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Gaubert M, Combès B, Bannier E, Masson A, Caron V, Baudron G, Ferré JC, Michel L, Le Page E, Stankoff B, Edan G, Bodini B, Kerbrat A. Microstructural Damage and Repair in the Spinal Cord of Patients With Early Multiple Sclerosis and Association With Disability at 5 Years. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2025; 12:e200333. [PMID: 39571137 PMCID: PMC11587990 DOI: 10.1212/nxi.0000000000200333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 10/01/2024] [Indexed: 11/27/2024]
Abstract
BACKGROUND AND OBJECTIVES The dynamics of microstructural spinal cord (SC) damage and repair in people with multiple sclerosis (pwMS) and their clinical relevance have yet to be explored. We set out to describe patient-specific profiles of microstructural SC damage and change during the first year after MS diagnosis and to investigate their associations with disability and SC atrophy at 5 years. METHODS We performed a longitudinal monocentric cohort study among patients with relapsing-remitting MS: first relapse <1 year, no relapse <1 month, and high initial severity on MRI (>9 T2 lesions on brain MRI and/or initial myelitis). pwMS and age-matched healthy controls (HCs) underwent cervical SC magnetization transfer (MT) imaging at baseline and at 1 year for pwMS. Based on HC data, SC MT ratio z-score maps were computed for each person with MS. An index of microstructural damage was calculated as the proportion of voxels classified as normal at baseline and identified as damaged after 1 year. Similarly, an index of repair was also calculated (voxels classified as damaged at baseline and as normal after 1 year). Linear models including these indices and disability or SC cross-sectional area (CSA) change between baseline and 5 years were implemented. RESULTS Thirty-seven patients and 19 HCs were included. We observed considerable variability in the extent of microstructural SC damage at baseline (0%-58% of SC voxels). We also observed considerable variability in damage and repair indices over 1 year (0%-31% and 0%-20%), with 18 patients showing predominance of damage and 18 predominance of repair. The index of microstructural damage was associated positively with the Expanded Disability Status Scale score (r = 0.504, p = 0.002) and negatively with CSA change (r = -0.416, p = 0.02) at 5 years, independent of baseline SC lesion volume. DISCUSSION People with early relapsing-remitting MS exhibited heterogeneous profiles of microstructural SC damage and repair. Progression of microstructural damage was associated with disability progression and SC atrophy 5 years later. These results indicate a potential for microstructural repair in the SC to prevent disability progression in pwMS.
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Affiliation(s)
- Malo Gaubert
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Benoit Combès
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Elise Bannier
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Arthur Masson
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Vivien Caron
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Gaëlle Baudron
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Jean-Christophe Ferré
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Laure Michel
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Emmanuelle Le Page
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Bruno Stankoff
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Gilles Edan
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Benedetta Bodini
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
| | - Anne Kerbrat
- From the Department of Neuroradiology (M.G., E.B., J.-C.F.), Rennes University Hospital; Empenn (M.G., B.C., E.B., A.M., V.C., G.B., J.-C.F., A.K.), INRIA, Rennes University-CNRS-INSERM; Department of Neurology (L.M., E.L.P., G.E., A.K.), Rennes University Hospital; Paris Brain Institute (ICM) (B.S., B.B.), Sorbonne University-CNRS-INSERM; and Neurology Department (B.S., B.B.), APHP St Antoine Hospital, Paris, France
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de Lucena LZ, Campanholo KR, Pereira SLA, Tavora DGF, Callegaro D, Buchpiguel CA, Pitombeira MS, de Paula Faria D. Evaluation of myelin content in the spinal cord of patients with multiple sclerosis: A positron emission tomography study. Mult Scler Relat Disord 2024; 93:106248. [PMID: 39731904 DOI: 10.1016/j.msard.2024.106248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 12/09/2024] [Accepted: 12/20/2024] [Indexed: 12/30/2024]
Abstract
BACKGROUND Multiple sclerosis (MS) is divided into Relapsing-Remitting (RRMS) and Progressive (PMS) phenotypes, both associated with spinal cord (SC) damage. MS-related disability and SC atrophy are not yet fully understood and can differ across phenotypes. A combined approach using Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) could provide a broader understanding of myelin changes in the cervical SC (CSC) in different MS phenotypes and the associations with disability. OBJECTIVES To evaluate CSC myelin content using a PET-MRI with [11C]PIB and its association with disability in PMS and RRMS compared to healthy volunteers (HV). METHODS [11C]PIB PET images and T1-MRI of 49 patients with MS and 19 HV were evaluated at C1-C2, C3, and C4 vertebrae levels. [11C]PIB uptake and volume were compared between groups. RESULTS [11C]PIB uptake was significantly lower at C1-C4, C1-C2, and C3 segments when comparing PMS to RRMS and HV. [11C]PIB uptake inversely correlated with overall disability in all CSC segments in all patients with MS, and in the RRMS phenotype separately. CONCLUSIONS Our findings suggest an association between [11C]PIB CSC uptake and overall disability score measured by EDSS. MRI and PET can be used as complementary methods for studying MS.
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Affiliation(s)
- Letícia Zorante de Lucena
- Laboratory of Nuclear Medicine (LIM43), Department of Radiology and Oncology, Faculdade de Medicina-FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil.
| | - Kenia Repiso Campanholo
- Laboratory of Nuclear Medicine (LIM43), Department of Radiology and Oncology, Faculdade de Medicina-FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil.
| | | | | | - Dagoberto Callegaro
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil.
| | - Carlos Alberto Buchpiguel
- Laboratory of Nuclear Medicine (LIM43), Department of Radiology and Oncology, Faculdade de Medicina-FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil.
| | - Milena Sales Pitombeira
- Laboratory of Nuclear Medicine (LIM43), Department of Radiology and Oncology, Faculdade de Medicina-FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil; Neurology Department, Hospital Geral de Fortaleza, Fortaleza 60150-160, CE, Brazil.
| | - Daniele de Paula Faria
- Laboratory of Nuclear Medicine (LIM43), Department of Radiology and Oncology, Faculdade de Medicina-FMUSP, Universidade de São Paulo, São Paulo 05403-911, SP, Brazil.
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Mayfield JD, Murtagh R, Ciotti J, Robertson D, Naqa IE. Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:3231-3249. [PMID: 38871944 PMCID: PMC11612123 DOI: 10.1007/s10278-024-01031-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/05/2024] [Accepted: 01/23/2024] [Indexed: 06/15/2024]
Abstract
The majority of deep learning models in medical image analysis concentrate on single snapshot timepoint circumstances, such as the identification of current pathology on a given image or volume. This is often in contrast to the diagnostic methodology in radiology where presumed pathologic findings are correlated to prior studies and subsequent changes over time. For multiple sclerosis (MS), the current body of literature describes various forms of lesion segmentation with few studies analyzing disability progression over time. For the purpose of longitudinal time-dependent analysis, we propose a combinatorial analysis of a video vision transformer (ViViT) benchmarked against traditional recurrent neural network of Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architectures and a hybrid Vision Transformer-LSTM (ViT-LSTM) to predict long-term disability based upon the Extended Disability Severity Score (EDSS). The patient cohort was procured from a two-site institution with 703 patients' multisequence, contrast-enhanced MRIs of the cervical spine between the years 2002 and 2023. Following a competitive performance analysis, a VGG-16-based CNN-LSTM was compared to ViViT with an ablation analysis to determine time-dependency of the models. The VGG16-LSTM predicted trinary classification of EDSS score in 6 years with 0.74 AUC versus the ViViT with 0.84 AUC (p-value < 0.001 per 5 × 2 cross-validation F-test) on an 80:20 hold-out testing split. However, the VGG16-LSTM outperformed ViViT when patients with only 2 years of MRIs (n = 94) (0.75 AUC versus 0.72 AUC, respectively). Exact EDSS classification was investigated for both models using both classification and regression strategies but showed collectively worse performance. Our experimental results demonstrate the ability of time-dependent deep learning models to predict disability in MS using trinary stratification of disability, mimicking clinical practice. Further work includes external validation and subsequent observational clinical trials.
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Affiliation(s)
- John D Mayfield
- USF Health Department of Radiology, 2 Tampa General Circle, STC 6103, Tampa, FL, 33612, USA.
| | - Ryan Murtagh
- USF Health Department of Radiology, 2 Tampa General Circle, STC 6103, Tampa, FL, 33612, USA
| | - John Ciotti
- Department of Neurology, University of South Florida, Morsani College of Medicine, USF Multiple Sclerosis Center, 13330 USF Laurel Drive, Tampa, FL, 33612, USA
| | - Derrick Robertson
- Department of Neurology, James A. Haley VA Medical Center, 13000 Bruce B Downs Blvd, Tampa, FL, 33612, USA
| | - Issam El Naqa
- University of South Florida, College of Engineering, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA
- H. Lee Moffitt Cancer Center Department of Machine Learning, Tampa, FL, 33612, USA
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4
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Keegan BM, Absinta M, Cohen-Adad J, Flanagan EP, Henry RG, Klawiter EC, Kolind S, Krieger S, Laule C, Lincoln JA, Messina S, Oh J, Papinutto N, Smith SA, Traboulsee A. Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future. Brain Commun 2024; 6:fcae395. [PMID: 39611182 PMCID: PMC11604059 DOI: 10.1093/braincomms/fcae395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 09/30/2024] [Accepted: 11/05/2024] [Indexed: 11/30/2024] Open
Abstract
Spinal cord disease is important in most people with multiple sclerosis, but assessment remains less emphasized in patient care, basic and clinical research and therapeutic trials. The North American Imaging in Multiple Sclerosis Spinal Cord Interest Group was formed to determine and present the contemporary landscape of multiple sclerosis spinal cord evaluation, further existing and advanced spinal cord imaging techniques, and foster collaborative work. Important themes arose: (i) multiple sclerosis spinal cord lesions (differential diagnosis, association with clinical course); (ii) spinal cord radiological-pathological associations; (iii) 'critical' spinal cord lesions; (iv) multiple sclerosis topographical model; (v) spinal cord atrophy; and (vi) automated and special imaging techniques. Distinguishing multiple sclerosis from other myelopathic aetiology is increasingly refined by imaging and serological studies. Post-mortem spinal cord findings and MRI pathological correlative studies demonstrate MRI's high sensitivity in detecting microstructural demyelination and axonal loss. Spinal leptomeninges include immune inflammatory infiltrates, some in B-cell lymphoid-like structures. 'Critical' demyelinating lesions along spinal cord corticospinal tracts are anatomically consistent with and may be disproportionately associated with motor progression. Multiple sclerosis topographical model implicates the spinal cord as an area where threshold impairment associates with multiple sclerosis disability. Progressive spinal cord atrophy and 'silent' multiple sclerosis progression may be emerging as an important multiple sclerosis prognostic biomarker. Manual atrophy assessment is complicated by rater bias, while automation (e.g. Spinal Cord Toolbox), and artificial intelligence may reduce this. Collaborative research by the North American Imaging in Multiple Sclerosis and similar groups with experts combining distinct strengths is key to advancing assessment and treatment of people with multiple sclerosis spinal cord disease.
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Affiliation(s)
- B Mark Keegan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Julien Cohen-Adad
- Institute of Biomedical Imaging, Polytechnique Montreal, Montreal, Canada H3T 1J4
| | - Eoin P Flanagan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Roland G Henry
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Eric C Klawiter
- Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Shannon Kolind
- Division of Neurology, University of British Columbia, Vancouver, Canada V6T 2B5
| | - Stephen Krieger
- Department of Neurology, Mount Sinai, New York City, NY 10029, USA
| | - Cornelia Laule
- Division of Neurology, University of British Columbia, Vancouver, Canada V6T 2B5
| | - John A Lincoln
- McGovern Medical School, UTHealth, Houston, TX 77030, USA
| | - Steven Messina
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Jiwon Oh
- Division of Neurology, University of Toronto, Toronto, Canada M5B 1W8
| | - Nico Papinutto
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Seth Aaron Smith
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Anthony Traboulsee
- Division of Neurology, University of British Columbia, Vancouver, Canada V6T 2B5
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Johnson P, Vavasour IM, Stojkova BJ, Abel S, Lee LE, Laule C, Tam R, Li DKB, Ackermans N, Schabas AJ, Chan J, Cross H, Sayao AL, Devonshire V, Carruthers R, Traboulsee A, Kolind SH. Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis. J Neuroimaging 2023; 33:227-234. [PMID: 36443960 DOI: 10.1111/jon.13069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND PURPOSE Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability. METHODS Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed. RESULTS NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC. CONCLUSIONS Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.
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Affiliation(s)
- Poljanka Johnson
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Shawna Abel
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nathalie Ackermans
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Alice J Schabas
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Jillian Chan
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Helen Cross
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Ana-Luiza Sayao
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Virginia Devonshire
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Carruthers
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
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Combes AJE, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States.
| | - Margareta A Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States; Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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Update on myelin imaging in neurological syndromes. Curr Opin Neurol 2022; 35:467-474. [PMID: 35788545 DOI: 10.1097/wco.0000000000001078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Myelin water imaging (MWI) is generally regarded as the most rigorous approach for noninvasive, in-vivo measurement of myelin content, which has been histopathologically validated. As such, it has been increasingly applied to neurological diseases with white matter involvement, especially those affecting myelin. This review provides an overview of the most recent research applying MWI in neurological syndromes. RECENT FINDINGS Myelin water imaging has been applied in neurological syndromes including multiple sclerosis, Alzheimer's disease, Huntington's disease, traumatic brain injury, Parkinson's disease, cerebral small vessel disease, leukodystrophies and HIV. These syndromes generally showed alterations observable with MWI, with decreased myelin content tending to correlate with lower cognitive scores and worse clinical presentation. MWI has also been correlated with genetic variation in the APOE and PLP1 genes, demonstrating genetic factors related to myelin health. SUMMARY MWI can detect and quantify changes not observable with conventional imaging, thereby providing insight into the pathophysiology and disease mechanisms of a diverse range of neurological syndromes.
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Upper cervical cord atrophy is independent of cervical cord lesion volume in early multiple sclerosis: A two-year longitudinal study. Mult Scler Relat Disord 2022; 60:103713. [PMID: 35272146 DOI: 10.1016/j.msard.2022.103713] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/10/2022] [Accepted: 02/24/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Upper cervical cord atrophy and lesions have been shown to be associated with disease and disability progression already in early relapsing-remitting multiple sclerosis (RRMS). However, their longitudinal relationship remains unclear. OBJECTIVE To investigate the cross-sectional and longitudinal relation between focal T2 cervical cord lesion volume (CCLV) and regional and global mean upper cervical cord area (UCCA), and their relations with disability. METHODS Over a two-year interval, subjects with RRMS (n = 36) and healthy controls (HC, n = 16) underwent annual clinical and MRI examinations. UCCA and CCLV were obtained from C1 through C4 level. Linear mixed model analysis was performed to investigate the relation between UCCA, CCLV, and disability over time. RESULTS UCCA at baseline was significantly lower in RRMS subjects compared to HCs (p = 0.003), but did not decrease faster over time (p ≥ 0.144). UCCA and CCLV were independent of each other at any of the time points or cervical levels, and over time. Lower baseline UCCA, but not CCLV, was related to worsening of both upper and lower extremities function over time. CONCLUSION UCCA and CCLV are independent from each other, both cross-sectionally and longitudinally, in early MS. Lower UCCA, but not CCLV, was related to increasing disability over time.
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