1
|
Smyth LCD, Xu D, Okar SV, Dykstra T, Rustenhoven J, Papadopoulos Z, Bhasiin K, Kim MW, Drieu A, Mamuladze T, Blackburn S, Gu X, Gaitán MI, Nair G, Storck SE, Du S, White MA, Bayguinov P, Smirnov I, Dikranian K, Reich DS, Kipnis J. Identification of direct connections between the dura and the brain. Nature 2024; 627:165-173. [PMID: 38326613 DOI: 10.1038/s41586-023-06993-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 12/18/2023] [Indexed: 02/09/2024]
Abstract
The arachnoid barrier delineates the border between the central nervous system and dura mater. Although the arachnoid barrier creates a partition, communication between the central nervous system and the dura mater is crucial for waste clearance and immune surveillance1,2. How the arachnoid barrier balances separation and communication is poorly understood. Here, using transcriptomic data, we developed transgenic mice to examine specific anatomical structures that function as routes across the arachnoid barrier. Bridging veins create discontinuities where they cross the arachnoid barrier, forming structures that we termed arachnoid cuff exit (ACE) points. The openings that ACE points create allow the exchange of fluids and molecules between the subarachnoid space and the dura, enabling the drainage of cerebrospinal fluid and limited entry of molecules from the dura to the subarachnoid space. In healthy human volunteers, magnetic resonance imaging tracers transit along bridging veins in a similar manner to access the subarachnoid space. Notably, in neuroinflammatory conditions such as experimental autoimmune encephalomyelitis, ACE points also enable cellular trafficking, representing a route for immune cells to directly enter the subarachnoid space from the dura mater. Collectively, our results indicate that ACE points are a critical part of the anatomy of neuroimmune communication in both mice and humans that link the central nervous system with the dura and its immunological diversity and waste clearance systems.
Collapse
Affiliation(s)
- Leon C D Smyth
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA.
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
| | - Di Xu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Taitea Dykstra
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Justin Rustenhoven
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Department of Pharmacology and Clinical Pharmacology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Zachary Papadopoulos
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Neuroscience Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Kesshni Bhasiin
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Min Woo Kim
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Antoine Drieu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Tornike Mamuladze
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Susan Blackburn
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Xingxing Gu
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - María I Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Steffen E Storck
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Siling Du
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Michael A White
- Department of Genetics, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Peter Bayguinov
- Washington University Center for Cellular Imaging, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Igor Smirnov
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Krikor Dikranian
- Department of Neuroscience, Washington University School of Medicine, Washington University in St Louis, St Louis, MO, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jonathan Kipnis
- Brain Immunology and Glia (BIG) Center, Washington University in St Louis, St Louis, MO, USA.
- Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
- Neuroscience Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
- Immunology Graduate Program, School of Medicine, Washington University in St Louis, St Louis, MO, USA.
| |
Collapse
|
2
|
Okar SV, Dieckhaus H, Beck ES, Gaitán MI, Norato G, Pham DL, Absinta M, Cortese IC, Fletcher A, Jacobson S, Nair G, Reich DS. Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis. Invest Radiol 2024; 59:243-251. [PMID: 37493285 PMCID: PMC10818009 DOI: 10.1097/rli.0000000000001011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
BACKGROUND Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. PURPOSE To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. MATERIALS AND METHODS We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. RESULTS We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. CONCLUSIONS Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.
Collapse
Affiliation(s)
- Serhat Vahip Okar
- From the Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (S.V.O., E.S.B., M.I.G., M.A., D.S.R.); qMRI Core facility, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, USA (H.D., G.N.); Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA (E.S.B.); Office of Biostatistics, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (G.N.); Department of Radiology and Radiological Sciences, Uniformed Services University of the Health Sciences, Bethesda, MD, USA (D.L.P.); Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy (M.A.); Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA (M.A.); Experimental Immunotherapeutics Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (I.C.M.C.); Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA (A.F.); and Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD20814, USA (S.J.)
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
3
|
Chien A, Wu T, Lau CY, Pandya D, Wiebold A, Agan B, Snow J, Smith B, Nath A, Nair G. White and Gray Matter Changes are Associated With Neurocognitive Decline in HIV Infection. Ann Neurol 2024. [PMID: 38362961 DOI: 10.1002/ana.26896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/09/2024] [Accepted: 01/30/2024] [Indexed: 02/17/2024]
Abstract
OBJECTIVE To investigate the relationship between neurocognitive deficits and structural changes on brain magnetic resonance imaging in people living with HIV (PLWH) with good virological control on combination antiretroviral therapy, compared with socioeconomically matched control participants recruited from the same communities. METHODS Brain magnetic resonance imaging scans, and clinical and neuropsychological data were obtained from virologically controlled PLWH (viral load of <50 c/mL and at least 1 year of combination antiretroviral therapy) and socioeconomically matched control participants. Magnetic resonance imaging was carried out on 3 T scanner with 8-channel head coils and segmented using Classification using Derivative-based Features. Multiple regression analysis was performed to examine the association between brain volume and various clinical and neuropsychiatric parameters adjusting for age, race, and sex. To evaluate longitudinal changes in brain volumes, a random coefficient model was used to evaluate the changes over time (age) adjusting for sex and race. RESULTS The cross-sectional study included 164 PLWH and 51 controls, and the longitudinal study included 68 PLWH and 20 controls with 2 or more visits (mean 2.2 years, range 0.8-5.1 years). Gray matter (GM) atrophy rate was significantly higher in PLWH compared with control participants, and importantly, the GM and global atrophy was associated with the various neuropsychological domain scores. Higher volume of white matter hyperintensities were associated with increased atherosclerotic cardiovascular disease risk score, and decreased executive functioning and memory domain scores in PLWH. INTERPRETATION These findings suggest ongoing neurological damage even in virologically controlled participants, with significant implications for clinical management of PLWH. ANN NEUROL 2024.
Collapse
Affiliation(s)
- Alice Chien
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Tianxia Wu
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | | | - Darshan Pandya
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Amanda Wiebold
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Brian Agan
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Joseph Snow
- National Institute of Mental Health, Bethesda, MD, USA
| | - Bryan Smith
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Avindra Nath
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| |
Collapse
|
4
|
Galbusera R, Bahn E, Weigel M, Cagol A, Lu PJ, Schaedelin SA, Franz J, Barakovic M, Rahmanzadeh R, Dechent P, Nair G, Brück W, Kuhle J, Kappos L, Stadelmann C, Granziera C. Characteristics, Prevalence, and Clinical Relevance of Juxtacortical Paramagnetic Rims in Patients With Multiple Sclerosis. Neurology 2024; 102:e207966. [PMID: 38165297 DOI: 10.1212/wnl.0000000000207966] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 09/11/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES A subgroup of patients with multiple sclerosis (MS) presents focal paramagnetic rims at the border between cortex and white matter (juxtacortical paramagnetic rims [JPRs]). We investigated the presence of this finding in our in vivo MS cohort and explored its potential clinical relevance. Moreover, we exploited postmortem MRI of fixed whole MS brains to (1) detect those rims and (2) investigate their histologic correlation. METHODS Quantitative susceptibility mapping (QSM) and magnetization-prepared 2 rapid acquisition gradient-echo (MP2RAGE) images at 3T-MRI of 165 patients with MS from the in vivo cohort were screened for JPRs and the presence of cortical lesions. Five postmortem brains from patients with MS were imaged with 3T-MRI to obtain QSM and MP2RAGE sequences. Tissue blocks containing JPRs were excised and paraffin-embedded slices stained by immunohistochemistry for myelin basic protein (for myelin) and anti-CR3/43 (for major histocompatibility complex II-positive microglia/macrophages). DAB-Turnbull stain was performed to detect iron. RESULTS JPRs are present in approximately 10% of in vivo patients and are associated with increased cortical lesion load. One of the 5 postmortem brains showed JPRs. Histologically, JPRs correspond to an accumulation of activated iron-laden phagocytes and are associated with demyelination of the whole overlying cortical ribbon. DISCUSSION JPRs are a novel potential MRI biomarker of focal cortical demyelination, which seems related to global cortical pathology and might be useful for diagnostic and stratification purposes in a clinical setting.
Collapse
Affiliation(s)
- Riccardo Galbusera
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Erik Bahn
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Matthias Weigel
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Alessandro Cagol
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Po-Jui Lu
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Sabine A Schaedelin
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Jonas Franz
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Muhamed Barakovic
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Reza Rahmanzadeh
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Peter Dechent
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Govind Nair
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Wolfgang Brück
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Jens Kuhle
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Ludwig Kappos
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Christine Stadelmann
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| | - Cristina Granziera
- From the Neurology Clinic and Policlinic (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Departments of Medicine, Clinical Research and Biomedical Engineering, Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, (R.G., M.W., A.C., P.-J.L., M.B., L.K., C.G.), Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel (R.G., M.W., A.C., P.-J.L., M.B., J.K., L.K., C.G.), Radiological Physics, Department of Radiology (M.W.), and Department of Clinical Research (S.A.S.), University Hospital Basel and University of Basel, Switzerland; Institute of Neuropathology (E.B., J.F., W.B., C.S.), University Medical Center Göttingen, Germany; Department of Cognitive Neurology (P.D.), MR-Research in Neurosciences, University Medical Center Göttingen, Germany; Institute of Diagnostic and Interventional Neuroradiology (R.R.), Bern University Hospital, University of Bern, Switzerland; and National Institute of Neurological Disorders and Stroke (G.N.), Bethesda, MD
| |
Collapse
|
5
|
Nair G, Sun R, Merkle H, Hoskin K, Bree K, Dodd S, Koretsky A. Postmortem MRI of Tissue Frozen at Autopsy. bioRxiv 2024:2024.01.20.576456. [PMID: 38313300 PMCID: PMC10836069 DOI: 10.1101/2024.01.20.576456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Introduction Postmortem MRI provides insight into location of pathology within tissue blocks, enabling efficient targeting of histopathological studies. While postmortem imaging of fixed tissue is gaining popularity, imaging tissue frozen at the time of extraction is significantly more challenging. Methods Tissue integrity was examined using RNA integrity number (RIN), in mouse brains placed between -20 °C and 20 °C for up to 24 hours, to determine the highest temperature that could potentially be used for imaging without tissue degeneration. Human tissue frozen at the time of autopsy was sealed in a tissue chamber filled with 2-methylbutane to prevent contamination of the MRI components. The tissue was cooled to a range of temperatures in a 9.4T MRI using a recirculating aqueous ethylene glycol solution. MRI was performed using a magnetization-prepared rapid gradient echo (MPRAGE) sequence with inversion time of 1400 ms to null the signal from 2-methylbutane bath, isotropic resolution between 0.3-0.4 mm, and scan time of about 4 hours was used to study the anatomical details of the tissue block. Results and Discussion A temperature of -7 °C was chosen for imaging as it was below the highest temperature that did not show significant RIN deterioration for over 12 hours, at the same time gave robust imaging signal and contrast between brain tissue types. Imaging performed on various human tissue blocks revealed good gray-white matter contrast and revealing subpial, subcortical, and deep white matter lesions typical of multiple sclerosis enabling further spatially targeted studies. Conclusion Here, we describe a new method to image cold tissue, while maintaining tissue integrity and biosafety during scanning. In addition to improving efficiency of downstream processes, imaging tissue at sub-zero temperatures may also improve our understanding of compartment specificity of MRI signal.
Collapse
Affiliation(s)
- Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Roy Sun
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Hellmut Merkle
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Kyra Hoskin
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Kendyl Bree
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Stephen Dodd
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Alan Koretsky
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| |
Collapse
|
6
|
Donnay C, Dieckhaus H, Tsagkas C, Gaitán MI, Beck ES, Mullins A, Reich DS, Nair G. Pseudo-Label Assisted nnU-Net enables automatic segmentation of 7T MRI from a single acquisition. Front Neuroimaging 2023; 2:1252261. [PMID: 38107773 PMCID: PMC10722186 DOI: 10.3389/fnimg.2023.1252261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023]
Abstract
Introduction Automatic whole brain and lesion segmentation at 7T presents challenges, primarily from bias fields, susceptibility artifacts including distortions, and registration errors. Here, we sought to use deep learning algorithms (D/L) to do both skull stripping and whole brain segmentation on multiple imaging contrasts generated in a single Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) acquisition on participants clinically diagnosed with multiple sclerosis (MS), bypassing registration errors. Methods Brain scans Segmentation from 3T and 7T scanners were analyzed with software packages such as FreeSurfer, Classification using Derivative-based Features (C-DEF), nnU-net, and a novel 3T-to-7T transfer learning method, Pseudo-Label Assisted nnU-Net (PLAn). 3T and 7T MRIs acquired within 9 months from 25 study participants with MS (Cohort 1) were used for training and optimizing. Eight MS patients (Cohort 2) scanned only at 7T, but with expert annotated lesion segmentation, was used to further validate the algorithm on a completely unseen dataset. Segmentation results were rated visually by experts in a blinded fashion and quantitatively using Dice Similarity Coefficient (DSC). Results Of the methods explored here, nnU-Net and PLAn produced the best tissue segmentation at 7T for all tissue classes. In both quantitative and qualitative analysis, PLAn significantly outperformed nnU-Net (and other methods) in lesion detection in both cohorts. PLAn's lesion DSC improved by 16% compared to nnU-Net. Discussion Limited availability of labeled data makes transfer learning an attractive option, and pre-training a nnUNet model using readily obtained 3T pseudo-labels was shown to boost lesion detection capabilities at 7T.
Collapse
Affiliation(s)
- Corinne Donnay
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Henry Dieckhaus
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
| | - Charidimos Tsagkas
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - María Inés Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andrew Mullins
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, United States
| | - Govind Nair
- qMRI Core, NINDS, National Institutes of Health, Bethesda, MD, United States
| |
Collapse
|
7
|
Middleton DM, Shahrampour S, Krisa L, Liu W, Nair G, Jacobson S, Conklin CJ, Alizadeh M, Faro SH, Mulcahey MJ, Mohamed FB. Correlations of diffusion tensor imaging and clinical measures with spinal cord cross-sectional area measurements in pediatric spinal cord injury patients. J Spinal Cord Med 2023; 46:950-957. [PMID: 34855576 PMCID: PMC10653768 DOI: 10.1080/10790268.2021.1997027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Abstract
PURPOSE The purpose of this work was to employ a semi-automatic method for measuring spinal cord cross-sectional area (SCCSA) and investigate the correlations between diffusion tensor imaging (DTI) metrics and SCCSA for the cervical and thoracic spinal cord for typically developing pediatric subjects and pediatric subject with spinal cord injury. METHODS Ten typically developing (TD) pediatric subjects and ten pediatric subjects with spinal cord injury (SCI) were imaged using a Siemens Verio 3 T MR scanner to acquire DTI and high-resolution anatomic scans covering the cervical and thoracic spinal cord (C1-T12). SCCSA was measured using a semi-automated edge detection algorithm for the entire spinal cord. DTI metrics were obtained from whole cord axial ROIs at each vertebral level. SCCSA measures were compared to DTI metrics by vertebral level throughout the entire cord, and above and below the injury site. Correlation analysis was performed to compare SCCSA, DTI and clinical measures as determined by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination. RESULTS In subjects with SCI, FA and SCCSA had a positive correlation (r = 0.81, P < 0.01), while RD and SCCSA had a negative correlation (r = -0.68, P = 0.02) for the full spinal cord. FA and SCCSA were correlated above (r = 0.56, P < 0.01) and below (r = 0.54, P < 0.01) the injury site. TD subjects showed negative correlations between AD and SCCSA (r = -0.73, P = 0.01) and RD and SCCSA (r = -0.79, P < 0.01). CONCLUSION The ability to quickly and effectively measure SCCSA in subjects with SCI has the potential to allow for a better understanding of the progression of atrophy following a SCI. Correlations between cord cross section and DTI metrics by vertebral level suggest that imaging inferior and superior to lesion may yield useful information for diagnosis and prognosis.
Collapse
Affiliation(s)
- Devon M. Middleton
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Shiva Shahrampour
- Department of Bioengineering, Temple University, Philadelphia, Pennsylvania, USA
| | - Laura Krisa
- College of Rehabilitation Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Winston Liu
- School of Medicine, Duke University, Durham, North Carolina, USA
| | - Govind Nair
- National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Steven Jacobson
- National Institutes of Health, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | | | - Mahdi Alizadeh
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Scott H. Faro
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - M. J. Mulcahey
- College of Rehabilitation Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Feroze B. Mohamed
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| |
Collapse
|
8
|
Galbusera R, Bahn E, Weigel M, Schaedelin S, Franz J, Lu P, Barakovic M, Melie‐Garcia L, Dechent P, Lutti A, Sati P, Reich DS, Nair G, Brück W, Kappos L, Stadelmann C, Granziera C. Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis. Brain Pathol 2023; 33:e13136. [PMID: 36480267 PMCID: PMC10580009 DOI: 10.1111/bpa.13136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022] Open
Abstract
Quantitative MRI (qMRI) probes the microstructural properties of the central nervous system (CNS) by providing biophysical measures of tissue characteristics. In this work, we aimed to (i) identify qMRI measures that distinguish histological lesion types in postmortem multiple sclerosis (MS) brains, especially the remyelinated ones; and to (ii) investigate the relationship between those measures and quantitative histological markers of myelin, axons, and astrocytes in the same experimental setting. Three fixed MS whole brains were imaged with qMRI at 3T to obtain magnetization transfer ratio (MTR), myelin water fraction (MWF), quantitative T1 (qT1), quantitative susceptibility mapping (QSM), fractional anisotropy (FA) and radial diffusivity (RD) maps. The identification of lesion types (active, inactive, chronic active, or remyelinated) and quantification of tissue components were performed using histological staining methods as well as immunohistochemistry and immunofluorescence. Pairwise logistic and LASSO regression models were used to identify the best qMRI discriminators of lesion types. The association between qMRI and quantitative histological measures was performed using Spearman's correlations and linear mixed-effect models. We identified a total of 65 lesions. MTR and MWF best predicted the chance of a lesion to be remyelinated, whereas RD and QSM were useful in the discrimination of active lesions. The measurement of microstructural properties through qMRI did not show any difference between chronic active and inactive lesions. MWF and RD were associated with myelin content in both lesions and normal-appearing white matter (NAWM), FA was the measure most associated with axon content in both locations, while MWF was associated with astrocyte immunoreactivity only in lesions. Moreover, we provided evidence of extensive astrogliosis in remyelinated lesions. Our study provides new information on the discriminative power of qMRI in differentiating MS lesions -especially remyelinated ones- as well as on the relative association between multiple qMRI measures and myelin, axon and astrocytes.
Collapse
Affiliation(s)
- Riccardo Galbusera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Erik Bahn
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
- Division of Radiological Physics, Department of RadiologyUniversity Hospital BaselBaselSwitzerland
| | - Sabine Schaedelin
- Clinical Trial Unit, Department of Clinical ResearchUniversity Hospital Basel, University of BaselBaselSwitzerland
| | - Jonas Franz
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Campus Institute for Dynamics of Biological NetworksUniversity of GöttingenGöttingenGermany
- Max Planck Institute for Experimental MedicineGöttingenGermany
| | - Po‐Jui Lu
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Lester Melie‐Garcia
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Peter Dechent
- Department of Cognitive NeurologyMR‐Research in Neurosciences, University Medical Center GöttingenGöttingenGermany
| | - Antoine Lutti
- Centre for Research in Neuroscience, Department of Clinical NeurosciencesLaboratoire de Recherche en Neuroimagerie (LREN) University Hospital and University of LausanneLausanneSwitzerland
| | - Pascal Sati
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMarylandUSA
| | - Govind Nair
- National Institute of Neurological Disorders and StrokeBethesdaMarylandUSA
| | - Wolfgang Brück
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| | - Christine Stadelmann
- Institute of NeuropathologyUniversity Medical CenterGöttingenGermany
- Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Network of Excitable Cells (MBExC) ”University of GoettingenGermany
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of MedicineUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB)University Hospital Basel and University of BaselBaselSwitzerland
| |
Collapse
|
9
|
Clark KA, O’Donnell CM, Elliott MA, Tauhid S, Dewey BE, Chu R, Khalil S, Nair G, Sati P, DuVal A, Pellegrini N, Bar-Or A, Markowitz C, Schindler MK, Zurawski J, Calabresi PA, Reich DS, Bakshi R, Shinohara RT. Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis. J Neuroimaging 2023; 33:941-952. [PMID: 37587544 PMCID: PMC10981935 DOI: 10.1111/jon.13147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND AND PURPOSE Multicenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites. METHODS Images were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole-brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization-prepared rapid acquisition gradient echo and T2 fluid-attenuated inversion recovery lesions. Random-effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. RESULTS Random-effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. CONCLUSION Differences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.
Collapse
Affiliation(s)
- Kelly A. Clark
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Carly M. O’Donnell
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Mark A. Elliott
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | - Shahamat Tauhid
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Blake E. Dewey
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Renxin Chu
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Samar Khalil
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Govind Nair
- Quantitative MRI core facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Anna DuVal
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nicole Pellegrini
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Amit Bar-Or
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Clyde Markowitz
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Matthew K. Schindler
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jonathan Zurawski
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Peter A. Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Rohit Bakshi
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | | |
Collapse
|
10
|
Kohut EA, Graff SA, Wakelin SH, Arhin M, Nair G, Heiss JD. Developing Semiautomated Methods to Measure Pre- and Postoperative Syrinx Volumes. J Clin Med 2023; 12:6725. [PMID: 37959191 PMCID: PMC10650856 DOI: 10.3390/jcm12216725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/20/2023] [Accepted: 10/21/2023] [Indexed: 11/15/2023] Open
Abstract
Neurosurgeons evaluate MRI scans to document whether surgical treatment has reduced syrinx size. Manual measurement of syrinx volume is time-consuming and potentially introduces operator error and bias. Developing convenient semiautomated volumetric analysis methods may encourage their clinical implementation and improve syringomyelia monitoring. We analyzed 30 SPGR axial MRI scans from 15 pre- and postoperative Chiari I and syringomyelia patients using two semiautomated (SCAT and 3DQI) methods and a manual Cavalieri (CAV) method. Patients' spinal cord and syrinx volumes pre- and postoperatively were compared by paired t-test. A decrease in syrinx volume (mm3) after surgery was detected across all methods. Mean syrinx volume (± SD) measured by CAV (n = 30) was, preoperatively, 4515 mm3 ± 3720, postoperatively 1109 ± 1469; (p = 0.0004). SCAT was, pre, 4584 ± 3826, post, 1064 ± 1465; (p = 0.0007) and 3DQI was, pre, 4027 ± 3805, post, 819 ± 1242; (p = 0.001). 3DQI and CAV detected similar mean spinal cord volumes before (p = 0.53) and after surgery (p = 0.23), but SCAT volumes differed significantly (p = 0.005, p = 0.0001). The SCAT and 3DQI semiautomated methods recorded surgically related syrinx volume changes efficiently and with enough accuracy for clinical decision-making and research studies.
Collapse
Affiliation(s)
- Eric A. Kohut
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, The National Institutes of Health, Bethesda, MD 20892, USA; (E.A.K.); (S.H.W.); (M.A.); (J.D.H.)
| | - Shantelle A. Graff
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, The National Institutes of Health, Bethesda, MD 20892, USA; (E.A.K.); (S.H.W.); (M.A.); (J.D.H.)
| | - Samuel H. Wakelin
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, The National Institutes of Health, Bethesda, MD 20892, USA; (E.A.K.); (S.H.W.); (M.A.); (J.D.H.)
| | - Martin Arhin
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, The National Institutes of Health, Bethesda, MD 20892, USA; (E.A.K.); (S.H.W.); (M.A.); (J.D.H.)
| | - Govind Nair
- qMRI Core Facility, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20892, USA;
| | - John D. Heiss
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, The National Institutes of Health, Bethesda, MD 20892, USA; (E.A.K.); (S.H.W.); (M.A.); (J.D.H.)
| |
Collapse
|
11
|
Beck ES, Mullins WA, Dos Santos Silva J, Filippini S, Parvathaneni P, Maranzano J, Morrison M, Suto DJ, Donnay C, Dieckhaus H, Luciano NJ, Sharma K, Gaitán MI, Liu J, de Zwart JA, van Gelderen P, Cortese I, Narayanan S, Duyn JH, Nair G, Sati P, Reich DS. Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis. medRxiv 2023:2023.09.22.23295974. [PMID: 37886541 PMCID: PMC10602044 DOI: 10.1101/2023.09.22.23295974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background and objectives Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL. Methods A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2. Results 59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010μl, range 13-9888 vs median 267μl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183μl, range 270-9888 vs median 321μl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS. Discussion CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.
Collapse
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
| |
Collapse
|
12
|
Mina Y, Enose-Akahata Y, Hammoud DA, Videckis AJ, Narpala SR, O'Connell SE, Carroll R, Lin BC, McMahan CC, Nair G, Reoma LB, McDermott AB, Walitt B, Jacobson S, Goldstein DS, Smith BR, Nath A. Deep Phenotyping of Neurologic Postacute Sequelae of SARS-CoV-2 Infection. Neurol Neuroimmunol Neuroinflamm 2023; 10:10/4/e200097. [PMID: 37147136 PMCID: PMC10162706 DOI: 10.1212/nxi.0000000000200097] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 01/04/2023] [Indexed: 05/07/2023]
Abstract
BACKGROUND AND OBJECTIVES SARS-CoV-2 infection has been associated with a syndrome of long-term neurologic sequelae that is poorly characterized. We aimed to describe and characterize in-depth features of neurologic postacute sequelae of SARS-CoV-2 infection (neuro-PASC). METHODS Between October 2020 and April 2021, 12 participants were seen at the NIH Clinical Center under an observational study to characterize ongoing neurologic abnormalities after SARS-CoV-2 infection. Autonomic function and CSF immunophenotypic analysis were compared with healthy volunteers (HVs) without prior SARS-CoV-2 infection tested using the same methodology. RESULTS Participants were mostly female (83%), with a mean age of 45 ± 11 years. The median time of evaluation was 9 months after COVID-19 (range 3-12 months), and most (11/12, 92%) had a history of only a mild infection. The most common neuro-PASC symptoms were cognitive difficulties and fatigue, and there was evidence for mild cognitive impairment in half of the patients (MoCA score <26). The majority (83%) had a very disabling disease, with Karnofsky Performance Status ≤80. Smell testing demonstrated different degrees of microsmia in 8 participants (66%). Brain MRI scans were normal, except 1 patient with bilateral olfactory bulb hypoplasia that was likely congenital. CSF analysis showed evidence of unique intrathecal oligoclonal bands in 3 cases (25%). Immunophenotyping of CSF compared with HVs showed that patients with neuro-PASC had lower frequencies of effector memory phenotype both for CD4+ T cells (p < 0.0001) and for CD8+ T cells (p = 0.002), an increased frequency of antibody-secreting B cells (p = 0.009), and increased frequency of cells expressing immune checkpoint molecules. On autonomic testing, there was evidence for decreased baroreflex-cardiovagal gain (p = 0.009) and an increased peripheral resistance during tilt-table testing (p < 0.0001) compared with HVs, without excessive plasma catecholamine responses. DISCUSSION CSF immune dysregulation and neurocirculatory abnormalities after SARS-CoV-2 infection in the setting of disabling neuro-PASC call for further evaluation to confirm these changes and explore immunomodulatory treatments in the context of clinical trials.
Collapse
Affiliation(s)
- Yair Mina
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Yoshimi Enose-Akahata
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Dima A Hammoud
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Anthony J Videckis
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Sandeep R Narpala
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Sarah E O'Connell
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Robin Carroll
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Bob C Lin
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Cynthia Chen McMahan
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Govind Nair
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Lauren B Reoma
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Adrian B McDermott
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Brian Walitt
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Steven Jacobson
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - David S Goldstein
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Bryan R Smith
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Avindra Nath
- From the National Institute of Neurological Disorders and Stroke (Y.M., Y.E.-A., A.J.V., C.C.M., G.N., L.B.R., B.W., S.J., D.S.G., B.R.S., A.N.), National Institutes of Health, Bethesda, MD; Sackler Faculty of Medicine (Y.M.), Tel-Aviv University, Israel; Center for Infectious Disease Imaging (D.A.H.), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health; and Vaccine Immunology Program (S.R.N., S.E.O.C., R.C., B.C.L., A.B.M.), Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD.
| |
Collapse
|
13
|
McMahan C, Dietrich DK, Horne EF, Kelly E, Geannopoulos K, Siyahhan Julnes PS, Ham L, Santamaria U, Lau CY, Wu T, Hsieh HC, Ganesan A, Berjohn C, Kapetanovic S, Reich DS, Nair G, Snow J, Agan BK, Nath A, Smith BR. Neurocognitive Dysfunction With Neuronal Injury in People With HIV on Long-Duration Antiretroviral Therapy. Neurology 2023:WNL.0000000000207339. [PMID: 37105760 DOI: 10.1212/wnl.0000000000207339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 03/09/2023] [Indexed: 04/29/2023] Open
Abstract
BackgroundNeurologic outcomes in people with HIV (PWH) on long-duration antiretroviral therapy (ART) are not fully understood and the underlying pathophysiology is unclear. To address this, we established a cohort of such individuals and compared them to HIV-negative controls using a novel matching technique. Both groups underwent extensive cognitive testing, evaluation for psychiatric measures, and MRI and cerebrospinal fluid (CSF) analyses.MethodsParticipants underwent comprehensive neuropsychological (NP) testing and completed standardized questionnaires measuring depressive symptoms, perceptions of own functioning, and activities of daily living as part of an observational study. Brain MRI and lumbar puncture were optional. Coarsened Exact Matching (CEM) was used to reduce between-group differences in age and sex, and weighted linear/logistic regression models were used to assess the effect of HIV on outcomes.ResultsData were analyzed from 155 PWH on ART for at least 15 years and 100 HIV-negative controls. Compared to controls, PWH scored lower in the domains of attention/working memory (PWH Least Square Mean [LSM]=50.4 vs. controls LSM=53.1, p=0.008) and motor function (44.6 vs. 47.7, p=0.009), and a test of information processing speed (symbol search 30.3 vs. 32.2, p=0.003). They were more likely to self-report a higher number of cognitive difficulties in everyday life (p=0.011). PWH also reported more depressive symptoms, general anxiety, and use of psychiatric medications (all with p<0.05). PWH had reduced proportions of subcortical gray matter on MRI (β=-0.001, p<0.001) and CSF showed elevated levels of neurofilament-light chain (664 vs. 529 pg/mL, p=0.01) and TNF-α (0.229 vs. 0.156 ng/mL, p=0.0008).ConclusionsPWH, despite effective ART for over a decade, displayed neurocognitive deficits and mood abnormalities. MRI and CSF analyses revealed reduced brain volume and signs of ongoing neuronal injury and neuroinflammation. As the already large proportion of virologically controlled PWH continues to grow, longitudinal studies should be conducted to elucidate the implications of cognitive, psychiatric, MRI, and CSF abnormalities in this group.
Collapse
Affiliation(s)
- Cynthia McMahan
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Devon K Dietrich
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
| | - Elizabeth F Horne
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Duke University School of Medicine, Durham, NC
| | - Erin Kelly
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Virginia Commonwealth University School of Medicine, Richmond, VA
| | - Katrina Geannopoulos
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Department of Neurology, Case Western Reserve University/University Hospitals Cleveland Medical Center, Cleveland, OH
| | - Peter Selim Siyahhan Julnes
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Lillian Ham
- Office of the Clinical Director, NIMH, NIH, Bethesda, MD
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA
| | | | - Chuen-Yen Lau
- HIV Dynamics and Replication Program, NCI, NIH, Bethesda, MD
| | - Tianxia Wu
- Office of the Clinical Director, NINDS, NIH, Bethesda, MD
| | - Hsing-Chuan Hsieh
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
| | - Anuradha Ganesan
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
- Department of Medicine, Uniformed Services University, Bethesda, MD
| | - Catherine Berjohn
- Division of Infectious Diseases, Naval Medical Center San Diego, San Diego, CA
| | - Suad Kapetanovic
- Department of Psychiatry and the Behavioral Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA
| | - Daniel S Reich
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD
| | - Govind Nair
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD
| | - Joseph Snow
- Office of the Clinical Director, NIMH, NIH, Bethesda, MD
| | - Brian K Agan
- Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD
- Department of Medicine, Uniformed Services University, Bethesda, MD
| | - Avindra Nath
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
| | - Bryan R Smith
- Section of Infections of the Nervous System, NINDS, NIH, Bethesda, MD
| |
Collapse
|
14
|
Manning AR, Beck ES, Schindler MK, Nair G, Clark KA, Parvathaneni P, Reich DS, Shinohara RT, Solomon AJ. T 1 /T 2 ratio from 3T MRI improves multiple sclerosis cortical lesion contrast. J Neuroimaging 2023; 33:434-445. [PMID: 36715449 PMCID: PMC10175128 DOI: 10.1111/jon.13088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND AND PURPOSE Cortical demyelinated lesions are prevalent in multiple sclerosis (MS), associated with disability, and have recently been incorporated into MS diagnostic criteria. Presently, advanced and ultrahigh-field MRIs-not routinely available in clinical practice-are the most sensitive methods for detection of cortical lesions. Approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need. We plan to assess the sensitivity of the ratio of T1 -weighted and T2 -weighted (T1 /T2 ) signal intensity for focal cortical lesions in comparison to other high-field imaging methods. METHODS 3-Tesla and 7-Tesla MRI collected from 10 adults with MS were included in the study. T1 /T2 images were calculated by dividing 3T T1 -weighted (T1 w) images by 3T T2 -weighted (T2 w) fluid-attenuated inversion recovery images for each participant. A total of 614 cortical lesions were identified using 7T T2 *w and T1 w images and corresponding voxels were assessed on registered 3T images. Signal intensities were compared across 3T imaging sequences, including T1 /T2 , T1 w, T2 w, and inversion recovery susceptibility-weighted imaging with enhanced T2 weighting (IR-SWIET) images. RESULTS T1 /T2 images demonstrated a larger contrast between median lesional and nonlesional cortical signal intensity (median ratio = 1.29, range: 1.19-1.38) when compared to T1 w (1.01, 0.97-1.10, p < .002), T2 w (1.17, 1.07-1.26, p < .002), and IR-SWIET (1.21, 1.01-1.29, p < .03). CONCLUSION T1 /T2 images are sensitive to cortical lesions. Approaches incorporating T1 /T2 could improve the accessibility of cortical lesion detection in research settings and clinical practice.
Collapse
Affiliation(s)
- Abigail R Manning
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Matthew K Schindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Kelly A Clark
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Prasanna Parvathaneni
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at The University of Vermont, Burlington, Vermont, USA
| |
Collapse
|
15
|
Chen AA, Clark K, Dewey B, DuVal A, Pellegrini N, Nair G, Jalkh Y, Khalil S, Zurawski J, Calabresi P, Reich D, Bakshi R, Shou H, Shinohara RT. Deconfounded Dimension Reduction via Partial Embeddings. bioRxiv 2023:2023.01.10.523448. [PMID: 36711940 PMCID: PMC9882043 DOI: 10.1101/2023.01.10.523448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. Our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.
Collapse
Affiliation(s)
- Andrew A. Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA
| | - Kelly Clark
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA
| | - Blake Dewey
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Anna DuVal
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nicole Pellegrini
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Youmna Jalkh
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Samar Khalil
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Jon Zurawski
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Peter Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Daniel Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Rohit Bakshi
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Haochang Shou
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA
| |
Collapse
|
16
|
Weng W, Birnie D, Sadek M, Ramirez F, Nery P, Nair G, Davis D, Redpath C, Klein A, Green M, Hansom S, Aydin A. CARDIAC IMPLANTABLE ELECTRONIC DEVICE LEAD PERFORATION RATES, MANAGEMENT AND OUTCOMES. Can J Cardiol 2022. [DOI: 10.1016/j.cjca.2022.08.076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
|
17
|
Geannopoulos K, McMahan C, Maldonado RS, Abbott A, Knickelbein J, Agron E, Wu T, Snow J, Nair G, Horne E, Lau CY, Nath A, Chew EY, Smith BR. Retinal Thinning in People With Well-Controlled HIV Infection. J Acquir Immune Defic Syndr 2022; 91:210-216. [PMID: 36094488 PMCID: PMC9475731 DOI: 10.1097/qai.0000000000003048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/16/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Retinal measurements correlate with disease progression in patients with multiple sclerosis; however, whether they associate with neurologic disease in people with controlled HIV is unknown. Using spectral domain optical coherence tomography, we evaluated retinal differences between people with HIV and HIV-negative controls and investigated clinical correlates of retinal thinning. METHODS People with HIV on antiretroviral therapy for at least 1 year and HIV-negative controls recruited from the same communities underwent spectral domain optical coherence tomography, ophthalmic examination, brain MRI, and neuropsychological testing. Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GC-IPL) thicknesses were compared between groups using analysis of covariance with relevant clinical variables as covariates. Linear regression was used to explore associations of HIV history variables, cognitive domain scores, and MRI volume measurements within the HIV group. RESULTS The HIV group (n = 69), with long-duration HIV infection (median time from diagnosis 19 years) and outstanding viral control have thinner retinal layers than HIV-negative controls (n = 28), after adjusting for covariates (GC-IPL: P = 0.002; RNFL: P = 0.024). The effect of HIV on GC-IPL thickness was stronger in women than in men (Women: P = 0.011; Men: P = 0.126). GC-IPL thickness is associated with information processing speed in the HIV group (P = 0.007, semipartial r = 0.309). No associations were found with retinal thinning and MRI volumes or HIV factors. CONCLUSIONS People with HIV on antiretroviral therapy have thinning of the RNFL and GC-IPL of the retina, and women particularly are affected to a greater degree. This retinal thinning was associated with worse performance on tests of information processing speed.
Collapse
Affiliation(s)
- Katrina Geannopoulos
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
- College of Medicine, University of Illinois, Chicago, IL
| | - Cynthia McMahan
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Ramiro S Maldonado
- National Eye Institute, National Institutes of Health, Bethesda, MD
- College of Medicine, University of Kentucky, Lexington, KY
| | - Akshar Abbott
- National Eye Institute, National Institutes of Health, Bethesda, MD
- Veterans Affairs Medical Center, University of Minnesota, Minneapolis, MN
| | - Jared Knickelbein
- National Eye Institute, National Institutes of Health, Bethesda, MD
- University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Elvira Agron
- National Eye Institute, National Institutes of Health, Bethesda, MD
| | - Tianxia Wu
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Joseph Snow
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Govind Nair
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Elizabeth Horne
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
- Duke University School of Medicine, Durham, NC; and
| | - Chuen-Yen Lau
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Avindra Nath
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Emily Y Chew
- National Eye Institute, National Institutes of Health, Bethesda, MD
| | - Bryan R Smith
- National Institute of National Disorders and Stroke, National Institutes of Health, Bethesda, MD
| |
Collapse
|
18
|
Arnold TC, Tu D, Okar SV, Nair G, By S, Kawatra KD, Robert-Fitzgerald TE, Desiderio LM, Schindler MK, Shinohara RT, Reich DS, Stein JM. Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions. Neuroimage Clin 2022; 35:103101. [PMID: 35792417 PMCID: PMC9421456 DOI: 10.1016/j.nicl.2022.103101] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 12/25/2022]
Abstract
Paired, same-day, 3T and 64mT MRI studies were analyzed in 33 MS patients. 64mT MRI showed 94% sensitivity for detecting any lesions in 3T confirmed cases. The diameter of the smallest detected lesion was larger at 64mT compared to 3T. Total lesion volume estimates were strongly correlated between 3T and 64mT scans. Portable low-field MRI detects white matter lesions, but smaller lesions may be missed.
Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34–0.5 × 0.34–0.5 × 3–5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = –19.0–15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.
Collapse
Affiliation(s)
- T Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danni Tu
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Serhat V Okar
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | | | - Karan D Kawatra
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - Timothy E Robert-Fitzgerald
- Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lisa M Desiderio
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew K Schindler
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD 20892, USA.
| | - Joel M Stein
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| |
Collapse
|
19
|
Kouli O, Murray V, Bhatia S, Cambridge WA, Kawka M, Shafi S, Knight SR, Kamarajah SK, McLean KA, Glasbey JC, Khaw RA, Ahmed W, Akhbari M, Baker D, Borakati A, Mills E, Thavayogan R, Yasin I, Raubenheimer K, Ridley W, Sarrami M, Zhang G, Egoroff N, Pockney P, Richards T, Bhangu A, Creagh-Brown B, Edwards M, Harrison EM, Lee M, Nepogodiev D, Pinkney T, Pearse R, Smart N, Vohra R, Sohrabi C, Jamieson A, Nguyen M, Rahman A, English C, Tincknell L, Kakodkar P, Kwek I, Punjabi N, Burns J, Varghese S, Erotocritou M, McGuckin S, Vayalapra S, Dominguez E, Moneim J, Salehi M, Tan HL, Yoong A, Zhu L, Seale B, Nowinka Z, Patel N, Chrisp B, Harris J, Maleyko I, Muneeb F, Gough M, James CE, Skan O, Chowdhury A, Rebuffa N, Khan H, Down B, Fatimah Hussain Q, Adams M, Bailey A, Cullen G, Fu YXJ, McClement B, Taylor A, Aitken S, Bachelet B, Brousse de Gersigny J, Chang C, Khehra B, Lahoud N, Lee Solano M, Louca M, Rozenbroek P, Rozitis E, Agbinya N, Anderson E, Arwi G, Barry I, Batchelor C, Chong T, Choo LY, Clark L, Daniels M, Goh J, Handa A, Hanna J, Huynh L, Jeon A, Kanbour A, Lee A, Lee J, Lee T, Leigh J, Ly D, McGregor F, Moss J, Nejatian M, O'Loughlin E, Ramos I, Sanchez B, Shrivathsa A, Sincari A, Sobhi S, Swart R, Trimboli J, Wignall P, Bourke E, Chong A, Clayton S, Dawson A, Hardy E, Iqbal R, Le L, Mao S, Marinelli I, Metcalfe H, Panicker D, R HH, Ridgway S, Tan HH, Thong S, Van M, Woon S, Woon-Shoo-Tong XS, Yu S, Ali K, Chee J, Chiu C, Chow YW, Duller A, Nagappan P, Ng S, Selvanathan M, Sheridan C, Temple M, Do JE, Dudi-Venkata NN, Humphries E, Li L, Mansour LT, Massy-Westropp C, Fang B, Farbood K, Hong H, Huang Y, Joan M, Koh C, Liu YHA, Mahajan T, Muller E, Park R, Tanudisastro M, Wu JJG, Chopra P, Giang S, Radcliffe S, Thach P, Wallace D, Wilkes A, Chinta SH, Li J, Phan J, Rahman F, Segaran A, Shannon J, Zhang M, Adams N, Bonte A, Choudhry A, Colterjohn N, Croyle JA, Donohue J, Feighery A, Keane A, McNamara D, Munir K, Roche D, Sabnani R, Seligman D, Sharma S, Stickney Z, Suchy H, Tan R, Yordi S, Ahmed I, Aranha M, El Sabawy D, Garwood P, Harnett M, Holohan R, Howard R, Kayyal Y, Krakoski N, Lupo M, McGilberry W, Nepon H, Scoleri Y, Urbina C, Ahmad Fuad MF, Ahmed O, Jaswantlal D, Kelly E, Khan MHT, Naidu D, Neo WX, O'Neill R, Sugrue M, Abbas JD, Abdul-Fattah S, Azlan A, Barry K, Idris NS, Kaka N, Mc Dermott D, Mohammad Nasir MN, Mozo M, Rehal A, Shaikh Yousef M, Wong RH, Curran E, Gardner M, Hogan A, Julka R, Lasser G, Ní Chorráin N, Ting J, Browne R, George S, Janjua Z, Leung Shing V, Megally M, Murphy S, Ravenscroft L, Vedadi A, Vyas V, Bryan A, Sheikh A, Ubhi J, Vannelli K, Vawda A, Adeusi L, Doherty C, Fitzgerald C, Gallagher H, Gill P, Hamza H, Hogan M, Kelly S, Larry J, Lynch P, Mazeni NA, O'Connell R, O'Loghlin R, Singh K, Abbas Syed R, Ali A, Alkandari B, Arnold A, Arora E, Azam R, Breathnach C, Cheema J, Compton M, Curran S, Elliott JA, Jayasamraj O, Mohammed N, Noone A, Pal A, Pandey S, Quinn P, Sheridan R, Siew L, Tan EP, Tio SW, Toh VTR, Walsh M, Yap C, Yassa J, Young T, Agarwal N, Almoosawy SA, Bowen K, Bruce D, Connachan R, Cook A, Daniell A, Elliott M, Fung HKF, Irving A, Laurie S, Lee YJ, Lim ZX, Maddineni S, McClenaghan RE, Muthuganesan V, Ravichandran P, Roberts N, Shaji S, Solt S, Toshney E, Arnold C, Baker O, Belais F, Bojanic C, Byrne M, Chau CYC, De Soysa S, Eldridge M, Fairey M, Fearnhead N, Guéroult A, Ho JSY, Joshi K, Kadiyala N, Khalid S, Khan F, Kumar K, Lewis E, Magee J, Manetta-Jones D, Mann S, McKeown L, Mitrofan C, Mohamed T, Monnickendam A, Ng AYKC, Ortu A, Patel M, Pope T, Pressling S, Purohit K, Saji S, Shah Foridi J, Shah R, Siddiqui SS, Surman K, Utukuri M, Varghese A, Williams CYK, Yang JJ, Billson E, Cheah E, Holmes P, Hussain S, Murdock D, Nicholls A, Patel P, Ramana G, Saleki M, Spence H, Thomas D, Yu C, Abousamra M, Brown C, Conti I, Donnelly A, Durand M, French N, Goan R, O'Kane E, Rubinchik P, Gardiner H, Kempf B, Lai YL, Matthews H, Minford E, Rafferty C, Reid C, Sheridan N, Al Bahri T, Bhoombla N, Rao BM, Titu L, Chatha S, Field C, Gandhi T, Gulati R, Jha R, Jones Sam MT, Karim S, Patel R, Saunders M, Sharma K, Abid S, Heath E, Kurup D, Patel A, Ali M, Cresswell B, Felstead D, Jennings K, Kaluarachchi T, Lazzereschi L, Mayson H, Miah JE, Reinders B, Rosser A, Thomas C, Williams H, Al-Hamid Z, Alsadoun L, Chlubek M, Fernando P, Gaunt E, Gercek Y, Maniar R, Ma R, Matson M, Moore S, Morris A, Nagappan PG, Ratnayake M, Rockall L, Shallcross O, Sinha A, Tan KE, Virdee S, Wenlock R, Donnelly HA, Ghazal R, Hughes I, Liu X, McFadden M, Misbert E, Mogey P, O'Hara A, Peace C, Rainey C, Raja P, Salem M, Salmon J, Tan CH, Alves D, Bahl S, Baker C, Coulthurst J, Koysombat K, Linn T, Rai P, Sharma A, Shergill A, Ahmed M, Ahmed S, Belk LH, Choudhry H, Cummings D, Dixon Y, Dobinson C, Edwards J, Flint J, Franco Da Silva C, Gallie R, Gardener M, Glover T, Greasley M, Hatab A, Howells R, Hussey T, Khan A, Mann A, Morrison H, Ng A, Osmond R, Padmakumar N, Pervaiz F, Prince R, Qureshi A, Sawhney R, Sigurdson B, Stephenson L, Vora K, Zacken A, Cope P, Di Traglia R, Ferarrio I, Hackett N, Healicon R, Horseman L, Lam LI, Meerdink M, Menham D, Murphy R, Nimmo I, Ramaesh A, Rees J, Soame R, Dilaver N, Adebambo D, Brown E, Burt J, Foster K, Kaliyappan L, Knight P, Politis A, Richardson E, Townsend J, Abdi M, Ball M, Easby S, Gill N, Ho E, Iqbal H, Matthews M, Nubi S, Nwokocha JO, Okafor I, Perry G, Sinartio B, Vanukuru N, Walkley D, Welch T, Yates J, Yeshitila N, Bryans K, Campbell B, Gray C, Keys R, Macartney M, Chamberlain G, Khatri A, Kucheria A, Lee STP, Reese G, Roy choudhury J, Tan WYR, Teh JJ, Ting A, Kazi S, Kontovounisios C, Vutipongsatorn K, Amarnath T, Balasubramanian N, Bassett E, Gurung P, Lim J, Panjikkaran A, Sanalla A, Alkoot M, Bacigalupo V, Eardley N, Horton M, Hurry A, Isti C, Maskell P, Nursiah K, Punn G, Salih H, Epanomeritakis E, Foulkes A, Henderson R, Johnston E, McCullough H, McLarnon M, Morrison E, Cheung A, Cho SH, Eriksson F, Hedges J, Low Z, May C, Musto L, Nagi S, Nur S, Salau E, Shabbir S, Thomas MC, Uthayanan L, Vig S, Zaheer M, Zeng G, Ashcroft-Quinn S, Brown R, Hayes J, McConville R, French R, Gilliam A, Sheetal S, Shehzad MU, Bani W, Christie I, Franklyn J, Khan M, Russell J, Smolarek S, Varadarassou R, Ahmed SK, Narayanaswamy S, Sealy J, Shah M, Dodhia V, Manukyan A, O'Hare R, Orbell J, Chung I, Forenc K, Gupta A, Agarwal A, Al Dabbagh A, Bennewith R, Bottomley J, Chu TSM, Chu YYA, Doherty W, Evans B, Hainsworth P, Hosfield T, Li CH, McCullagh I, Mehta A, Thaker A, Thompson B, Virdi A, Walker H, Wilkins E, Dixon C, Hassan MR, Lotca N, Tong KS, Batchelor-Parry H, Chaudhari S, Harris T, Hooper J, Johnson C, Mulvihill C, Nayler J, Olutobi O, Piramanayagam B, Stones K, Sussman M, Weaver C, Alam F, Al Rawi M, Andrew F, Arrayeh A, Azizan N, Hassan A, Iqbal Z, John I, Jones M, Kalake O, Keast M, Nicholas J, Patil A, Powell K, Roberts P, Sabri A, Segue AK, Shah A, Shaik Mohamed SA, Shehadeh A, Shenoy S, Tong A, Upcott M, Vijayasingam D, Anarfi S, Dauncey J, Devindaran A, Havalda P, Komninos G, Mwendwa E, Norman C, Richards J, Urquhart A, Allan J, Cahya E, Hunt H, McWhirter C, Norton R, Roxburgh C, Tan JY, Ali Butt S, Hansdot S, Haq I, Mootien A, Sanchez I, Vainas T, Deliyannis E, Tan M, Vipond M, Chittoor Satish NN, Dattani A, De Carvalho L, Gaston-Grubb M, Karunanithy L, Lowe B, Pace C, Raju K, Roope J, Taylor C, Youssef H, Munro T, Thorn C, Wong KHF, Yunus A, Chawla S, Datta A, Dinesh AA, Field D, Georgi T, Gwozdz A, Hamstead E, Howard N, Isleyen N, Jackson N, Kingdon J, Sagoo KS, Schizas A, Yin L, Aung E, Aung YY, Franklin S, Han SM, Kim WC, Martin Segura A, Rossi M, Ross T, Tirimanna R, Wang B, Zakieh O, Ben-Arzi H, Flach A, Jackson E, Magers S, Olu abara C, Rogers E, Sugden K, Tan H, Veliah S, Walton U, Asif A, Bharwada Y, Bowley D, Broekhuizen A, Cooper L, Evans N, Girdlestone H, Ling C, Mann H, Mehmood N, Mulvenna CL, Rainer N, Trout I, Gujjuri R, Jeyaraman D, Leong E, Singh D, Smith E, Anderton J, Barabas M, Goyal S, Howard D, Joshi A, Mitchell D, Weatherby T, Badminton R, Bird R, Burtle D, Choi NY, Devalia K, Farr E, Fischer F, Fish J, Gunn F, Jacobs D, Johnston P, Kalakoutas A, Lau E, Loo YNAF, Louden H, Makariou N, Mohammadi K, Nayab Y, Ruhomaun S, Ryliskyte R, Saeed M, Shinde P, Sudul M, Theodoropoulou K, Valadao-Spoorenberg J, Vlachou F, Arshad SR, Janmohamed AM, Noor M, Oyerinde O, Saha A, Syed Y, Watkinson W, Ahmadi H, Akintunde A, Alsaady A, Bradley J, Brothwood D, Burton M, Higgs M, Hoyle C, Katsura C, Lathan R, Louani A, Mandalia R, Prihartadi AS, Qaddoura B, Sandland-Taylor L, Thadani S, Thompson A, Walshaw J, Teo S, Ali S, Bawa JH, Fox S, Gargan K, Haider SA, Hanna N, Hatoum A, Khan Z, Krzak AM, Li T, Pitt J, Tan GJS, Ullah Z, Wilson E, Cleaver J, Colman J, Copeland L, Coulson A, Davis P, Faisal H, Hassan F, Hughes JT, Jabr Y, Mahmoud Ali F, Nahaboo Solim ZN, Sangheli A, Shaya S, Thompson R, Cornwall H, De Andres Crespo M, Fay E, Findlay J, Groves E, Jones O, Killen A, Millo J, Thomas S, Ward J, Wilkins M, Zaki F, Zilber E, Bhavra K, Bilolikar A, Charalambous M, Elawad A, Eleni A, Fawdon R, Gibbins A, Livingstone D, Mala D, Oke SE, Padmakumar D, Patsalides MA, Payne D, Ralphs C, Roney A, Sardar N, Stefanova K, Surti F, Timms R, Tosney G, Bannister J, Clement NS, Cullimore V, Kamal F, Lendor J, McKay J, Mcswiggan J, Minhas N, Seneviratne K, Simeen S, Valverde J, Watson N, Bloom I, Dinh TH, Hirniak J, Joseph R, Kansagra M, Lai CKN, Melamed N, Patel J, Randev J, Sedighi T, Shurovi B, Sodhi J, Vadgama N, Abdulla S, Adabavazeh B, Champion A, Chennupati R, Chu K, Devi S, Haji A, Schulz J, Testa F, Davies P, Gurung B, Howell S, Modi P, Pervaiz A, Zahid M, Abdolrazaghi S, Abi Aoun R, Anjum Z, Bawa G, Bhardwaj R, Brown S, Enver M, Gill D, Gopikrishna D, Gurung D, Kanwal A, Kaushal P, Khanna A, Lovell E, McEvoy C, Mirza M, Nabeel S, Naseem S, Pandya K, Perkins R, Pulakal R, Ray M, Reay C, Reilly S, Round A, Seehra J, Shakeel NM, Singh B, Vijay Sukhnani M, Brown L, Desai B, Elzanati H, Godhaniya J, Kavanagh E, Kent J, Kishor A, Liu A, Norwood M, Shaari N, Wood C, Wood M, Brown A, Chellapuri A, Ferriman A, Ghosh I, Kulkarni N, Noton T, Pinto A, Rajesh S, Varghese B, Wenban C, Aly R, Barciela C, Brookes T, Corrin E, Goldsworthy M, Mohamed Azhar MS, Moore J, Nakhuda S, Ng D, Pillay S, Port S, Abdullah M, Akinyemi J, Islam S, Kale A, Lewis A, Manjunath T, McCabe H, Misra S, Stubley T, Tam JP, Waraich N, Chaora T, Ford C, Osinkolu I, Pong G, Rai J, Risquet R, Ainsworth J, Ayandokun P, Barham E, Barrett G, Barry J, Bisson E, Bridges I, Burke D, Cann J, Cloney M, Coates S, Cripps P, Davies C, Francis N, Green S, Handley G, Hathaway D, Hurt L, Jenkins S, Johnston C, Khadka A, McGee U, Morris D, Murray R, Norbury C, Pierrepont Z, Richards C, Ross O, Ruddy A, Salmon C, Shield M, Soanes K, Spencer N, Taverner S, Williams C, Wills-Wood W, Woodward S, Chow J, Fan J, Guest O, Hunter I, Moon WY, Arthur-Quarm S, Edwards P, Hamlyn V, McEneaney L, N D G, Pranoy S, Ting M, Abada S, Alawattegama LH, Ashok A, Carey C, Gogna A, Haglund C, Hurley P, Leelo N, Liu B, Mannan F, Paramjothy K, Ramlogan K, Raymond-Hayling O, Shanmugarajah A, Solichan D, Wilkinson B, Ahmad NA, Allan D, Amin A, Bakina C, Burns F, Cameron F, Campbell A, Cavanagh S, Chan SMZ, Chapman S, Chong V, Edelsten E, Ekpete O, El Sheikh M, Ghose R, Hassane A, Henderson C, Hilton-Christie S, Husain M, Hussain H, Javid Z, Johnson-Ogbuneke J, Johnston A, Khalil M, Leung TCC, Makin I, Muralidharan V, Naeem M, Patil P, Ravichandran S, Saraeva D, Shankey-Smith W, Sharma N, Swan R, Waudby-West R, Wilkinson A, Wright K, Balasubramanian A, Bhatti S, Chalkley M, Chou WK, Dixon M, Evans L, Fisher K, Gandhi P, Ho S, Lau YB, Lowe S, Meechan C, Murali N, Musonda C, Njoku P, Ochieng L, Pervez MU, Seebah K, Shaikh I, Sikder MA, Vanker R, Alom J, Bajaj V, Coleman O, Finch G, Goss J, Jenkins C, Kontothanassis A, Liew MS, Ng K, Outram M, Shakeel MM, Tawn J, Zuhairy S, Chapple K, Cinnamond A, Coleman S, George HA, Goulder L, Hare N, Hawksley J, Kret A, Luesley A, Mecia L, Porter H, Puddy E, Richardson G, Sohail B, Srikaran V, Tadross D, Tobin J, Tokidis E, Young L, Ashdown T, Bratsos S, Koomson A, Kufuor A, Lim MQ, Shah S, Thorne EPC, Warusavitarne J, Xu S, Abigail S, Ahmed A, Ahmed J, Akmal A, Al-Khafaji M, Amini B, Arshad M, Bogie E, Brazkiewicz M, Carroll M, Chandegra A, Cirelli C, Deng A, Fairclough S, Fung YJ, Gornell C, Green RL, Green SV, Gulamhussein AHM, Isaac AG, Jan R, Jegatheeswaran L, Knee M, Kotecha J, Kotecha S, Maxwell-Armstrong C, McIntyre C, Mendis N, Naing TKP, Oberman J, Ong ZX, Ramalingam A, Saeed Adam A, Tan LL, Towell S, Yadav J, Anandampillai R, Chung S, Hounat A, Ibrahim B, Jeyakumar G, Khalil A, Khan UA, Nair G, Owusu-Ayim M, Wilson M, Kanani A, Kilkelly B, Ogunmwonyi I, Ong L, Samra B, Schomerus L, Shea J, Turner O, Yang Y, Amin M, Blott N, Clark A, Feather A, Forrest M, Hague S, Hamilton K, Higginbotham G, Hope E, Karimian S, Loveday K, Malik H, McKenna O, Noor A, Onsiong C, Patel B, Radcliffe N, Shah P, Tye L, Verma K, Walford R, Yusufi U, Zachariah M, Casey A, Doré C, Fludder V, Fortescue L, Kalapu SS, Karel E, Khera G, Smith C, Appleton B, Ashaye A, Boggon E, Evans A, Faris Mahmood H, Hinchcliffe Z, Marei O, Silva I, Spooner C, Thomas G, Timlin M, Wellington J, Yao SL, Abdelrazek M, Abdelrazik Y, Bee F, Joseph A, Mounce A, Parry G, Vignarajah N, Biddles D, Creissen A, Kolhe S, K T, Lea A, Ledda V, O'Loughlin P, Scanlon J, Shetty N, Weller C, Abdalla M, Adeoye A, Bhatti M, Chadda KR, Chu J, Elhakim H, Foster-Davies H, Rabie M, Tailor B, Webb S, Abdelrahim ASA, Choo SY, Jiwa A, Mangam S, Murray S, Shandramohan A, Aghanenu O, Budd W, Hayre J, Khanom S, Liew ZY, McKinney R, Moody N, Muhammad-Kamal H, Odogwu J, Patel D, Roy C, Sattar Z, Shahrokhi N, Sinha I, Thomson E, Wonga L, Bain J, Khan J, Ricardo D, Bevis R, Cherry C, Darkwa S, Drew W, Griffiths E, Konda N, Madani D, Mak JKC, Meda B, Odunukwe U, Preest G, Raheel F, Rajaseharan A, Ramgopal A, Risbrooke C, Selvaratnam K, Sethunath G, Tabassum R, Taylor J, Thakker A, Wijesingha N, Wybrew R, Yasin T, Ahmed Osman A, Alfadhel S, Carberry E, Chen JY, Drake I, Glen P, Jayasuriya N, Kawar L, Myatt R, Sinan LOH, Siu SSY, Tjen V, Adeboyejo O, Bacon H, Barnes R, Birnie C, D'Cunha Kamath A, Hughes E, Middleton S, Owen R, Schofield E, Short C, Smith R, Wang H, Willett M, Zimmerman M, Balfour J, Chadwick T, Coombe-Jones M, Do Le HP, Faulkner G, Hobson K, Shehata Z, Beattie M, Chmielewski G, Chong C, Donnelly B, Drusch B, Ellis J, Farrelly C, Feyi-Waboso J, Hibell I, Hoade L, Ho C, Jones H, Kodiatt B, Lidder P, Ni Cheallaigh L, Norman R, Patabendi I, Penfold H, Playfair M, Pomeroy S, Ralph C, Rottenburg H, Sebastian J, Sheehan M, Stanley V, Welchman J, Ajdarpasic D, Antypas A, Azouaghe O, Basi S, Bettoli G, Bhattarai S, Bommireddy L, Bourne K, Budding J, Cookey-Bresi R, Cummins T, Davies G, Fabelurin C, Gwilliam R, Hanley J, Hird A, Kruczynska A, Langhorne B, Lund J, Lutchman I, McGuinness R, Neary M, Pampapathi S, Pang E, Podbicanin S, Rai N, Redhouse White G, Sujith J, Thomas P, Walker I, Winterton R, Anderson P, Barrington M, Bhadra K, Clark G, Fowler G, Gibson C, Hudson S, Kaminskaite V, Lawday S, Longshaw A, MacKrill E, McLachlan F, Murdeshwar A, Nieuwoudt R, Parker P, Randall R, Rawlins E, Reeves SA, Rye D, Sirkis T, Sykes B, Ventress N, Wosinska N, Akram B, Burton L, Coombs A, Long R, Magowan D, Ong C, Sethi M, Williams G, Chan C, Chan LH, Fernando D, Gaba F, Khor Z, Les JW, Mak R, Moin S, Ng Kee Kwong KC, Paterson-Brown S, Tew YY, Bardon A, Burrell K, Coldwell C, Costa I, Dexter E, Hardy A, Khojani M, Mazurek J, Raymond T, Reddy V, Reynolds J, Soma A, Agiotakis S, Alsusa H, Desai N, Peristerakis I, Adcock A, Ayub H, Bennett T, Bibi F, Brenac S, Chapman T, Clarke G, Clark F, Galvin C, Gwyn-Jones A, Henry-Blake C, Kerner S, Kiandee M, Lovett A, Pilecka A, Ravindran R, Siddique H, Sikand T, Treadwell K, Akmal K, Apata A, Barton O, Broad G, Darling H, Dhuga Y, Emms L, Habib S, Jain R, Jeater J, Kan CYP, Kathiravelupillai A, Khatkar H, Kirmani S, Kulasabanathan K, Lacey H, Lal K, Manafa C, Mansoor M, McDonald S, Mittal A, Mustoe S, Nottrodt L, Oliver P, Papapetrou I, Pattinson F, Raja M, Reyhani H, Shahmiri A, Small O, Soni U, Aguirrezabala Armbruster B, Bunni J, Hakim MA, Hawkins-Hooker L, Howell KA, Hullait R, Jaskowska A, Ottewell L, Thomas-Jones I, Vasudev A, Clements B, Fenton J, Gill M, Haider S, Lim AJM, Maguire H, McMullan J, Nicoletti J, Samuel S, Unais MA, White N, Yao PC, Yow L, Boyle C, Brady R, Cheekoty P, Cheong J, Chew SJHL, Chow R, Ganewatta Kankanamge D, Mamer L, Mohammed B, Ng Chieng Hin J, Renji Chungath R, Royston A, Sharrad E, Sinclair R, Tingle S, Treherne K, Wyatt F, Maniarasu VS, Moug S, Appanna T, Bucknall T, Hussain F, Owen A, Parry M, Parry R, Sagua N, Spofforth K, Yuen ECT, Bosley N, Hardie W, Moore T, Regas C, Abdel-Khaleq S, Ali N, Bashiti H, Buxton-Hopley R, Constantinides M, D'Afflitto M, Deshpande A, Duque Golding J, Frisira E, Germani Batacchi M, Gomaa A, Hay D, Hutchison R, Iakovou A, Iakovou D, Ismail E, Jefferson S, Jones L, Khouli Y, Knowles C, Mason J, McCaughan R, Moffatt J, Morawala A, Nadir H, Neyroud F, Nikookam Y, Parmar A, Pinto L, Ramamoorthy R, Richards E, Thomson S, Trainer C, Valetopoulou A, Vassiliou A, Wantman A, Wilde S, Dickinson M, Rockall T, Senn D, Wcislo K, Zalmay P, Adelekan K, Allen K, Bajaj M, Gatumbu P, Hang S, Hashmi Y, Kaur T, Kawesha A, Kisiel A, Woodmass M, Adelowo T, Ahari D, Alhwaishel K, Atherton R, Clayton B, Cockroft A, Curtis Lopez C, Hilton M, Ismail N, Kouadria M, Lee L, MacConnachie A, Monks F, Mungroo S, Nikoletopoulou C, Pearce L, Sara X, Shahid A, Suresh G, Wilcha R, Atiyah A, Davies E, Dermanis A, Gibbons H, Hyde A, Lawson A, Lee C, Leung-Tack M, Li Saw Hee J, Mostafa O, Nair D, Pattani N, Plumbley-Jones J, Pufal K, Ramesh P, Sanghera J, Saram S, Scadding S, See S, Stringer H, Torrance A, Vardon H, Wyn-Griffiths F, Brew A, Kaur G, Soni D, Tickle A, Akbar Z, Appleyard T, Figg K, Jayawardena P, Johnson A, Kamran Siddiqui Z, Lacy-Colson J, Oatham R, Rowlands B, Sludden E, Turnbull C, Allin D, Ansar Z, Azeez Z, Dale VH, Garg J, Horner A, Jones S, Knight S, McGregor C, McKenna J, McLelland T, Packham-Smith A, Rowsell K, Spector-Hill I, Adeniken E, Baker J, Bartlett M, Chikomba L, Connell B, Deekonda P, Dhar M, Elmansouri A, Gamage K, Goodhew R, Hanna P, Knight J, Luca A, Maasoumi N, Mahamoud F, Manji S, Marwaha PK, Mason F, Oluboyede A, Pigott L, Razaq AM, Richardson M, Saddaoui I, Wijeyendram P, Yau S, Atkins W, Liang K, Miles N, Praveen B, Ashai S, Braganza J, Common J, Cundy A, Davies R, Guthrie J, Handa I, Iqbal M, Ismail R, Jones C, Jones I, Lee KS, Levene A, Okocha M, Olivier J, Smith A, Subramaniam E, Tandle S, Wang A, Watson A, Wilson C, Chan XHF, Khoo E, Montgomery C, Norris M, Pugalenthi PP, Common T, Cook E, Mistry H, Shinmar HS, Agarwal G, Bandyopadhyay S, Brazier B, Carroll L, Goede A, Harbourne A, Lakhani A, Lami M, Larwood J, Martin J, Merchant J, Pattenden S, Pradhan A, Raafat N, Rothwell E, Shammoon Y, Sudarshan R, Vickers E, Wingfield L, Ashworth I, Azizi S, Bhate R, Chowdhury T, Christou A, Davies L, Dwaraknath M, Farah Y, Garner J, Gureviciute E, Hart E, Jain A, Javid S, Kankam HK, Kaur Toor P, Kaz R, Kermali M, Khan I, Mattson A, McManus A, Murphy M, Nair K, Ngemoh D, Norton E, Olabiran A, Parry L, Payne T, Pillai K, Price S, Punjabi K, Raghunathan A, Ramwell A, Raza M, Ritehnia J, Simpson G, Smith W, Sodeinde S, Studd L, Subramaniam M, Thomas J, Towey S, Tsang E, Tuteja D, Vasani J, Vio M, Badran A, Adams J, Anthony Wilkinson J, Asvandi S, Austin T, Bald A, Bix E, Carrick M, Chander B, Chowdhury S, Cooper Drake B, Crosbie S, D Portela S, Francis D, Gallagher C, Gillespie R, Gravett H, Gupta P, Ilyas C, James G, Johny J, Jones A, Kinder F, MacLeod C, Macrow C, Maqsood-Shah A, Mather J, McCann L, McMahon R, Mitham E, Mohamed M, Munton E, Nightingale K, O'Neill K, Onyemuchara I, Senior R, Shanahan A, Sherlock J, Spyridoulias A, Stavrou C, Stokes D, Tamang R, Taylor E, Trafford C, Uden C, Waddington C, Yassin D, Zaman M, Bangi S, Cheng T, Chew D, Hussain N, Imani-Masouleh S, Mahasivam G, McKnight G, Ng HL, Ota HC, Pasha T, Ravindran W, Shah K, Vishnu K S, Zaman S, Carr W, Cope S, Eagles EJ, Howarth-Maddison M, Li CY, Reed J, Ridge A, Stubbs T, Teasdaled D, Umar R, Worthington J, Dhebri A, Kalenderov R, Alattas A, Arain Z, Bhudia R, Chia D, Daniel S, Dar T, Garland H, Girish M, Hampson A, Kyriacou H, Lehovsky K, Mullins W, Omorphos N, Vasdev N, Venkatesh A, Waldock W, Bhandari A, Brown G, Choa G, Eichenauer CE, Ezennia K, Kidwai Z, Lloyd-Thomas A, Macaskill Stewart A, Massardi C, Sinclair E, Skajaa N, Smith M, Tan I, Afsheen N, Anuar A, Azam Z, Bhatia P, Davies-kelly N, Dickinson S, Elkawafi M, Ganapathy M, Gupta S, Khoury EG, Licudi D, Mehta V, Neequaye S, Nita G, Tay VL, Zhao S, Botsa E, Cuthbert H, Elliott J, Furlepa M, Lehmann J, Mangtani A, Narayan A, Nazarian S, Parmar C, Shah D, Shaw C, Zhao Z, Beck C, Caldwell S, Clements JM, French B, Kenny R, Kirk S, Lindsay J, McClung A, McLaughlin N, Watson S, Whiteside E, Alyacoubi S, Arumugam V, Beg R, Dawas K, Garg S, Lloyd ER, Mahfouz Y, Manobharath N, Moonesinghe R, Morka N, Patel K, Prashar J, Yip S, Adeeko ES, Ajekigbe F, Bhat A, Evans C, Farrugia A, Gurung C, Long T, Malik B, Manirajan S, Newport D, Rayer J, Ridha A, Ross E, Saran T, Sinker A, Waruingi D, Allen R, Al Sadek Y, Alves do Canto Brum H, Asharaf H, Ashman M, Balakumar V, Barrington J, Baskaran R, Berry A, Bhachoo H, Bilal A, Boaden L, Chia WL, Covell G, Crook D, Dadnam F, Davis L, De Berker H, Doyle C, Fox C, Gruffydd-Davies M, Hafouda Y, Hill A, Hubbard E, Hunter A, Inpadhas V, Jamshaid M, Jandu G, Jeyanthi M, Jones T, Kantor C, Kwak SY, Malik N, Matt R, McNulty P, Miles C, Mohomed A, Myat P, Niharika J, Nixon A, O'Reilly D, Parmar K, Pengelly S, Price L, Ramsden M, Turnor R, Wales E, Waring H, Wu M, Yang T, Ye TTS, Zander A, Zeicu C, Bellam S, Francombe J, Kawamoto N, Rahman MR, Sathyanarayana A, Tang HT, Cheung J, Hollingshead J, Page V, Sugarman J, Wong E, Chiong J, Fung E, Kan SY, Kiang J, Kok J, Krahelski O, Liew MY, Lyell B, Sharif Z, Speake D, Alim L, Amakye NY, Chandrasekaran J, Chandratreya N, Drake J, Owoso T, Thu YM, Abou El Ela Bourquin B, Alberts J, Chapman D, Rehnnuma N, Ainsworth K, Carpenter H, Emmanuel T, Fisher T, Gabrel M, Guan Z, Hollows S, Hotouras A, Ip Fung Chun N, Jaffer S, Kallikas G, Kennedy N, Lewinsohn B, Liu FY, Mohammed S, Rutherfurd A, Situ T, Stammer A, Taylor F, Thin N, Urgesi E, Zhang N, Ahmad MA, Bishop A, Bowes A, Dixit A, Glasson R, Hatta S, Hatt K, Larcombe S, Preece J, Riordan E, Fegredo D, Haq MZ, Li C, McCann G, Stewart D, Baraza W, Bhullar D, Burt G, Coyle J, Deans J, Devine A, Hird R, Ikotun O, Manchip G, Ross C, Storey L, Tan WWL, Tse C, Warner C, Whitehead M, Wu F, Court EL, Crisp E, Huttman M, Mayes F, Robertson H, Rosen H, Sandberg C, Smith H, Al Bakry M, Ashwell W, Bajaj S, Bandyopadhyay D, Browlee O, Burway S, Chand CP, Elsayeh K, Elsharkawi A, Evans E, Ferrin S, Fort-Schaale A, Iacob M, I K, Impelliziere Licastro G, Mankoo AS, Olaniyan T, Otun J, Pereira R, Reddy R, Saeed D, Simmonds O, Singhal G, Tron K, Wickstone C, Williams R, Bradshaw E, De Kock Jewell V, Houlden C, Knight C, Metezai H, Mirza-Davies A, Seymour Z, Spink D, Wischhusen S. Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study. Lancet Digit Health 2022; 4:e520-e531. [PMID: 35750401 DOI: 10.1016/s2589-7500(22)00069-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. METHODS We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). FINDINGS In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]). INTERPRETATION In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. FUNDING British Journal of Surgery Society.
Collapse
|
20
|
Al-Louzi O, Manukyan S, Donadieu M, Absinta M, Letchuman V, Calabresi B, Desai P, Beck ES, Roy S, Ohayon J, Pham DL, Thomas A, Jacobson S, Cortese I, Auluck PK, Nair G, Sati P, Reich DS. Lesion size and shape in central vein sign assessment for multiple sclerosis diagnosis: An in vivo and postmortem MRI study. Mult Scler 2022; 28:1891-1902. [PMID: 35674284 DOI: 10.1177/13524585221097560] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied. OBJECTIVE Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis. METHODS Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated. RESULTS CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm3, p = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives). CONCLUSION Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.
Collapse
Affiliation(s)
- Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sargis Manukyan
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Maxime Donadieu
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD; USA/IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy
| | - Vijay Letchuman
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Brent Calabresi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Parth Desai
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Erin S Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Snehashis Roy
- Section on Neural Function, National Institute of Mental Health, Bethesda, MD, USA
| | - Joan Ohayon
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Dzung L Pham
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Anish Thomas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Irene Cortese
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pavan K Auluck
- Human Brain Collection Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| |
Collapse
|
21
|
Dieckhaus H, Meijboom R, Okar S, Wu T, Parvathaneni P, Mina Y, Chandran S, Waldman AD, Reich DS, Nair G. Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation. Top Magn Reson Imaging 2022; 31:31-39. [PMID: 35767314 PMCID: PMC9258518 DOI: 10.1097/rmr.0000000000000296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 05/24/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data. MATERIALS AND METHODS C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison. RESULTS C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class. CONCLUSIONS These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF.
Collapse
Affiliation(s)
- Henry Dieckhaus
- qMRI Core Facility, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Serhat Okar
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Tianxia Wu
- Clinical Trials Unit, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Prasanna Parvathaneni
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Yair Mina
- Viral Immunology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
- Sackler Faculty of Medicine, Tel Aviv University, Israel
| | | | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Daniel S. Reich
- Translational Neuroradiology Section, NINDS, National Institutes of Health, Bethesda, MD, USA
| | - Govind Nair
- qMRI Core Facility, NINDS, National Institutes of Health, Bethesda, MD, USA
- Corresponding Author: Govind Nair, Room 5C440, 10 Center Drive, Bethesda MD 20892, ; 301-402-6391
| |
Collapse
|
22
|
Nair G, Venkatesan K, Nair A, Firoz IN, Haroon NN. COVID-19 vaccine hesitancy and influence of professional medical guidance. J Educ Health Promot 2022; 11:112. [PMID: 35677278 PMCID: PMC9170208 DOI: 10.4103/jehp.jehp_792_21] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 07/04/2021] [Indexed: 06/01/2023]
Abstract
BACKGROUND Vaccine hesitancy presents a major challenge during the COVID-19 pandemic. It is crucial to address the factors contributing to vaccine hesitancy necessary to control the associated morbidity and mortality. This study aimed to investigate the impact of professional medical guidance on the likelihood of receiving the COVID-19 vaccine in immigrants of USA and Canada. MATERIALS AND METHODS A total of 92 immigrants in the USA and Canada who predominantly spoke Malayalam were recruited using social media platforms. An online survey was administered investigating participants' confidence in receiving the COVID-19 vaccine. Following, a short webinar was conducted by a medical professional explaining the efficacy and safety of the vaccine. A postwebinar survey was immediately given assessing the confidence and likelihood of receiving the vaccine. SPSS was used to generate descriptive statistics and Pearson Chi-square analysis where appropriate. RESULTS Results revealed that participants who attended the webinar reported greater confidence in receiving the COVID-19 vaccine. There was a statistically significant difference between pre- and postwebinar confidence scores for the COVID-19 vaccine, χ2 (12, n = 80) = 43.34, P < 0.01. CONCLUSION Results from the current study demonstrate the successful delivery of professional medical guidance to the general public through online small-group sessions to help address the misconceptions surrounding the COVID-19 vaccine and combat vaccine hesitancy among vulnerable populations. Future studies should focus on interventions addressing vaccine hesitancy in larger and diverse populations and analyze other barriers to vaccination.
Collapse
Affiliation(s)
- Govind Nair
- Student, Greenwood Laboratory School, Springfield, Missouri, USA
| | - Kirthika Venkatesan
- Caribbean Medical University School of Medicine, 25 Pater Euwensweg, Willemstad, Curaçao
| | - Arjun Nair
- Undergraduate Student, Psychology, Neuroscience, and Behavior Program, McMaster University, Hamilton, Ontario, Canada
| | - Irene N. Firoz
- School of Medicine, Royal College of Surgeons in Ireland, 123 Stephen's Green, Dublin, D02 YN77, Ireland
| | - Nisha Nigil Haroon
- Department of Endocrinology and Internal Medicine, Northern Ontario School of Medicine, Sudbury, Ontario, Canada
| |
Collapse
|
23
|
Nair G, Ramasubbu R, Wilson S, Liao Q, Chambers M, Chan K. 396 Rotator Cuff Assessment Following Traumatic Anterior Shoulder Dislocation. Br J Surg 2022. [DOI: 10.1093/bjs/znac039.271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
Aim
Glenohumeral joint dislocation is the most common traumatic joint dislocation with a high recurrence rate correlating with age at first dislocation. There is an associated increased incidence in concurrent rotator cuff tears with increasing age affecting 40% aged 40–60. Patient care was assessed against BESS/BOA standard: These patients should have rotator cuff assessment and those aged 40–60 should undergo routine MRI/Ultrasound imaging.
Method
All patients admitted to the emergency departments of the 3 Lanarkshire hospitals undergoing first time traumatic anterior dislocation of the shoulder in February 2021 were included. This was the third cycle of this audit. Previous interventions were presentation at a CPD meeting after cycle one and an NHS Lanarkshire regional meeting after cycle two.
Results
Cycle one (2018)-14 patients. 3/14 underwent rotator cuff assessment. 5/14 aged 40–60. 1/5 underwent rotator cuff imaging.
Cycle two (2020)-11 patients. 0/9 underwent rotator cuff assessment (Two excluded as managed operatively). 4/11 aged 40–60. 0/4 underwent rotator cuff imaging.
Cycle three (2021)-13 patients. 3/11 underwent rotator cuff assessment (Two excluded as managed operatively). 3/13 aged 40–60. 0/3 underwent rotator cuff imaging.
Conclusions
Although a slight improvement has been made over the 3 cycles with rotator cuff assessment the BOA standard is not being met. There has been no improvement in the additional imaging required in traumatic anterior shoulder dislocations in those aged 40–60 over the 3 cycles. These patients may develop pain, reduced function, and rotator cuff arthropathy. There is now an aim to introduce a pathway for these patients across the health board.
Collapse
Affiliation(s)
- G. Nair
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - R. Ramasubbu
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - S. Wilson
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - Q. Liao
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - M. Chambers
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - K. Chan
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| |
Collapse
|
24
|
Nair G, Haque S, Wilson M. 408 Blood Parameters as an Early Indicator of Complications Following Oesophagogastric Resection. Br J Surg 2022. [DOI: 10.1093/bjs/znac039.277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Aim
Oesophageal and gastric cancers are the eighth and fifth most prevalent cancers with a high degree of morbidity and mortality. Oesophagogastric resections are associated with a high degree of complications postoperatively. Complications following resection are associated with poorer hospital recovery, recurrence of cancer, readmission to hospital and increased mortality. A study was carried out to examine if there was an association between post-operative bloods and the development of complications.
Method
Data was collected from theatre logbooks, Integrated Clinical Environment (ICE) and clinical portal. Patients undergoing oesophagogastric resection for gastric and oesophageal cancer between October 2010 and November 2014 were included. Complications were organised using the Clavien Dindo classification. Data was analysed using the Student’ T test and Chi-Squared test. A P-value of 0.05 was classed as being statiscally significant.
Results
94 patients met the inclusion criteria for this study. 55 patients (58.5%) underwent Oesophagectomy, 18 (19.1%) total gastrectomy and 21 (22.3%) partial gastrectomy. A significant association was seen between development of complications and higher Day 5 White Cell count (WCC) (p = 0.048), lower Day 2–5 Albumin (Day 2 Albumin p = 0.038) and higher Day 2–5 C Reactive Protein (CRP) (Day 2 CRP p<0.001).
Conclusions
This study suggests Albumin, CRP and WCC may be used to predict postoperative complications in patients undergoing oesophagogastric resections for malignancy. Changes in the blood parameters present as early as day 2 postoperatively and can highlight patients who require closer monitoring, allowing earlier re-intervention if required.
Collapse
Affiliation(s)
- G. Nair
- Ninewells' Hospital, Dundee, United Kingdom
- Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - S. Haque
- Ninewells' Hospital, Dundee, United Kingdom
| | - M. Wilson
- Ninewells' Hospital, Dundee, United Kingdom
| |
Collapse
|
25
|
Nair G, Silverwood R, Jeyakumar G, Davison M, Bailey O. 403 The Difficulties of Managing Trauma in Elderly Patients in a West of Scotland Trauma Unit. Br J Surg 2022. [DOI: 10.1093/bjs/znac039.275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
Aim
An increasing number of elderly patients require admission to Trauma & Orthopaedic units throughout Scotland with admissions often complex and lengthy. We aimed to assess the current standard of care within a west of Scotland trauma unit against the 2019 British Orthopaedic Associations Standard of Care (BOAST) - “The care of the older or frail orthopaedic trauma patient” and devise a multi-disciplinary quality improvement strategy.
Method
All patients over the age of 65 admitted to the Trauma & Orthopaedic department of the University Hospital Wishaw between the 1st-14th of August 2020 were included. Online medical records were assessed and compared to the BOAST guideline. Results were presented to Orthopaedic and Care of the elderly (COTE) team and postgraduate teaching before being re-audited from 1st-14th May 2021. Data was analysed using Chi- Squared test.
Results
Cycle one vs Cycle two:
Falls risk assessment was carried out in 50/57(87.7%) vs 49/57(86.0%); Nutritional assessment carried out in 53/57(93.0%) vs 50/57(87.7%); Delirium assessment carried out in 54/57(94.7%) vs 47/57(82.5%). More patients were reviewed by Acute Care of the Elderly nurses 24/57(42.1%) vs 30/57(52.6%). No significant improvement was seen in the percentage of patients reviewed by a COTE consultant:15/57(26.3%) vs 17/57(29.8%) (P = 0.68).
Conclusions
Both cycles show good concordance with the BOAST criteria, including physiotherapy reviews, falls and delirium assessment, however significant deficiencies exist, including the provision of COTE input. This has prompted a reconfiguration of orthogeriatric input for trauma patients, with significant investment in the recruitment of COTE medical staff.
Collapse
Affiliation(s)
- G. Nair
- University Hospital Wishaw, South Lanarkshire, United Kingdom
- Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - R. Silverwood
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - G. Jeyakumar
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - M. Davison
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| | - O. Bailey
- University Hospital Wishaw, South Lanarkshire, United Kingdom
| |
Collapse
|
26
|
Beck ES, Maranzano J, Luciano NJ, Parvathaneni P, Filippini S, Morrison M, Suto DJ, Wu T, van Gelderen P, de Zwart JA, Antel S, Fetco D, Ohayon J, Andrada F, Mina Y, Thomas C, Jacobson S, Duyn J, Cortese I, Narayanan S, Nair G, Sati P, Reich DS. Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis. Mult Scler 2022; 28:1351-1363. [PMID: 35142571 DOI: 10.1177/13524585211069167] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course. OBJECTIVE Characterize cortical lesions by 7 tesla (T) T2*-/T1-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability. METHODS Sixty-four adults with MS (45 relapsing-remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing. RESULTS Cortical lesions were found in 94% (progressive: median 56/range 2-203; relapsing-remitting: 15/0-168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform (p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated (r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated (r = 0.30, p = 0.002). Leukocortical (p = 0.02) but not subpial lesions (p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions (p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores. CONCLUSION Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.
Collapse
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
| |
Collapse
|
27
|
MATUROSTRAKUL B, Bhaskaran M, Jang H, Nair V, Nair G, Abate M, Teperman L, Grodstein E. POS-781 THROMBOTIC MICROANGIOPATHY IN RENAL TRANSPLANT RECIPIENT WITH NPHS 2 GENE MUTATION. Kidney Int Rep 2022. [DOI: 10.1016/j.ekir.2022.01.817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
|
28
|
Weng W, Theriault-Lauzier P, Birnie D, Nair G, Nery P, Sadek M, Golian M, Klein A, Redpath C, Ramirez F, Davis D, Green M, Aydin A. LONG TERM SAFETY OF ABANDONED CARDIAC IMPLANTABLE ELECTRONIC DEVICES. Can J Cardiol 2021. [DOI: 10.1016/j.cjca.2021.07.090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
|
29
|
Kolb H, Absinta M, Beck ES, Ha SK, Song Y, Norato G, Cortese I, Sati P, Nair G, Reich DS. 7T MRI Differentiates Remyelinated from Demyelinated Multiple Sclerosis Lesions. Ann Neurol 2021; 90:612-626. [PMID: 34390015 PMCID: PMC9291186 DOI: 10.1002/ana.26194] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 08/10/2021] [Accepted: 08/12/2021] [Indexed: 12/13/2022]
Abstract
Objective To noninvasively assess myelin status in chronic white matter lesions of multiple sclerosis (MS), we developed and evaluated a simple classification scheme based on T1 relaxation time maps derived from 7‐tesla postmortem and in vivo MRI. Methods Using the MP2RAGE MRI sequence, we classified 36 lesions from 4 postmortem MS brains as “long‐T1,” “short‐T1,” and “mixed‐T1” by visual comparison to neocortex. Within these groups, we compared T1 times to histologically derived measures of myelin and axons. We performed similar analysis of 235 chronic lesions with known date of onset in 25 MS cases in vivo and in a validation cohort of 222 lesions from 66 MS cases, investigating associations with clinical and radiological outcomes. Results Postmortem, lesions classified qualitatively as long‐T1, short‐T1, and mixed‐T1 corresponded to fully demyelinated, fully remyelinated, and mixed demyelinated/remyelinated lesions, respectively (p ≤ 0.001). Demyelination (rather than axon loss) dominantly contributed to initial T1 prolongation. We observed lesions with similar characteristics in vivo, allowing manual classification with substantial interrater and excellent intrarater reliability. Short‐T1 lesions were most common in the deep white matter, whereas long‐T1 and mixed‐T1 lesions were prevalent in the juxtacortical and periventricular white matter (p = 0.02) and were much more likely to have paramagnetic rims suggesting chronic inflammation (p < 0.001). Older age at the time of lesion formation portended less remyelination (p = 0.007). Interpretation 7‐tesla T1 mapping with MP2RAGE, a clinically available MRI method, allows qualitative and quantitative classification of chronic MS lesions according to myelin content, rendering straightforward the tracking of lesional myelination changes over time. ANN NEUROL 2021;90:612–626
Collapse
Affiliation(s)
- Hadar Kolb
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD.,Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yafo, Israel
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University, Baltimore, MD.,Vita-Salute San Raffaele University, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Erin S Beck
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD
| | - Seung-Kwon Ha
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD.,Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA
| | - Yeajin Song
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD
| | - Gina Norato
- Clinical Trials Unit, NINDS, NIH, Bethesda, MD
| | | | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD.,Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, CA, Los Angeles
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD.,qMRI Core Facility, NINDS, NIH, Bethesda, MD
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD
| |
Collapse
|
30
|
Klein B, Kolm I, Nair G, Nägeli MC. Toxic epidermal necrolysis-like acute cutaneous graft-versus-host disease in a stem cell recipient - a diagnostic dilemma. J Eur Acad Dermatol Venereol 2021; 35:e585-e587. [PMID: 33914967 DOI: 10.1111/jdv.17310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- B Klein
- Department of Dermatology, Venereology and Allergology, University Medical Center Leipzig, Leipzig, Germany
| | - I Kolm
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - G Nair
- Department of Hematology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - M C Nägeli
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| |
Collapse
|
31
|
Mina Y, Azodi S, Dubuche T, Andrada F, Osuorah I, Ohayon J, Cortese I, Wu T, Johnson KR, Reich DS, Nair G, Jacobson S. Cervical and thoracic cord atrophy in multiple sclerosis phenotypes: Quantification and correlation with clinical disability. Neuroimage Clin 2021; 30:102680. [PMID: 34215150 PMCID: PMC8131917 DOI: 10.1016/j.nicl.2021.102680] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 04/15/2021] [Accepted: 04/16/2021] [Indexed: 12/01/2022]
Abstract
Spinal cord atrophy is prevalent across multiple sclerosis phenotypes. It correlates with disability, especially in relapsing-remitting patients. This correlation can be demonstrated both cross-sectionally and longitudinally. Cervical atrophy is highly associated with disability and disease progression. Thoracic atrophy contributes to improved correlation and radiological subgrouping.
Objective We sought to characterize spinal cord atrophy along the entire spinal cord in the major multiple sclerosis (MS) phenotypes, and evaluate its correlation with clinical disability. Methods Axial T1-weighted images were automatically reformatted at each point along the cord. Spinal cord cross‐sectional area (SCCSA) were calculated from C1-T10 vertebral body levels and profile plots were compared across phenotypes. Average values from C2-3, C4-5, and T4-9 regions were compared across phenotypes and correlated with clinical scores, and then categorized as atrophic/normal based on z-scores derived from controls, to compare clinical scores between subgroups. In a subset of relapsing-remitting cases with longitudinal scans these regions were compared to change in clinical scores. Results The cross-sectional study consisted of 149 adults diagnosed with relapsing-remitting MS (RRMS), 49 with secondary-progressive MS (SPMS), 58 with primary-progressive MS (PPMS) and 48 controls. The longitudinal study included 78 RRMS cases. Compared to controls, all MS groups had smaller average regions except RRMS in T4-9 region. In all MS groups, SCCSA from all regions, particularly the cervical cord, correlated with most clinical measures. In the RRMS cohort, 22% of cases had at least one atrophic region, whereas in progressive MS the rate was almost 70%. Longitudinal analysis showed correlation between clinical disability and cervical cord thinning. Conclusions Spinal cord atrophy was prevalent across MS phenotypes, with regional measures from the RRMS cohort and the progressive cohort, including SPMS and PPMS, being correlated with disability. Longitudinal changes in the spinal cord were documented in RRMS cases, making it a potential marker for disease progression. While cervical SCCSA correlated with most disability and progression measures, inclusion of thoracic measurements improved this correlation and allowed for better subgrouping of spinal cord phenotypes. Cord atrophy is an important and easily obtainable imaging marker of clinical and sub-clinical progression in all MS phenotypes, and such measures can play a key role in patient selection for clinical trials.
Collapse
Affiliation(s)
- Yair Mina
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Shila Azodi
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States; Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Tsemacha Dubuche
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Frances Andrada
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Ikesinachi Osuorah
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Joan Ohayon
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Irene Cortese
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Tianxia Wu
- Clinical Trials Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Kory R Johnson
- Bioinformatics Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Govind Nair
- Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States; Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States.
| |
Collapse
|
32
|
Nair G, Saraswathy G, Hema Sree G. 48P Target mining and drug repurposing for hepatocellular carcinoma via bioinformatic and computational approaches. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.01.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
33
|
Lee MH, Perl DP, Nair G, Li W, Maric D, Murray H, Dodd SJ, Koretsky AP, Watts JA, Cheung V, Masliah E, Horkayne-Szakaly I, Jones R, Stram MN, Moncur J, Hefti M, Folkerth RD, Nath A. Microvascular Injury in the Brains of Patients with Covid-19. N Engl J Med 2021; 384:481-483. [PMID: 33378608 PMCID: PMC7787217 DOI: 10.1056/nejmc2033369] [Citation(s) in RCA: 345] [Impact Index Per Article: 115.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Myoung-Hwa Lee
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Daniel P Perl
- Uniformed Services University of the Health Sciences, Bethesda, MD
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Wenxue Li
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Dragan Maric
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Helen Murray
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Stephen J Dodd
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - Alan P Koretsky
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | | | | | | | | | | | | | | | | | | | - Avindra Nath
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| |
Collapse
|
34
|
Kerbrat A, Gros C, Badji A, Bannier E, Galassi F, Combès B, Chouteau R, Labauge P, Ayrignac X, Carra-Dalliere C, Maranzano J, Granberg T, Ouellette R, Stawiarz L, Hillert J, Talbott J, Tachibana Y, Hori M, Kamiya K, Chougar L, Lefeuvre J, Reich DS, Nair G, Valsasina P, Rocca MA, Filippi M, Chu R, Bakshi R, Callot V, Pelletier J, Audoin B, Maarouf A, Collongues N, De Seze J, Edan G, Cohen-Adad J. Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability. Brain 2020; 143:2089-2105. [PMID: 32572488 DOI: 10.1093/brain/awaa162] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 02/27/2020] [Accepted: 04/02/2020] [Indexed: 11/12/2022] Open
Abstract
Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P < 0.0001). Voxel-wise analyses confirmed that lesion frequency was higher in progressive compared to relapsing-remitting patients, with significant bilateral clusters in the spinal cord corticospinal tracts (P < 0.01). The baseline Expanded Disability Status Scale score was associated with lesion volume fraction within the brain (r = 0.31, P < 0.0001), brainstem (r = 0.45, P < 0.0001) and spinal cord (r = 0.57, P < 0.0001) corticospinal tracts. The spinal cord corticospinal tracts lesion volume fraction remained the strongest factor in the multiple linear regression model, independently from cord atrophy. Baseline spinal cord corticospinal tracts lesion volume fraction was also associated with disability progression at 2-year follow-up (P = 0.003). Our results suggest a cumulative effect of lesions within the corticospinal tracts along the brain, brainstem and spinal cord portions to explain physical disability in multiple sclerosis patients, with a predominant impact of intramedullary lesions.
Collapse
Affiliation(s)
- Anne Kerbrat
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,Department of Neurosciences, Faculty of Medicine, Université de Montréal, QC, Canada
| | - Elise Bannier
- CHU Rennes, Radiology department, Rennes, France.,Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Francesca Galassi
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Benoit Combès
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1128, Rennes, France
| | - Raphaël Chouteau
- CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Pierre Labauge
- MS Unit, Department of Neurology, CHU Montpellier, Montpellier, France
| | - Xavier Ayrignac
- MS Unit, Department of Neurology, CHU Montpellier, Montpellier, France
| | | | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.,University of Quebec in Trois-Rivieres, Quebec, Canada
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | | | - Masaaki Hori
- Toho University Omori Medical Center, Tokyo, Japan
| | | | - Lydia Chougar
- Department of Neuroradiology, La Pitié Salpêtrière Hospital, Paris, France
| | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Paola Valsasina
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Renxin Chu
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Rohit Bakshi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Virginie Callot
- AP-HM, Pôle d'imagerie médicale, Hôpital de la Timone, CEMEREM, Marseille, France.,Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Jean Pelletier
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Bertrand Audoin
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Adil Maarouf
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Nicolas Collongues
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, INSERM U1119, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Bâtiment 3 de la Faculté de Médecine, 67 000 Strasbourg, France.,Département de Neurologie, Centre Hospitalier Universitaire de Strasbourg, 67200 Strasbourg, France.,Centre d'investigation Clinique, INSERM U1434, Centre Hospitalier Universitaire de Strasbourg, 67000 Strasbourg, France
| | - Jérôme De Seze
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, INSERM U1119, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Bâtiment 3 de la Faculté de Médecine, 67 000 Strasbourg, France.,Département de Neurologie, Centre Hospitalier Universitaire de Strasbourg, 67200 Strasbourg, France.,Centre d'investigation Clinique, INSERM U1434, Centre Hospitalier Universitaire de Strasbourg, 67000 Strasbourg, France
| | - Gilles Edan
- CHU Rennes, Neurology department, Empenn U 1128 Inserm, CIC1414 Inserm, Rennes, France
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.,Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada
| |
Collapse
|
35
|
Zhang X, Li CX, Yan Y, Nair G, Rilling JK, Herndon JG, Preuss TM, Hu X, Li L. In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T. Magn Reson Imaging 2020; 77:194-203. [PMID: 33359631 DOI: 10.1016/j.mri.2020.12.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 10/30/2020] [Accepted: 12/20/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Diffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. METHODS A multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. RESULTS The SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. CONCLUSION The single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.
Collapse
Affiliation(s)
- Xiaodong Zhang
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America; Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America.
| | - Chun-Xia Li
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Yumei Yan
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Govind Nair
- qMRI Core Facility, NINDS, NIH, Bethesda, MD 20892, United States of America
| | - James K Rilling
- Department of Anthropology, Emory University, Atlanta, GA, United States of America; Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - James G Herndon
- Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Todd M Preuss
- Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America
| | - Xiaoping Hu
- Dept of Bioengineering, University of California, Riverside, CA, United States of America
| | - Longchuan Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, United States of America.
| |
Collapse
|
36
|
Absinta M, Sati P, Masuzzo F, Nair G, Sethi V, Kolb H, Ohayon J, Wu T, Cortese ICM, Reich DS. Association of Chronic Active Multiple Sclerosis Lesions With Disability In Vivo. JAMA Neurol 2020; 76:1474-1483. [PMID: 31403674 DOI: 10.1001/jamaneurol.2019.2399] [Citation(s) in RCA: 255] [Impact Index Per Article: 63.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance In multiple sclerosis (MS), chronic active lesions, which previously could only be detected at autopsy, can now be identified on susceptibility-based magnetic resonance imaging (MRI) in vivo as non-gadolinium-enhancing lesions with paramagnetic rims. Pathologically, they feature smoldering inflammatory demyelination at the edge, remyelination failure, and axonal degeneration. To our knowledge, the prospect of long-term in vivo monitoring makes it possible for the first time to determine their contribution to disability and value as a treatment target. Objective To assess whether rim lesions are associated with patient disability and long-term lesion outcomes. Design, Setting, Participants We performed 3 studies at the National Institutes of Health Clinical Center: (1) a prospective clinical/radiological cohort of 209 patients with MS (diagnosis according to the 2010 McDonald revised MS criteria, age ≥18 years, with 7-T or 3-T susceptibility-based brain MRI results) who were enrolled from January 2012 to March 2018 (of 209, 17 patients [8%] were excluded because of uninterpretable MRI scans); (2) a radiological/pathological analysis of expanding lesions featuring rims; and (3) a retrospective longitudinal radiological study assessing long-term lesion evolution in 23 patients with MS with yearly MRI scans for 10 years or more (earliest scan, 1992). Main Outcomes and Measures (1) Identification of chronic rim lesions on 7-T or 3-T susceptibility-based brain MRI in 192 patients with MS and the association of rim counts with clinical disability (primary analysis) and brain volume changes (exploratory analysis). (2) Pathological characterization of 10 expanding lesions from an adult with progressive MS who came to autopsy after 7 years of receiving serial in vivo MRI scans. (3) Evaluation of annual lesion volume change (primary analysis) and T1 times (exploratory analysis) in 27 rim lesions vs 27 rimless lesions. Results Of 209 participants, 104 (50%) were women and 32 (15%) were African American. One hundred seventeen patients (56%) had at least 1 rim lesion regardless of prior or ongoing treatment. Further, 84 patients (40%) had no rims (mean [SD] age, 47 [14] years), 66 (32%) had 1 to 3 rims (mean [SD] age, 47 [11] years), and 42 (20%) had 4 rims or more (mean [SD] age, 44 [11] years). Individuals with 4 rim lesions or more reached motor and cognitive disability at an earlier age. Normalized volumes of brain, white matter, and basal ganglia were lower in those with rim lesions. Whereas rimless lesions shrank over time (-3.6%/year), rim lesions were stable in size or expanded (2.2%/year; P < .001). Rim lesions had longer T1 times, suggesting more tissue destruction, than rimless lesions. On histopathological analysis, all 10 rim lesions that expanded in vivo had chronic active inflammation. Conclusions and Relevance Chronic active lesions are common, are associated with more aggressive disease, exert ongoing tissue damage, and occur even in individuals treated with effective disease-modifying therapies. These results prompt the planning of MRI-based clinical trials aimed at treating perilesional chronic inflammation in MS.
Collapse
Affiliation(s)
- Martina Absinta
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Pascal Sati
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Federica Masuzzo
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Govind Nair
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Varun Sethi
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Hadar Kolb
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Joan Ohayon
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Tianxia Wu
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Irene C M Cortese
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| |
Collapse
|
37
|
Maggi P, Sati P, Nair G, Cortese IC, Jacobson S, Smith BR, Nath A, Ohayon J, van Pesch V, Perrotta G, Pot C, Théaudin M, Martinelli V, Scotti R, Wu T, Du Pasquier R, Calabresi PA, Filippi M, Reich DS, Absinta M. Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study. Ann Neurol 2020; 88:1034-1042. [PMID: 32799417 PMCID: PMC9943711 DOI: 10.1002/ana.25877] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 01/04/2023]
Abstract
In multiple sclerosis (MS), a subset of chronic active white matter lesions are identifiable on magnetic resonance imaging by their paramagnetic rims, and increasing evidence supports their association with severity of clinical disease. We studied their potential role in differential diagnosis, screening an international multicenter clinical research-based sample of 438 individuals affected by different neurological conditions (MS, other inflammatory, infectious, and non-inflammatory conditions). Paramagnetic rim lesions, rare in other neurological conditions (52% of MS vs 7% of non-MS cases), yielded high specificity (93%) in differentiating MS from non-MS. Future prospective multicenter studies should validate their role as a diagnostic biomarker. ANN NEUROL 2020;88:1034-1042.
Collapse
Affiliation(s)
- Pietro Maggi
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium;,Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Bruxelles, Belgium;,Service of Neurology, Department of clinical neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pascal Sati
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA;,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Govind Nair
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Irene C.M. Cortese
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Steven Jacobson
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Bryan R. Smith
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Avindra Nath
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Joan Ohayon
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Vincent van Pesch
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Gaetano Perrotta
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Caroline Pot
- Service of Neurology, Department of clinical neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Marie Théaudin
- Service of Neurology, Department of clinical neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Vittorio Martinelli
- Departments of Neurology and Neurophysiology and Neuroimaging Research Unit, Ospedale San Raffaele and Università Vita e Salute, Milan, Italy
| | - Roberta Scotti
- Department of Neuroradiology, Ospedale San Raffaele and Università Vita e Salute, Milan, Italy
| | - Tianxia Wu
- Clinical Trials Unit, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Renaud Du Pasquier
- Service of Neurology, Department of clinical neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Massimo Filippi
- Departments of Neurology and Neurophysiology and Neuroimaging Research Unit, Ospedale San Raffaele and Università Vita e Salute, Milan, Italy
| | - Daniel S. Reich
- Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|
38
|
Beck ES, Gai N, Filippini S, Maranzano J, Nair G, Reich DS. Inversion Recovery Susceptibility Weighted Imaging With Enhanced T2 Weighting at 3 T Improves Visualization of Subpial Cortical Multiple Sclerosis Lesions. Invest Radiol 2020; 55:727-735. [PMID: 32604385 PMCID: PMC7541598 DOI: 10.1097/rli.0000000000000698] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Cortical demyelination is common in multiple sclerosis (MS) and can be extensive. Cortical lesions contribute to disability independently from white matter lesions and may form via a distinct mechanism. However, current magnetic resonance imaging methods at 3 T are insensitive to cortical, and especially subpial cortical, lesions. Subpial lesions are well seen on T2*-weighted imaging at 7 T, but T2*-weighted methods on 3 T scanners are limited by poor lesion-to-cortex and cerebrospinal fluid-to-lesion contrast. We aimed to develop and evaluate a cerebrospinal fluid-suppressed, T2*-weighted sequence optimized for subpial cortical lesion visualization. MATERIALS AND METHODS We developed a new magnetic resonance imaging sequence, inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET; 0.8 mm × 0.8 mm in plane, 0.64 mm slice thickness with whole brain coverage, acquisition time ~5 minutes). We compared cortical lesion visualization independently on IR-SWIET (median signal from 4 acquisitions), magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE), double inversion recovery (DIR), T2*-weighted segmented echo-planar imaging, and phase-sensitive inversion recovery images for 10 adults with MS. We also identified cortical lesions with a multicontrast reading of IR-SWIET (median of 2 acquisitions), MP2RAGE, and fluid-attenuated inversion recovery (FLAIR) images for each case. Lesions identified on 3 T images were verified on "gold standard" 7 T T2* and MP2RAGE images. RESULTS Cortical, and particularly subpial, lesions appeared much more conspicuous on IR-SWIET compared with other 3 T methods. A total of 101 true-positive subpial lesions were identified on IR-SWIET (average per-participant sensitivity vs 7 T, 29% ± 8%) versus 36 on MP2RAGE (5% ± 2%; comparison to IR-SWIET sensitivity, P = 0.07), 17 on FLAIR (2% ± 1%; P < 0.05), 28 on DIR (6% ± 2%; P < 0.05), 42 on T2*-weighted segmented echo-planar imaging (11% ± 5%; P < 0.05), and 13 on phase-sensitive inversion recovery (4% ± 2%; P < 0.05). When a combination of IR-SWIET, MP2RAGE, and FLAIR images was used, a total of 147 subpial lesions (30% ± 5%) were identified versus 83 (16% ± 3%, P < 0.01) on a combination of DIR, MP2RAGE, and FLAIR. More cases had at least 1 subpial lesion on IR-SWIET, and IR-SWIET improved cortical lesion subtyping accuracy and correlation with 7 T subpial lesion number. CONCLUSIONS Subpial lesions are better visualized on IR-SWIET compared with other 3 T methods. A 3 T protocol combining IR-SWIET with MP2RAGE, in which leukocortical lesions are well seen, improves cortical lesion visualization over existing approaches. Therefore, IR-SWIET may enable improved MS diagnostic specificity and a better understanding of the clinical implications of cortical demyelination.
Collapse
Affiliation(s)
- Erin S Beck
- Clinical Neuroimmunology Fellow, Translational Neuroradiology Section (TNS), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Neville Gai
- Staff Scientist, Radiology and Imaging Sciences, Clinical Center, NIH, Bethesda, MD, NIH
| | - Stefano Filippini
- Visiting Fellow, Translational Neuroradiology Section (TNS), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
- Neurology Resident, Department of Neurosciences, Drug, and Child Health, University of Florence, Florence, Italy
| | - Josefina Maranzano
- Assistant Professor, University of Quebec in Trois-Rivieres, Trois-Rivieres, Quebec, Canada
| | - Govind Nair
- Staff Scientist, Translational Neuroradiology Section (TNS), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Daniel S Reich
- Senior Investigator, Translational Neuroradiology Section (TNS), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| |
Collapse
|
39
|
Gupta A, Fatemi A, Ducatman B, Khayyata S, Iftikhar H, Nair G. Pulmonary Capillaritis: The Breakdown of the Histologic Features. Am J Clin Pathol 2020. [DOI: 10.1093/ajcp/aqaa161.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Introduction/Objective
Capillary inflammation (capillaritis) is rarely the primary pathologic cause of pulmonary hemorrhage. It may coexist with vasculitis. The aim of this study is to investigate the specificity of five histologic features of pulmonary capillaritis previously described by Mark and Ramirez (discussed below). They are usually treated with corticosteroids and cyclophosphamide or azathioprine.
Methods
A retrospective review of patients with a pathologic diagnosis of capillaritis in open lung biopsies was done. The diagnosis was confirmed by two expert pulmonary pathologists. The slides were reviewed and compared to a control group, who also underwent open lung biopsies for clinical suggestion of pulmonary hemorrhage and no pathologic diagnosis of capillaritis. Cases with malignant neoplasms, large and medium size vasculitis syndromes, and diffuse alveolar damage (DAD) were excluded. The five pathologic features of capillaritis were evaluated and scored as negative (0), focal (1+) and moderate to diffuse (2+) in both groups.
Results
Five cases of pulmonary capillaritis and five cases in control group were identified. The etiology of pulmonary capillaritis in the five identified cases included autoimmune diseases, pulmonary hypertension, non-specific interstitial pneumonia, and idiopathic capillaritis. The average score for the morphologic features of capillaritis versus the control group were as follows: Interstitial erythrocytes and/or hemosiderin (2+ vs 2+), fibrinoid necrosis of capillary walls (2+vs 0), intraalveolar septal capillary occlusion by fibrin thrombi (1+ vs 0), neutrophils and nuclear dust in the interstitium, in the fibrin, and in the adjacent alveolar spaces (2+ vs 1+), and fibrin clots attached to interalveolar septa in a sessile manner (2+ vs 1+).
Conclusion
In this small study, we can conclude that fibrinous necrosis is the most specific finding for pulmonary capillaritis while interstitial erythrocytes and/or hemosiderin is least specific. Therefore, in the presence of fibrinous necrosis; in addition to other supporting features; a pathologist is more inclined to communicate a diagnosis of pulmonary capillaritis to the clinicians.
Collapse
Affiliation(s)
- A Gupta
- Pathology, Beaumont Hospital, Troy, Michigan, UNITED STATES
| | - A Fatemi
- Pathology, Beaumont Hospital, Troy, Michigan, UNITED STATES
| | - B Ducatman
- Pathology, Beaumont Hospital, Troy, Michigan, UNITED STATES
| | - S Khayyata
- Pathology, Beaumont Hospital, Troy, Michigan, UNITED STATES
| | - H Iftikhar
- Beaumont Hospital, Royal Oak, Michigan, UNITED STATES
| | - G Nair
- Beaumont Hospital, Royal Oak, Michigan, UNITED STATES
| |
Collapse
|
40
|
Mao B, Golian M, Nery P, Davis D, Green M, Birnie D, Sadek M, Nair G, Redpath C. OVER-READING OF CONTINUOUS CARDIAC TELEMETRY EMBEDDED IN THE ELECTRONIC MEDICAL RECORD IMPROVED OUTCOMES FOR UNSELECTED GENERAL CARDIOLOGY IN-PATIENTS. Can J Cardiol 2020. [DOI: 10.1016/j.cjca.2020.07.106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
|
41
|
Nair G, Dodd S, Ha SK, Koretsky AP, Reich DS. Ex vivo MR microscopy of a human brain with multiple sclerosis: Visualizing individual cells in tissue using intrinsic iron. Neuroimage 2020; 223:117285. [PMID: 32828923 PMCID: PMC7811778 DOI: 10.1016/j.neuroimage.2020.117285] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 07/27/2020] [Accepted: 08/15/2020] [Indexed: 01/30/2023] Open
Abstract
Purpose: To perform magnetic resonance microscopy (MRM) on human cortex and a cortical lesion as well as the adjacent normal appearing white matter. To shed light on the origins of MRI contrast by comparison with histochemical and immunostaining. Methods: 3D MRM at a nominal isotropic resolution of 15 and 18 μm was performed on 2 blocks of tissue from the brain of a 77-year-old man who had MS for 47 years. One block contained normal appearing cortical gray matter (CN block) and adjacent normal appearing white matter (NAWM), and the other also included a cortical lesion (CL block). Postmortem ex-vivo MRI was performed at 11.7T using a custom solenoid coil and T2*-weighted 3D GRE sequence. Histochemical and immunostaining were done after paraffin embedding for iron, myelin, oligodendrocytes, neurons, blood vessels, macrophages and microglia, and astrocytes. Results: MRM could identify individual iron-laden oligodendrocytes with high sensitivity (70% decrease in signal compared to surrounding) in CN and CL blocks, as well as some iron-laden activated macrophages and microglia. Iron-deficient oligodendrocytes seemed to cause relative increase in MRI signal within the cortical lesion. High concentration of myelin in the white matter was primarily responsible for its hypointense appearance relative to the cortex, however, signal variations within NAWM could be attributed to changes in density of iron-laden oligodendrocytes. Conclusion: Changes in iron accumulation within cells gave rise to imaging contrast seen between cortical lesions and normal cortex, as well as the patchy signal in NAWM. Densely packed myelin and collagen deposition also contributed to MRM signal changes. Even though we studied only one block each from normal appearing and cortical lesions, such studies can help better understand the origins of histopathological and microstructural correlates of MRI signal changes in multiple sclerosis and contextualize the interpretation of lower-resolution in vivo MRI scans.
Collapse
Affiliation(s)
- Govind Nair
- Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, United States.
| | - Stephen Dodd
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Seung-Kwon Ha
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Alan P Koretsky
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, United States
| |
Collapse
|
42
|
Suto DJ, Nair G, Sudarshana DM, Steele SU, Dwyer J, Beck ES, Ohayon J, McFarland H, Koretsky AP, Cortese ICM, Reich DS. Manganese-Enhanced MRI in Patients with Multiple Sclerosis. AJNR Am J Neuroradiol 2020; 41:1569-1576. [PMID: 32763897 DOI: 10.3174/ajnr.a6665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 05/31/2020] [Indexed: 01/16/2023]
Abstract
BACKGROUND AND PURPOSE Cellular uptake of the manganese ion, when administered as a contrast agent for MR imaging, can noninvasively highlight cellular activity and disease processes in both animals and humans. The purpose of this study was to explore the enhancement profile of manganese in patients with multiple sclerosis. MATERIALS AND METHODS Mangafodipir is a manganese chelate that was clinically approved for MR imaging of liver lesions. We present a case series of 6 adults with multiple sclerosis who were scanned at baseline with gadolinium, then injected with mangafodipir, and followed at variable time points thereafter. RESULTS Fourteen new lesions formed during or shortly before the study, of which 10 demonstrated manganese enhancement of varying intensity, timing, and spatial pattern. One gadolinium-enhancing extra-axial mass, presumably a meningioma, also demonstrated enhancement with manganese. Most interesting, manganese enhancement was detected in lesions that formed in the days after mangafodipir injection, and this enhancement persisted for several weeks, consistent with contrast coming from intracellular uptake of manganese. Some lesions demonstrated a diffuse pattern of manganese enhancement in an area larger than that of both gadolinium enhancement and T2-FLAIR signal abnormality. CONCLUSIONS This work demonstrates the first use of a manganese-based contrast agent to enhance MS lesions on MR imaging. Multiple sclerosis lesions were enhanced with a temporal and spatial profile distinct from that of gadolinium. Further experiments are necessary to uncover the mechanism of manganese contrast enhancement as well as cell-specific uptake.
Collapse
Affiliation(s)
- D J Suto
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - G Nair
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - D M Sudarshana
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - S U Steele
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - J Dwyer
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - E S Beck
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - J Ohayon
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - H McFarland
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - A P Koretsky
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - I C M Cortese
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - D S Reich
- From the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.
| |
Collapse
|
43
|
Lee NJ, Ha SK, Sati P, Absinta M, Nair G, Luciano NJ, Leibovitch EC, Yen CC, Rouault TA, Silva AC, Jacobson S, Reich DS. Potential role of iron in repair of inflammatory demyelinating lesions. J Clin Invest 2020; 129:4365-4376. [PMID: 31498148 DOI: 10.1172/jci126809] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 07/16/2019] [Indexed: 12/20/2022] Open
Abstract
Inflammatory destruction of iron-rich myelin is characteristic of multiple sclerosis (MS). Although iron is needed for oligodendrocytes to produce myelin during development, its deposition has also been linked to neurodegeneration and inflammation, including in MS. We report perivascular iron deposition in multiple sclerosis lesions that was mirrored in 72 lesions from 13 marmosets with experimental autoimmune encephalomyelitis. Iron accumulated mainly inside microglia/macrophages from 6 weeks after demyelination. Consistently, expression of transferrin receptor, the brain's main iron-influx protein, increased as lesions aged. Iron was uncorrelated with inflammation and postdated initial demyelination, suggesting that iron is not directly pathogenic. Iron homeostasis was at least partially restored in remyelinated, but not persistently demyelinated, lesions. Taken together, our results suggest that iron accumulation in the weeks after inflammatory demyelination may contribute to lesion repair rather than inflammatory demyelination per se.
Collapse
Affiliation(s)
- Nathanael J Lee
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA.,Department of Neuroscience, Georgetown University Medical Center, Georgetown University, Washington, District of Columbia, USA
| | - Seung-Kwon Ha
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Nicholas J Luciano
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Emily C Leibovitch
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Cecil C Yen
- Cerebral Microcirculation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Tracey A Rouault
- Section on Human Iron Metabolism, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA
| | - Afonso C Silva
- Cerebral Microcirculation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| |
Collapse
|
44
|
Griffin AD, Turtzo LC, Parikh GY, Tolpygo A, Lodato Z, Moses AD, Nair G, Perl DP, Edwards NA, Dardzinski BJ, Armstrong RC, Ray-Chaudhury A, Mitra PP, Latour LL. Traumatic microbleeds suggest vascular injury and predict disability in traumatic brain injury. Brain 2020; 142:3550-3564. [PMID: 31608359 DOI: 10.1093/brain/awz290] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 07/15/2019] [Accepted: 07/28/2019] [Indexed: 12/14/2022] Open
Abstract
Traumatic microbleeds are small foci of hypointensity seen on T2*-weighted MRI in patients following head trauma that have previously been considered a marker of axonal injury. The linear appearance and location of some traumatic microbleeds suggests a vascular origin. The aims of this study were to: (i) identify and characterize traumatic microbleeds in patients with acute traumatic brain injury; (ii) determine whether appearance of traumatic microbleeds predict clinical outcome; and (iii) describe the pathology underlying traumatic microbleeds in an index patient. Patients presenting to the emergency department following acute head trauma who received a head CT were enrolled within 48 h of injury and received a research MRI. Disability was defined using Glasgow Outcome Scale-Extended ≤6 at follow-up. All magnetic resonance images were interpreted prospectively and were used for subsequent analysis of traumatic microbleeds. Lesions on T2* MRI were stratified based on 'linear' streak-like or 'punctate' petechial-appearing traumatic microbleeds. The brain of an enrolled subject imaged acutely was procured following death for evaluation of traumatic microbleeds using MRI targeted pathology methods. Of the 439 patients enrolled over 78 months, 31% (134/439) had evidence of punctate and/or linear traumatic microbleeds on MRI. Severity of injury, mechanism of injury, and CT findings were associated with traumatic microbleeds on MRI. The presence of traumatic microbleeds was an independent predictor of disability (P < 0.05; odds ratio = 2.5). No differences were found between patients with punctate versus linear appearing microbleeds. Post-mortem imaging and histology revealed traumatic microbleed co-localization with iron-laden macrophages, predominately seen in perivascular space. Evidence of axonal injury was not observed in co-localized histopathological sections. Traumatic microbleeds were prevalent in the population studied and predictive of worse outcome. The source of traumatic microbleed signal on MRI appeared to be iron-laden macrophages in the perivascular space tracking a network of injured vessels. While axonal injury in association with traumatic microbleeds cannot be excluded, recognizing traumatic microbleeds as a form of traumatic vascular injury may aid in identifying patients who could benefit from new therapies targeting the injured vasculature and secondary injury to parenchyma.
Collapse
Affiliation(s)
- Allison D Griffin
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Acute Cerebrovasular Diagnostics Unit of the National Institute of Neurologic Disorders and Stroke, Bethesda, Maryland, USA
| | - L Christine Turtzo
- Acute Cerebrovasular Diagnostics Unit of the National Institute of Neurologic Disorders and Stroke, Bethesda, Maryland, USA
| | - Gunjan Y Parikh
- R. Adams Cowley Shock Trauma Center, Program in Trauma, University of Maryland School of Medicine, Baltimore, USA.,Division of Neurocritical Care and Emergency Neurology, Department of Neurology, University of Maryland School of Medicine, Baltimore, USA
| | | | - Zachary Lodato
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Anita D Moses
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Acute Cerebrovasular Diagnostics Unit of the National Institute of Neurologic Disorders and Stroke, Bethesda, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Daniel P Perl
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
| | - Nancy A Edwards
- Surgical Neurology Branch of the National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Bernard J Dardzinski
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
| | - Regina C Armstrong
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
| | - Abhik Ray-Chaudhury
- Surgical Neurology Branch of the National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Partha P Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA
| | - Lawrence L Latour
- Center for Neuroscience and Regenerative Medicine, Bethesda, Maryland, USA.,Acute Cerebrovasular Diagnostics Unit of the National Institute of Neurologic Disorders and Stroke, Bethesda, Maryland, USA
| |
Collapse
|
45
|
Eden D, Gros C, Badji A, Dupont SM, De Leener B, Maranzano J, Zhuoquiong R, Liu Y, Granberg T, Ouellette R, Stawiarz L, Hillert J, Talbott J, Bannier E, Kerbrat A, Edan G, Labauge P, Callot V, Pelletier J, Audoin B, Rasoanandrianina H, Brisset JC, Valsasina P, Rocca MA, Filippi M, Bakshi R, Tauhid S, Prados F, Yiannakas M, Kearney H, Ciccarelli O, Smith SA, Andrada Treaba C, Mainero C, Lefeuvre J, Reich DS, Nair G, Shepherd TM, Charlson E, Tachibana Y, Hori M, Kamiya K, Chougar L, Narayanan S, Cohen-Adad J. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain 2020; 142:633-646. [PMID: 30715195 DOI: 10.1093/brain/awy352] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 10/25/2018] [Accepted: 11/20/2018] [Indexed: 12/12/2022] Open
Abstract
Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.
Collapse
Affiliation(s)
- Dominique Eden
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Atef Badji
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada
| | - Sara M Dupont
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Benjamin De Leener
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.,Department of Anatomy, Université de Québec à Trois-Rivières, Trois-Rivières, QC, Canada
| | - Ren Zhuoquiong
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China
| | - Yaou Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, P. R. China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, P. R. China
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Massachusetts General Hospital, Boston, USA
| | - Leszek Stawiarz
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jan Hillert
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jason Talbott
- Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital, University of California, San Francisco, CA, USA
| | - Elise Bannier
- CHU Rennes, Radiology Department, Rennes, France.,Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France
| | - Anne Kerbrat
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Gilles Edan
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN - ERL U 1228, Rennes, France.,CHU Rennes, Neurology Department, Rennes, France
| | - Pierre Labauge
- MS Unit, Department of Neurology, University Hospital of Montpellier, Montpellier, France
| | - Virginie Callot
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean Pelletier
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Bertrand Audoin
- APHM, CHU Timone, CEMEREM, Marseille, France.,APHM, Department of Neurology, CHU Timone, APHM, Marseille
| | - Henitsoa Rasoanandrianina
- Aix Marseille University, CNRS, CRMBM, Marseille, France.,APHM, CHU Timone, CEMEREM, Marseille, France
| | - Jean-Christophe Brisset
- Observatoire Français de la Sclérose en Plaques (OFSEP) ; Université de Lyon, Université Claude Bernard Lyon 1; Hospices Civils de Lyon; CREATIS-LRMN, UMR 5220 CNRS and U 1044 INSERM; Lyon, France
| | - Paola Valsasina
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Rohit Bakshi
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Shahamat Tauhid
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Ferran Prados
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK.,Center for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marios Yiannakas
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Hugh Kearney
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Olga Ciccarelli
- Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London,UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Jennifer Lefeuvre
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Daniel S Reich
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | - Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Maryland, USA
| | | | - Erik Charlson
- Department of Radiology, NYU Langone Medical Center, New York, USA
| | | | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Lydia Chougar
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.,Hospital Cochin, Paris, France
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.,Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada
| |
Collapse
|
46
|
Dey R, Patnaik S, Nair G, Steiner S, Sivarasu S. An intra-operative device for parallel drilling and femoral landmark estimation during medial patellofemoral ligament reconstructive surgery. SA orthop j 2020. [DOI: 10.17159/2309-8309/2020/v19n4a3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
ABSTRACT BACKGROUND: The aim of this study was to design and test a device to guide medial patellofemoral reconstruction surgeries. Materials and methods: A three-dimensional (3D) printed, modular and cost-effective medial patellofemoral ligament (MPFL) reconstruction guide, Pat-Rig, was designed with parallel holes running in the medio-lateral direction. This device was manufactured using a commercial additive manufacturing facility, and bench tested using a custom-built test rig. CT scans of patella bones were reconstructed, and the device was tested on four 3D-printed patellas of various sizes. RESULTS: The device was successful in guiding the surgical drill into the patella to drill parallel holes adhering to the current surgical requirements and specifications. The device was augmented with an innovative radiopaque scale which can allow the surgeon to accurately predict the landmarks to drill and measure the drill depth of the tunnels. CONCLUSION: There are no devices on the market that accurately predict the drill locations on the patella during MPFL reconstruction surgeries. The device, Pat-Rig, was found to overcome the current limitations of the MPFL surgeries and was able to provide satisfactory surgical guidance during the reconstruction. Level of evidence: Level 5 Keywords: knee surgery, patella, orthopaedic, MPFL reconstruction, 3D-printed, novel surgical device.
Collapse
|
47
|
Reoma LB, Trindade CJ, Monaco MC, Solis J, Montojo MG, Vu P, Johnson K, Beck E, Nair G, Khan OI, Quezado M, Hewitt SM, Reich DS, Childs R, Nath A. Fatal encephalopathy with wild-type JC virus and ruxolitinib therapy. Ann Neurol 2019; 86:878-884. [PMID: 31600832 DOI: 10.1002/ana.25608] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 09/16/2019] [Accepted: 09/16/2019] [Indexed: 12/12/2022]
Abstract
OBJECTIVE JC virus (JCV) infection is a lytic infection of oligodendrocytes in progressive multifocal leukoencephalopathy; less common forms of central nervous system manifestations associated with JCV infection include granule cell neuronopathy, encephalopathy, and meningitis. Presented is the first case of fatal JCV encephalopathy after immunosuppressive therapy that included ruxolitinib. METHODS Postmortem analysis included next generation sequencing, Sanger sequencing, tissue immunohistochemistry, and formalin-fixed hemisphere 7T magnetic resonance imaging. RESULTS JCV DNA isolated from postmortem tissue samples identified a novel 12bp insertion that altered the transcription site binding pattern in an otherwise "wild-type virus," which has long been thought to be the nonpathogenic form of JCV. Anti-VP1 staining demonstrated infection in cortical neurons, hippocampal neurons, and glial and endothelial cells. INTERPRETATION This expands the spectrum of identified JCV diseases associated with broad-spectrum immunosuppression, including JAK-STAT inhibitors, and sheds light on an additional neurotropic virus strain of the archetype variety. ANN NEUROL 2019;86:878-884.
Collapse
Affiliation(s)
- Lauren Bowen Reoma
- Sections of Infections of the Nervous System, NIH National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD
| | | | | | - Jamie Solis
- Sections of Infections of the Nervous System, NIH National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD
| | - Marta Garcia Montojo
- Sections of Infections of the Nervous System, NIH National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD
| | - Phuong Vu
- Medical Oncology Service, NCI, Bethesda, MD
| | | | - Erin Beck
- Translational Neuroradiology Unit, NINDS, Bethesda, MD
| | - Govind Nair
- Translational Neuroradiology Unit, NINDS, Bethesda, MD
| | - Omar I Khan
- Neurology Consult Service, NINDS, Bethesda, MD
| | - Marta Quezado
- Surgical Pathology, Lab of Pathology, NCI, Bethesda, MD
| | - Stephen M Hewitt
- Experimental Pathology Laboratory, Lab of Pathology, NIH National Cancer Institute (NCI), Bethesda, MD
| | | | | | - Avindra Nath
- Sections of Infections of the Nervous System, NIH National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD
| |
Collapse
|
48
|
Hassan A, Birnie D, Nery P, Nair G, Davis D, Green M, Sadek M, Golian M, Redpath C. P2853Contemporary reporting of acute complications from implantable cardioverter defibrillator surgery. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz748.1162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Defibrillator placement carries an inherent risk to the patient. Traditionally, major adverse events defined as cardiac arrest, tamponnade, pneumothorax, infection requiring re-operation, MI and CVA within 30 days are reported to occur between 3 and 4%. Minor complications such as heamatomae or lead dislodgement are reported between 8 and 13%. Novel lead technologies, protocolised programming and reduced use of Heparin bridging have been reported to reduce adverse outcomes. However, patients are still typically monitored in hospital for 24 hours to mitigate these risks. There is little evidence that discharge delay is effective yet incurs significant additional costs.
Purpose
We sought to evaluate the frequency and timing of adverse events relating to defibrillator surgery (ICD and CRT-D) at a large Canadian tertiary care center (UOHI).
Methods
We retrospectively reviewed all patients who received a defibrillator placed from 1st April 2013 to 31st March 2018 inclusive. Patient comorbidities were extracted from the hospital electronic medical record (EMR) system. Device related information and complications were extracted from UOHI PaceartTM system and EMR and cross referenced with physician remuneration databases.
Results
A total of 2221 procedures were performed on 2153 patients (78% male, mean age 65 years). The majority (60%) of defibrillator implants were de novo, with 884 (40%) pulse generator replacements/ upgrades and 868 (39%) defibrillators had CRT capability. Patients were routinely discharged within 24 hours of ICD surgery. Post-operative follow up ≥30 days was complete in 97% patients. Major adverse events occurred within 30 days in 9 patients (0.4%); 9 (100%) were infection requiring re-operation. An additional 32 patients (1.5%) required repeat interventions or readmission within 30 days of implant, most commonly due to lead dislodgement. Only 2 patients required readmission within 24 hours of surgery (0.1%). All procedure-related adverse events during clinical follow up (≤5 years) were 131 (5.9%) occurring in 122 patients. There were no apparent predictors of adverse events in this cohort.
Conclusion(s)
Contemporary risks to patients undergoing defibrillator surgery are considerably lower than that reported in 2010. The risk of infection appears constant despite increased antibiosis. Patients receiving an ICD or CRT-D can safely be discharged within 24 hours if no complications are apparent.
Acknowledgement/Funding
None
Collapse
Affiliation(s)
- A Hassan
- University of Ottawa Heart Institute, Ottawa, Canada
| | - D Birnie
- University of Ottawa Heart Institute, Ottawa, Canada
| | - P Nery
- University of Ottawa Heart Institute, Ottawa, Canada
| | - G Nair
- University of Ottawa Heart Institute, Ottawa, Canada
| | - D Davis
- University of Ottawa Heart Institute, Ottawa, Canada
| | - M Green
- University of Ottawa Heart Institute, Ottawa, Canada
| | - M Sadek
- University of Ottawa Heart Institute, Ottawa, Canada
| | - M Golian
- University of Ottawa Heart Institute, Ottawa, Canada
| | - C Redpath
- University of Ottawa Heart Institute, Ottawa, Canada
| |
Collapse
|
49
|
Kaoutskaia A, Shurrab M, Amit G, Parkash R, Exner D, Toal S, Sterns L, Sarrazin JF, Glover B, Chauhan V, Sultan O, Nair G, Deyell MW, Macle L, Crystal E. P1872Canadian electrophysiology labs registry report update 2011–2018. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz748.0622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Interventional cardiac electrophysiology (EP) is rapidly evolving; a nationwide registry was established and re-administered since 2011 to conduct a periodic review of resource allocation across Canada.
Methods
The registry collects annual data on EP lab infrastructure, imaging, tools, human resources, procedural volumes, and wait times. Leading physicians from each EP lab were contacted electronically.
Results
All Canadian EP centres were identified (n=30); 50% and 45% of active centres participated in the last 2 instalments of the registry. Since 2011, data has been consistently obtained from 11 university-affiliated centres. Table 1 reports trends in procedural volumes and operators. Figure 1 depicts the ablations done per operator. The mean wait time to see an electrophysiologist for an initial non-urgent consult is 23 weeks. The wait time between an EP consult and ablation date is 17.8 weeks for simple ablation, 15.9 weeks for VT ablation, and 30.1 weeks for AF ablation. On average centres have 2 (range: 1–4) rooms equipped for ablations; each centre uses the EP lab an average of 7 shifts per week. While diagnostic studies and radiofrequency ablations are performed in all centres, point-by-point cryoablation is available in 85% and cryoballoon in 77% of the centres; 38% of the respondents use circular ablation techniques.
Trends in procedural volumes + operators 2015–2016 2013–2014 2011–2012 Procedures per operator 117±70 120±68 113±42 Procedures per centre 498±299 477±245 446±237 Ratio of staff to trainees 2.0:1 1.6:1 1.5:1 Full time physicians per centre 4.1 (0–7) 4.1 (1–7) 3.5 (0–7) Nurses trained specifically for EP 4.6 (0–10) 4.4 (0–10) n/a Ablation procedures volume: AV Reciprocal Tachycardia 12% 10% 11% AV Nodal Re-entry Tachycardia 18% 19% 23% Atrial Fibrillation/Atypical Flutter 33% 35% 30% Typical Flutter 20% 14% 19% Ventricular Tachycardia 8% 8% 10% Total annual ablations in all respondent centres 5478 5243 4908 Mean ± standard deviation. Staff (full-time + part-time prorated to 0.5).
Annual ablation volumes per operator
Conclusion
This initiative provides contemporary data on invasive EP practices. The results show feasibility in data collection which will serve as a reference for decisions regarding resource planning.
Collapse
Affiliation(s)
- A Kaoutskaia
- Sunnybrook Health Sciences Centre, Toronto, Canada
| | - M Shurrab
- Health Sciences North, Sudbury, Canada
| | - G Amit
- McMaster University, Hamilton, Canada
| | - R Parkash
- Dalhousie University, Halifax, Canada
| | - D Exner
- University of Calgary, Calgary, Canada
| | - S Toal
- Saint John Regional Hospital, Saint John, Canada
| | - L Sterns
- Royal Jubilee Hospital, Victoria, Canada
| | | | - B Glover
- Sunnybrook Health Sciences Centre, Toronto, Canada
| | - V Chauhan
- Toronto General Hospital, Toronto, Canada
| | - O Sultan
- Regina General Hospital, Regina, Canada
| | - G Nair
- University of Ottawa Heart Institute, Ottawa, Canada
| | - M W Deyell
- University of British Columbia, Vancouver, Canada
| | - L Macle
- Montreal Heart Institute, Montreal, Canada
| | - E Crystal
- Sunnybrook Health Sciences Centre, Toronto, Canada
| |
Collapse
|
50
|
Alqarawi W, Thornhill R, Nair G, Redpath C, Golian M, Sadek M, m Abderrazek, DeKemp R, Birnie D, Nery P. MAGNETIC RESONANCE IMAGING FOR THE DETECTION OF LEFT ATRIAL SCAR: CORRELATION WITH HIGH-DENSITY VOLTAGE MAPPING. Can J Cardiol 2019. [DOI: 10.1016/j.cjca.2019.07.083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
|