-IV lesions. Despite modest sensitivity, 7 T MRI is still capable of visualizing all aspects of cortical lesion pathology and could potentially aid clinicians in diagnosing and monitoring MS, and progressive MS in particular. However, standardization of acquisition and segmentation protocols is needed.
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Affiliation(s)
- Mads A J Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark.
| | - Vanessa Wiggermann
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark
| | - Stephan Bramow
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Jeppe Romme Christensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital - Bispebjerg, Bispebjerg Bakke 23, 2400 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
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18
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Shadmani G, Simkins TJ, Assadsangabi R, Apperson M, Hacein-Bey L, Raslan O, Ivanovic V. Autoimmune diseases of the brain, imaging and clinical review. Neuroradiol J 2021; 35:152-169. [PMID: 34490814 DOI: 10.1177/19714009211042879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
There is an extensive spectrum of autoimmune entities that can involve the central nervous system, which has expanded with the emergence of new imaging modalities and several clinicopathologic entities. Clinical presentation is usually non-specific, and imaging has a critical role in the workup of these diseases. Immune-mediated diseases of the brain are not common in daily practice for radiologists and, except for a few of them such as multiple sclerosis, there is a vague understanding about differentiating them from each other based on the radiological findings. In this review, we aim to provide a practical diagnostic approach based on the unique radiological findings for each disease. We hope our diagnostic approach will help radiologists expand their basic understanding of the discussed disease entities and narrow the differential diagnosis in specific clinical scenarios. An understanding of unique imaging features of these disorders, along with laboratory evaluation, may enable clinicians to decrease the need for tissue biopsy.
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Affiliation(s)
- Ghazal Shadmani
- Department of Radiology, Section of Neuroradiology, University of California Davis Medical Center, USA
| | - Tyrell J Simkins
- Department of Neurology (Neuroimmunulogy), University of California Davis Medical center, USA
| | - Reza Assadsangabi
- Department of Radiology, Section of Neuroradiology, University of California Davis Medical Center, USA
| | - Michelle Apperson
- Department of Neurology (Neuroimmunulogy), University of California Davis Medical center, USA
| | - Lotfi Hacein-Bey
- Department of Radiology, Section of Neuroradiology, University of California Davis Medical Center, USA
| | - Osama Raslan
- Department of Radiology, Section of Neuroradiology, University of California Davis Medical Center, USA
| | - Vladimir Ivanovic
- Department of Radiology, Section of Neuroradiology, University of California Davis Medical Center, USA
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19
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Vachha B, Huang SY. MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond. Eur Radiol Exp 2021; 5:35. [PMID: 34435246 PMCID: PMC8387544 DOI: 10.1186/s41747-021-00216-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/30/2021] [Indexed: 12/12/2022] Open
Abstract
Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.
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Affiliation(s)
- Behroze Vachha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, 10065, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 13th Street, Room 2301, Charlestown, MA, 02129, USA.
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20
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Mizell R, Chen H, Lambe J, Saidha S, Harrison DM. Association of retinal atrophy with cortical lesions and leptomeningeal enhancement in multiple sclerosis on 7T MRI. Mult Scler 2021; 28:393-405. [PMID: 34125629 DOI: 10.1177/13524585211023343] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Retinal atrophy in multiple sclerosis (MS) as measured by optical coherence tomography (OCT) correlates with demyelinating lesions and brain atrophy, but its relationship with cortical lesions (CLs) and meningeal inflammation is not well known. OBJECTIVES To evaluate the relationship of retinal layer atrophy with leptomeningeal enhancement (LME) and CLs in MS as visualized on 7 Tesla (7T) magnetic resonance imaging (MRI). METHODS Forty participants with MS underwent 7T MRI of the brain and OCT. Partial correlation and mixed-effects regression evaluated relationships between MRI and OCT findings. RESULTS All participants had CLs and 32 (80%) participants had LME on post-contrast MRI. Ganglion cell/inner plexiform layer (GCIPL) thickness correlated with total CL volume (r =-0.45, p < 0.01). Participants with LME at baseline had thinner macular retinal nerve fiber layer (mRNFL; p = 0.01) and GCIPL (p < 0.01). Atrophy in various retinal layers was faster in those with certain patterns of LME. For example, mRNFL declined -1.113 (-1.974, -0.252) μm/year faster in those with spread/fill-pattern LME foci at baseline compared with those without (p = 0.01). CONCLUSION This study associates MRI findings of LME and cortical pathology with thinning of retinal layers as measured by OCT, suggesting a common link between meningeal inflammation, CLs, and retinal atrophy in MS.
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Affiliation(s)
- Ryan Mizell
- Baltimore VA Medical Center, Baltimore, MD, USA/University of Maryland Medical Center, Baltimore, MD, USA
| | - Hegang Chen
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeffrey Lambe
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shiv Saidha
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel M Harrison
- Baltimore VA Medical Center, Baltimore, MD, USA/University of Maryland Medical Center, Baltimore, MD, USA/Johns Hopkins University School of Medicine, Baltimore, MD, USA/Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
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21
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Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, Fazekas F, Filippi M, Frederiksen J, Gasperini C, Hacohen Y, Kappos L, Li DKB, Mankad K, Montalban X, Newsome SD, Oh J, Palace J, Rocca MA, Sastre-Garriga J, Tintoré M, Traboulsee A, Vrenken H, Yousry T, Barkhof F, Rovira À. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 2021; 20:653-670. [PMID: 34139157 DOI: 10.1016/s1474-4422(21)00095-8] [Citation(s) in RCA: 255] [Impact Index Per Article: 85.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 02/15/2021] [Accepted: 03/12/2021] [Indexed: 12/11/2022]
Abstract
The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.
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Affiliation(s)
- Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Olga Ciccarelli
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Brenda Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicola de Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria; Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jette Frederiksen
- Department of Neurology, Rigshospitalet Glostrup, University Hospital of Copenhagen, Glostrup, Denmark
| | - Claudio Gasperini
- Department of Neurology, San Camillo-Forlanini Hospital, Roma, Italy
| | - Yael Hacohen
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; Department of Paediatric Neurology, Great Ormond Street Hospital for Children, London, UK
| | - Ludwig Kappos
- Department of Neurology and Research Center for Clinical Neuroimmunology and Neuroscience, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Kshitij Mankad
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain; Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jiwon Oh
- Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anthony Traboulsee
- Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, London, UK; Neuroradiological Academic Unit, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands; Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.
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22
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Herrmann CJJ, Els A, Boehmert L, Periquito J, Eigentler TW, Millward JM, Waiczies S, Kuchling J, Paul F, Niendorf T. Simultaneous T 2 and T 2 ∗ mapping of multiple sclerosis lesions with radial RARE-EPI. Magn Reson Med 2021; 86:1383-1402. [PMID: 33951214 DOI: 10.1002/mrm.28811] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 03/26/2021] [Accepted: 03/26/2021] [Indexed: 12/26/2022]
Abstract
PURPOSE The characteristic MRI features of multiple sclerosis (MS) lesions make it conceptually appealing to pursue parametric mapping techniques that support simultaneous generation of quantitative maps of 2 or more MR contrast mechanisms. We present a modular rapid acquisition with relaxation enhancement (RARE)-EPI hybrid that facilitates simultaneous T2 and T 2 ∗ mapping (2in1-RARE-EPI). METHODS In 2in1-RARE-EPI the first echoes in the echo train are acquired with a RARE module, later echoes are acquired with an EPI module. To define the fraction of echoes covered by the RARE and EPI module, an error analysis of T2 and T 2 ∗ was conducted with Monte Carlo simulations. Radial k-space (under)sampling was implemented for acceleration (R = 2). The feasibility of 2in1-RARE-EPI for simultaneous T2 and T 2 ∗ mapping was examined in a phantom study mimicking T2 and T 2 ∗ relaxation times of the brain. For validation, 2in1-RARE-EPI was benchmarked versus multi spin-echo (MSE) and multi gradient-echo (MGRE) techniques. The clinical applicability of 2in1-RARE-EPI was demonstrated in healthy subjects and MS patients. RESULTS There was a good agreement between T2 / T 2 ∗ values derived from 2in1-RARE-EPI and T2 / T 2 ∗ reference values obtained from MSE and MGRE in both phantoms and healthy subjects. In patients, MS lesions in T2 and T 2 ∗ maps deduced from 2in1-RARE-EPI could be just as clearly delineated as in reference maps calculated from MSE/MGRE. CONCLUSION This work demonstrates the feasibility of radially (under)sampled 2in1-RARE-EPI for simultaneous T2 and T 2 ∗ mapping in MS patients.
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Affiliation(s)
- Carl J J Herrmann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.,Department of Physics, Humboldt University of Berlin, Berlin, Germany
| | - Antje Els
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Laura Boehmert
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Joao Periquito
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Thomas Wilhelm Eigentler
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.,Chair of Medical Engineering, Technical University of Berlin, Berlin, Germany
| | - Jason M Millward
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Sonia Waiczies
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Joseph Kuchling
- Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin, Berlin, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.,Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine, Berlin, Germany
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23
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Abstract
PURPOSE OF REVIEW Ultra-high field 7 T MRI has multiple applications for the in vivo characterization of the heterogeneous aspects underlying multiple sclerosis including the identification of cortical lesions, characterization of the different types of white matter plaques, evaluation of structures difficult to assess with conventional MRI (thalamus, cerebellum, spinal cord, meninges). RECENT FINDINGS The sensitivity of cortical lesion detection at 7 T is twice than at lower field MRI, especially for subpial lesions, the most common cortical lesion type in multiple sclerosis. Cortical lesion load accrual is independent of that in the white matter and predicts disability progression.Seven Tesla MRI provides details on tissue microstructure that can be used to improve white matter lesion characterization. These include the presence of a central vein, whose identification can be used to improve multiple sclerosis diagnosis, or the appearance of an iron-rich paramagnetic rim on susceptibility-weighted images, which corresponds to iron-rich microglia at the periphery of slow expanding lesions. Improvements in cerebellar and spinal cord tissue delineation and lesion characterization have also been demonstrated. SUMMARY Imaging at 7 T allows assessing more comprehensively the complementary pathophysiological aspects of multiple sclerosis, opening up novel perspectives for clinical and therapeutics evaluation.
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24
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Treaba CA, Herranz E, Barletta VT, Mehndiratta A, Ouellette R, Sloane JA, Klawiter EC, Kinkel RP, Mainero C. The relevance of multiple sclerosis cortical lesions on cortical thinning and their clinical impact as assessed by 7.0-T MRI. J Neurol 2021; 268:2473-2481. [PMID: 33523256 DOI: 10.1007/s00415-021-10400-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE This study aimed to investigate at 7.0-T MRI a) the role of multiple sclerosis (MS) cortical lesions in cortical tissue loss b) their relation to neurological disability. METHODS In 76 relapsing remitting and 26 secondary progressive MS patients (N = 102) and 56 healthy subjects 7.0-T T2*-weighted images were acquired for lesion segmentation; 3.0-T T1-weighted structural scans for cortical surface reconstruction/cortical thickness estimation. Patients were dichotomized based on the median cortical lesion volume in low and high cortical lesion load groups that differed by age, MS phenotype and degree of neurological disability. Group differences in cortical thickness were tested on reconstructed cortical surface. Patients were evaluated clinically by means of the Expanded Disability Status Scale (EDSS). RESULTS Cortical lesions were detected in 96% of patients. White matter lesion load was greater in the high than in the low cortical lesion load MS group (p = 0.01). Both MS groups disclosed clusters (prevalently parietal) of cortical thinning relative to healthy subjects, though these regions did not show the highest cortical lesion density, which predominantly involved frontal regions. Cortical thickness decreased on average by 0.37 mm, (p = 0.002) in MS patients for each unit standard deviation change in white matter lesion volume. The odds of having a higher EDSS were associated with cortical lesion volume (1.78, p = 0.01) and disease duration (1.15, p < 0.001). CONCLUSION Cortical thinning in MS is not directly related to cortical lesion load but rather with white matter lesion volume. Neurological disability in MS is better explained by cortical lesion volume assessment.
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Affiliation(s)
- Constantina A Treaba
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Elena Herranz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Valeria T Barletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Ambica Mehndiratta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Russell Ouellette
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Jacob A Sloane
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. .,Harvard Medical School, Boston, MA, USA.
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25
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Clinical 7-T MRI for neuroradiology: strengths, weaknesses, and ongoing challenges. Neuroradiology 2021; 63:167-177. [PMID: 33388947 DOI: 10.1007/s00234-020-02629-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 12/20/2020] [Indexed: 10/22/2022]
Abstract
Since the relatively recent regulatory approval for clinical use in both Europe and North America, 7-Tesla (T) MRI has been adopted for clinical practice at our institution. Based on this experience, this article reviews the unique features of 7-T MRI neuroimaging and addresses the challenges of establishing a 7-T MRI clinical practice. The underlying fundamental physics principals of high-field strength MRI are briefly reviewed. Scanner installation, safety considerations, and artifact mitigation techniques are discussed. Seven-tesla MRI case examples of neurologic diseases including epilepsy, vascular abnormalities, and tumor imaging are presented to illustrate specific applications of 7-T MRI. The advantages of 7-T MRI in conjunction with advanced neuroimaging techniques such as functional MRI are presented. Seven-tesla MRI produces more detailed information and, in some cases, results in specific diagnoses where previous 3-T studies were insufficient. Still, persistent technical issues for 7-T scanning present ongoing challenges for radiologists.
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26
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Bruschi N, Boffa G, Inglese M. Ultra-high-field 7-T MRI in multiple sclerosis and other demyelinating diseases: from pathology to clinical practice. Eur Radiol Exp 2020; 4:59. [PMID: 33089380 PMCID: PMC7578213 DOI: 10.1186/s41747-020-00186-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 09/11/2020] [Indexed: 11/10/2022] Open
Abstract
Magnetic resonance imaging (MRI) is essential for the early diagnosis of multiple sclerosis (MS), for investigating the disease pathophysiology, and for discriminating MS from other neurological diseases. Ultra-high-field strength (7-T) MRI provides a new tool for studying MS and other demyelinating diseases both in research and in clinical settings. We present an overview of 7-T MRI application in MS focusing on increased sensitivity and specificity for lesion detection and characterisation in the brain and spinal cord, central vein sign identification, and leptomeningeal enhancement detection. We also discuss the role of 7-T MRI in improving our understanding of MS pathophysiology with the aid of metabolic imaging. In addition, we present 7-T MRI applications in other demyelinating diseases. 7-T MRI allows better detection of the anatomical, pathological, and functional features of MS, thus improving our understanding of MS pathology in vivo. 7-T MRI also represents a potential tool for earlier and more accurate diagnosis.
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Affiliation(s)
- Nicolo' Bruschi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Giacomo Boffa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.
- Ospedale Policlinico San Martino, IRCCS, Largo Daneo 3, 16100, Genoa, Italy.
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27
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Moccia M, van de Pavert S, Eshaghi A, Haider L, Pichat J, Yiannakas M, Ourselin S, Wang Y, Wheeler-Kingshott C, Thompson A, Barkhof F, Ciccarelli O. Pathologic correlates of the magnetization transfer ratio in multiple sclerosis. Neurology 2020; 95:e2965-e2976. [PMID: 32938787 DOI: 10.1212/wnl.0000000000010909] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 07/22/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To identify pathologic correlates of magnetization transfer ratio (MTR) in multiple sclerosis (MS) in an MRI-pathology study. METHODS We acquired MTR maps at 3T from 16 fixed MS brains and 4 controls, and immunostained 100 tissue blocks for neuronal neurofilaments, myelin (SMI94), tissue macrophages (CD68), microglia (IBA1), B-lymphocytes, T-lymphocytes, cytotoxic T-lymphocytes, astrocytes (glial fibrillary acidic protein), and mitochondrial damage (COX4, VDAC). We defined regions of interest in lesions, normal-appearing white matter (NAWM), and cortical normal-appearing gray matter (NAGM). Associations between MTR and immunostaining intensities were explored using linear mixed-effects models (with cassettes nested within patients) and interaction terms (for differences between regions of interest and between cases and controls); a multivariate linear mixed-effects model identified the best pathologic correlates of MTR. RESULTS MTR was the lowest in white matter (WM) lesions (23.4 ± 9.4%) and the highest in NAWM (38.1 ± 8.7%). In MS brains, lower MTR was associated with lower immunostaining intensity for myelin (coefficient 0.31; 95% confidence interval [CI] 0.07-0.55), macrophages (coefficient 0.03; 95% CI 0.01-0.07), and astrocytes (coefficient 0.51; 95% CI 0.02-1.00), and with greater mitochondrial damage (coefficient 0.31; 95% CI 0.07-0.55). Based on interaction terms, MTR was more strongly associated with myelin in WM (coefficient 1.58; 95% CI 1.09-2.08) and gray matter (GM) lesions (coefficient 0.66; 95% CI 0.13-1.20), and with macrophages (coefficient 1.40; 95% CI 0.56-2.25), astrocytes (coefficient 2.66; 95% CI 1.31-4.01), and mitochondrial damage (coefficient -12.59; 95% CI -23.16 to -2.02) in MS brains than controls. In the multivariate model, myelin immunostaining intensity was the best correlate of MTR (coefficient 0.31; 95% CI 0.09-0.52; p = 0.004). CONCLUSIONS Myelin was the strongest correlate of MTR, especially in WM and cortical GM lesions, but additional correlates should be kept in mind when designing and interpreting MTR observational and experimental studies in MS.
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Affiliation(s)
- Marcello Moccia
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Steven van de Pavert
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Arman Eshaghi
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Lukas Haider
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Jonas Pichat
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Marios Yiannakas
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Sebastien Ourselin
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Yi Wang
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Claudia Wheeler-Kingshott
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Alan Thompson
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Frederik Barkhof
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK
| | - Olga Ciccarelli
- From the Department of Neuroinflammation, Queen Square MS Centre, NMR Research Unit, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences (M.M., S.v.d.P., A.E., L.H., M.Y., Y.W., C.W.-K., A.T., F.B., O.C.), Centre for Medical Image Computing, Department of Medical Physics and Bioengineering (J.P., S.O.), and Translational Imaging Group, UCL Institute of Healthcare Engineering (F.B.), University College London, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences (M.M.), Federico II University, Naples, Italy; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research University College London Hospitals Biomedical Research Centre (A.T., F.B., O.C.), UK.
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Editorial for "Deep‐Learning‐Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size". J Magn Reson Imaging 2020; 51:1856-1857. [DOI: 10.1002/jmri.26997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 10/28/2019] [Indexed: 11/07/2022] Open
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Cocozza S, Cosottini M, Signori A, Fleysher L, El Mendili MM, Lublin F, Inglese M, Roccatagliata L. A clinically feasible 7-Tesla protocol for the identification of cortical lesions in Multiple Sclerosis. Eur Radiol 2020; 30:4586-4594. [PMID: 32211962 DOI: 10.1007/s00330-020-06803-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 02/25/2020] [Accepted: 03/11/2020] [Indexed: 12/01/2022]
Abstract
OBJECTIVES The aim of this study was to evaluate the capability of sequences acquired on a 7-T MRI scanner, within times and anatomical coverage appropriate for clinical studies, to identify cortical lesions (CLs) in patients with Multiple Sclerosis (MS). Furthermore, we aimed to confirm the clinical significance of CL, testing the correlations between gray matter (GM) lesions and clinical scores. METHODS A 7-T MRI protocol included 3D-T1-weighted and T2*-weighted sequences. Images were evaluated independently by three readers of different experience, and the number of CLs was recorded. Between-rater concordance was assessed calculating the intraclass correlation coefficient (ICC). Lin's concordance correlation coefficient was used to compare CL detection between sequences, while partial correlations and multivariable regression models were used to study the relationship between CL and clinical data. RESULTS Forty MS patients (M/F, 17/23; 44.7 ± 12.6 years) were enrolled in this study, and CLs were identified in 35/40 subjects (87.5%). CL detection rate on 3D-T1-weighted images was significantly correlated with the detection rate on T2*-weighted images (r = 0.99; p < 0.001), with high concordance between readers (ICC ≥ 0.995). CLs were significantly correlated with both motor and cognitive scores (all with p ≤ 0.04). CONCLUSIONS CL can be identified over the whole brain at 7-T in MS using a 3D-T1-weighted volume, acquired in a clinically feasible time and with comparable performance to that achievable using the T2*-weighted sequence. Based on the central role of CL in the development of clinical disability, we suggest that 3D-T1-weighted volume may play a role in the evaluation of CL in MS undergoing MRI on ultra-high-field scanners. KEY POINTS • Cortical lesions can be identified in a clinically feasible time with a 7-T protocol, which includes a 3D-T1-weighted volume. • Cortical lesions correlated significantly with both motor and cognitive disability in MS patients. • Given their correlation with clinical disability, evaluation of a cortical lesion on a 7-T clinical protocol could help in the management of MS patients.
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Affiliation(s)
- Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Mirco Cosottini
- Department of Translational Research and New Surgical and Medical Technologies, University of Pisa, Pisa, Italy
| | - Alessio Signori
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
| | | | - Fred Lublin
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, USA. .,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI) and Center of Excellence for Biomedical Research (CEBR), University of Genoa, Largo Paolo Daneo 3, Genoa, Italy. .,Ospedale Policlinico San Martino IRCCS, Genoa, Italy.
| | - Luca Roccatagliata
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.,Department of Neuroradiology, Ospedale Policlinico San Martino IRCCS, Genoa, Italy
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Dadar M, Narayanan S, Arnold DL, Collins DL, Maranzano J. Conversion of diffusely abnormal white matter to focal lesions is linked to progression in secondary progressive multiple sclerosis. Mult Scler 2020; 27:208-219. [DOI: 10.1177/1352458520912172] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Background: Diffusely abnormal white matter (DAWM) regions are observed in magnetic resonance images of secondary progressive multiple sclerosis (SPMS) patients. However, their role in clinical progression is still not established. Objectives: To characterize the longitudinal volumetric and intensity evolution of DAWM and focal white matter lesions (FWML) and assess their associations with clinical outcomes and progression in SPMS. Methods: Data include 589 SPMS participants followed up for 3 years (3951 time points). FWML and DAWM were automatically segmented. Screening DAWM volumes that transformed into FWML at the last visit (DAWM-to-FWML) and normalized T1-weighted intensities (indicating severity of damage) in those voxels were calculated. Results: FWML volume increased and DAWM volume decreased with an increase in disease duration ( p < 0.001). The Expanded Disability Status Scale (EDSS) was positively associated with FWML volumes ( p = 0.002), but not with DAWM. DAWM-to-FWML volume was higher in patients who progressed (2.75 cm3 vs. 1.70 cm3; p < 0.0001). Normalized T1-weighted intensity of DAWM-to-FWML was negatively associated with progression ( p < 0.00001). Conclusion: DAWM transformed into FWML over time, and this transformation was associated with clinical progression. DAWM-to-FWML voxels had greater normalized T1-weighted intensity decrease over time, in keeping with relatively greater tissue damage. Evaluation of DAWM in progressive multiple sclerosis provides a useful measure for therapies aiming to protect this at-risk tissue with the potential to slow progression.
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Affiliation(s)
- Mahsa Dadar
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada/Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada/Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada/Department of Anatomy, University of Quebec in Trois-Rivieres, Trois-Rivieres, QC, Canada
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