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Sanabria-Diaz G, Cagol A, Lu PJ, Barakovic M, Ocampo-Pineda M, Chen X, Weigel M, Ruberte E, Siebenborn NDOS, Galbusera R, Schädelin S, Benkert P, Kuhle J, Kappos L, Melie-Garcia L, Granziera C. Advanced MRI Measures of Myelin and Axon Volume Identify Repair in Multiple Sclerosis. Ann Neurol 2024. [PMID: 39390658 DOI: 10.1002/ana.27102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 08/10/2024] [Accepted: 09/04/2024] [Indexed: 10/12/2024]
Abstract
OBJECTIVE Pathological studies suggest that multiple sclerosis (MS) lesions endure multiple waves of damage and repair; however, the dynamics and characteristics of these processes are poorly understood in patients living with MS. METHODS We studied 128 MS patients (75 relapsing-remitting, 53 progressive) and 72 healthy controls who underwent advanced magnetic resonance imaging and clinical examination at baseline and 2 years later. Magnetization transfer saturation and multi-shell diffusion imaging were used to quantify longitudinal changes in myelin and axon volumes within MS lesions. Lesions were grouped into 4 classes (repair, damage, mixed repair damage, and stable). The frequency of each class was correlated to clinical measures, demographic characteristics, and levels of serum neurofilament light chain (sNfL). RESULTS Stable lesions were the most frequent (n = 2,276; 44%), followed by lesions with patterns of "repair" (n = 1,352; 26.2%) and damage (n = 1,214; 23.5%). The frequency of "repair" lesion was negatively associated with disability (β = -0.04; p < 0.001) and sNfL (β = -0.16; p < 0.001) at follow-up. The frequency of the "damage" class was higher in progressive than relapsing-remitting patients (p < 0.05) and was related to disability (baseline: β = -0.078; follow-up: β = -0.076; p < 0.001) and age (baseline: β = -0.078; p < 0.001). Stable lesions were more frequent in relapsing-remitting than in progressive patients (p < 0.05), and in younger patients versus older (β = -0.07; p < 0.001) at baseline. Further, "mixed" lesions were most frequent in older patients (β = 0.004; p < 0.001) at baseline. INTERPRETATION These findings show that repair and damage processes within MS lesions occur across the entire disease spectrum and that their frequency correlates with patients disability, age, disease duration, and extent of neuroaxonal damage. ANN NEUROL 2024.
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Affiliation(s)
- Gretel Sanabria-Diaz
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Cagol
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Health Sciences, University of Genova, Genoa, Italy
| | - Po-Jui Lu
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Mario Ocampo-Pineda
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Xinjie Chen
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Esther Ruberte
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC), Basel, Switzerland
| | - Nina de Oliveira S Siebenborn
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC), Basel, Switzerland
| | - Riccardo Galbusera
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schädelin
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Pascal Benkert
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Multiple Sclerosis Centre, Department of Neurology, Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Department of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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Müller J, Lu PJ, Cagol A, Ruberte E, Shin HG, Ocampo-Pineda M, Chen X, Tsagkas C, Barakovic M, Galbusera R, Weigel M, Schaedelin SA, Wang Y, Nguyen TD, Spincemaille P, Kappos L, Kuhle J, Lee J, Granziera C. Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions. Neurology 2024; 103:e209604. [PMID: 39213476 PMCID: PMC11362958 DOI: 10.1212/wnl.0000000000209604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 05/20/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals. METHODS This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models. RESULTS Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = -5.111 × 10-5), lower disability (p = 0.04, b = -2.352 × 10-5), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = -6.686 × 10-4). DISCUSSION χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.
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Affiliation(s)
- Jannis Müller
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Po-Jui Lu
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Alessandro Cagol
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Esther Ruberte
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Hyeong-Geol Shin
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Mario Ocampo-Pineda
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Xinjie Chen
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Charidimos Tsagkas
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Muhamed Barakovic
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Riccardo Galbusera
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Matthias Weigel
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Sabine A Schaedelin
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Yi Wang
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Thanh D Nguyen
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Pascal Spincemaille
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Ludwig Kappos
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Jens Kuhle
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Jongho Lee
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
| | - Cristina Granziera
- From the Translational Imaging in Neurology (ThINk) Basel (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., S.A.S., L.K., C.G.), Department of Biomedical Engineering, Faculty of Medicine, and Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) (J.M., P.-J.L., A.C., E.R., M.O.-P., X.C., C.T., M.B., R.G., M.W., L.K., J.K., C.G.), University Hospital Basel and University of Basel, Switzerland; Department of Health Sciences (A.C.), University of Genova, Italy; Laboratory for Imaging Science and Technology (H.-G.S., J.L.), Department of Electrical and Computer Engineering, Seoul National University, South Korea; Division of Radiological Physics (M.W.), Department of Radiology, University Hospital Basel; Department of Clinical Research (S.A.S.), Clinical Trial Unit, University Hospital Basel, Switzerland; and Department of Radiology (Y.W., T.D.N., P.S.), Weill Medical College of Cornell University, New York, NY
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Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024; 168:2243-2263. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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4
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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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5
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Zuroff LR, Green AJ. The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair. J Neuroophthalmol 2024; 44:143-156. [PMID: 38654413 DOI: 10.1097/wno.0000000000002149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration. METHODS A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted. RESULTS There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials. CONCLUSIONS We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures.
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Affiliation(s)
- Leah R Zuroff
- Department of Neurology (LZ), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Neurology (AJG), University of California San Francisco, San Francisco, California
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6
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Rovira À, Doniselli FM, Auger C, Haider L, Hodel J, Severino M, Wattjes MP, van der Molen AJ, Jasperse B, Mallio CA, Yousry T, Quattrocchi CC. Use of gadolinium-based contrast agents in multiple sclerosis: a review by the ESMRMB-GREC and ESNR Multiple Sclerosis Working Group. Eur Radiol 2024; 34:1726-1735. [PMID: 37658891 DOI: 10.1007/s00330-023-10151-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/06/2023] [Accepted: 07/12/2023] [Indexed: 09/05/2023]
Abstract
Magnetic resonance imaging (MRI) is the most sensitive technique for detecting inflammatory demyelinating lesions in multiple sclerosis (MS) and plays a crucial role in diagnosis and monitoring treatment effectiveness, and for predicting the disease course. In clinical practice, detection of MS lesions is mainly based on T2-weighted and contrast-enhanced T1-weighted sequences. Contrast-enhancing lesions (CEL) on T1-weighted sequences are related to (sub)acute inflammation, while new or enlarging T2 lesions reflect the permanent footprint from a previous acute inflammatory demyelinating event. These two types of MRI features provide redundant information, at least in regular monitoring of the disease. Due to the concern of gadolinium deposition after repetitive injections of gadolinium-based contrast agents (GBCAs), scientific organizations and regulatory agencies in Europe and North America have proposed that these contrast agents should be administered only if clinically necessary. In this article, we provide data on the mode of action of GBCAs in MS, the indications of the use of these agents in clinical practice, their value in MS for diagnostic, prognostic, and monitoring purposes, and their use in specific populations (children, pregnant women, and breast-feeders). We discuss imaging strategies that achieve the highest sensitivity for detecting CELs in compliance with the safety regulations established by different regulatory agencies. Finally, we will briefly discuss some alternatives to the use of GBCA for detecting blood-brain barrier disruption in MS lesions. CLINICAL RELEVANCE STATEMENT: Although use of GBCA at diagnostic workup of suspected MS is highly valuable for diagnostic and prognostic purposes, their use in routine monitoring is not mandatory and must be reduced, as detection of disease activity can be based on the identification of new or enlarging lesions on T2-weighted images. KEY POINTS: • Both the EMA and the FDA state that the use of GBCA in medicine should be restricted to clinical scenarios in which the additional information offered by the contrast agent is required. • The use of GBCA is generally recommended in the diagnostic workup in subjects with suspected MS and is generally not necessary for routine monitoring in clinical practice. • Alternative MRI-based approaches for detecting acute focal inflammatory MS lesions are not yet ready to be used in clinical practice.
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Affiliation(s)
- Àlex Rovira
- Section of Neuroradiology, Department of Radiology, University Hospital Vall d'Hebron, Autonomous University of Barcelona, Barcelona, Spain.
| | - Fabio M Doniselli
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Cristina Auger
- Section of Neuroradiology, Department of Radiology, University Hospital Vall d'Hebron, Autonomous University of Barcelona, Barcelona, Spain
| | - Lukas Haider
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jerome Hodel
- Department of Radiology, Groupe Hospitalier Paris-Saint Joseph, Paris, France
| | | | - Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | | | - Bas Jasperse
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Carlo A Mallio
- Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Rome, Italy
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK
| | - Carlo C Quattrocchi
- Centre for Medical Sciences CISMed, University of Trento, Trento, Italy
- Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, Trento, Italy
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Gloor M, Andelova M, Gaetano L, Papadopoulou A, Burguet Villena F, Sprenger T, Radue EW, Kappos L, Bieri O, Garcia M. Longitudinal analysis of new multiple sclerosis lesions with magnetization transfer and diffusion tensor imaging. Eur Radiol 2024; 34:1680-1691. [PMID: 37658894 PMCID: PMC10873225 DOI: 10.1007/s00330-023-10173-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/02/2023] [Accepted: 07/12/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVE The potential of magnetization transfer imaging (MTI) and diffusion tensor imaging (DTI) for the detection and evolution of new multiple sclerosis (MS) lesions was analyzed. METHODS Nineteen patients with MS obtained conventional MRI, MTI, and DTI examinations bimonthly for 12 months and again after 24 months at 1.5 T MRI. MTI was acquired with balanced steady-state free precession (bSSFP) in 10 min (1.3 mm3 isotropic resolution) yielding both magnetization transfer ratio (MTR) and quantitative magnetization transfer (qMT) parameters (pool size ratio (F), exchange rate (kf), and relaxation times (T1/T2)). DTI provided fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). RESULTS At the time of their appearance on MRI, the 21 newly detected MS lesions showed significantly reduced MTR/F/kf and prolonged T1/T2 parameters, as well as significantly reduced FA and increased AD/MD/RD. Significant differences were already observed for MTR 4 months and for qMT parameters 2 months prior to lesions' detection on MRI. DTI did not show any significant pre-lesional differences. Slightly reversed trends were observed for most lesions up to 8 months after their detection for qMT and less pronounced for MTR and three diffusion parameters, while appearing unchanged on MRI. CONCLUSIONS MTI provides more information than DTI in MS lesions and detects tissue changes 2 to 4 months prior to their appearance on MRI. After lesions' detection, qMT parameter changes promise to be more sensitive than MTR for the lesions' evolutional assessment. Overall, bSSFP-based MTI adumbrates to be more sensitive than MRI and DTI for the early detection and follow-up assessment of MS lesions. CLINICAL RELEVANCE STATEMENT When additionally acquired in routine MRI, fast bSSFP-based MTI can complement the MRI/DTI longitudinal lesion assessment by detecting MS lesions 2-4 months earlier than with MRI, which could implicate earlier clinical decisions and better follow-up/treatment assessment in MS patients. KEY POINTS • Magnetization transfer imaging provides more information than DTI in multiple sclerosis lesions and can detect tissue changes 2 to 4 months prior to their appearance on MRI. • After lesions' detection, quantitative magnetization transfer changes are more pronounced than magnetization transfer ratio changes and therefore promise to be more sensitive for the lesions' evolutional assessment. • Balanced steady-state free precession-based magnetization transfer imaging is more sensitive than MRI and DTI for the early detection and follow-up assessment of multiple sclerosis lesions.
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Affiliation(s)
- Monika Gloor
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Michaela Andelova
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Laura Gaetano
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Medical Image Analysis Center (MIAC) AG, Basel, Switzerland
- Novartis Institutes for BioMedical Research Basel, Basel, Switzerland
| | - Athina Papadopoulou
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Federico Burguet Villena
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Till Sprenger
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- University Hospital Zürich, Zurich, Switzerland
| | | | - Ludwig Kappos
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Clinical Research, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Meritxell Garcia
- Division of Neuroradiology, Department of Radiology, University Hospital Basel, Basel, Switzerland.
- Department of Neuroradiology, University Hospital Zürich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
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Ananthavarathan P, Sahi N, Chard DT. An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression. Expert Rev Neurother 2024; 24:201-216. [PMID: 38235594 DOI: 10.1080/14737175.2024.2304116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024]
Abstract
INTRODUCTION While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear. AREAS COVERED The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning. EXPERT OPINION Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.
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Affiliation(s)
- Piriyankan Ananthavarathan
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Nitin Sahi
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Declan T Chard
- Clinical Research Associate & Consultant Neurologist, Institute of Neurology - Queen Square Multiple Sclerosis Centre, London, UK
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Kreiter D, Postma AA, Hupperts R, Gerlach O. Hallmarks of spinal cord pathology in multiple sclerosis. J Neurol Sci 2024; 456:122846. [PMID: 38142540 DOI: 10.1016/j.jns.2023.122846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement.
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Affiliation(s)
- Daniel Kreiter
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Raymond Hupperts
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Oliver Gerlach
- Academic MS Center Zuyd, Department of Neurology, Zuyderland MC, Sittard-Geleen, the Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
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Khormi I, Al-Iedani O, Alshehri A, Ramadan S, Lechner-Scott J. MR myelin imaging in multiple sclerosis: A scoping review. J Neurol Sci 2023; 455:122807. [PMID: 38035651 DOI: 10.1016/j.jns.2023.122807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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Hartung HP, Cree BA, Barnett M, Meuth SG, Bar-Or A, Steinman L. Bioavailable central nervous system disease-modifying therapies for multiple sclerosis. Front Immunol 2023; 14:1290666. [PMID: 38162670 PMCID: PMC10755740 DOI: 10.3389/fimmu.2023.1290666] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/09/2023] [Indexed: 01/03/2024] Open
Abstract
Disease-modifying therapies for relapsing multiple sclerosis reduce relapse rates by suppressing peripheral immune cells but have limited efficacy in progressive forms of the disease where cells in the central nervous system play a critical role. To our knowledge, alemtuzumab, fumarates (dimethyl, diroximel, and monomethyl), glatiramer acetates, interferons, mitoxantrone, natalizumab, ocrelizumab, ofatumumab, and teriflunomide are either limited to the periphery or insufficiently studied to confirm direct central nervous system effects in participants with multiple sclerosis. In contrast, cladribine and sphingosine 1-phosphate receptor modulators (fingolimod, ozanimod, ponesimod, and siponimod) are central nervous system-penetrant and could have beneficial direct central nervous system properties.
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Affiliation(s)
- Hans-Peter Hartung
- Department of Neurology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Department of Neurology, Medical University of Vienna, Vienna, Austria
- Department of Neurology, Palacký University Olomouc, Olomouc, Czechia
| | - Bruce A.C. Cree
- Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, United States
| | - Michael Barnett
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Sven G. Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Lawrence Steinman
- Department of Neurology and Neurological Sciences, Beckman Center for Molecular Medicine, Stanford University Medical Center, Stanford, CA, United States
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12
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Liu H, Grouza V, Tuznik M, Siminovitch KA, Bagheri H, Peterson A, Rudko DA. Self-labelled encoder-decoder (SLED) for multi-echo gradient echo-based myelin water imaging. Neuroimage 2022; 264:119717. [PMID: 36367497 DOI: 10.1016/j.neuroimage.2022.119717] [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: 06/13/2022] [Revised: 10/07/2022] [Accepted: 10/27/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Reconstruction of high quality myelin water imaging (MWI) maps is challenging, particularly for data acquired using multi-echo gradient echo (mGRE) sequences. A non-linear least squares fitting (NLLS) approach has often been applied for MWI. However, this approach may produce maps with limited detail and, in some cases, sub-optimal signal to noise ratio (SNR), due to the nature of the voxel-wise fitting. In this study, we developed a novel, unsupervised learning method called self-labelled encoder-decoder (SLED) to improve gradient echo-based MWI data fitting. METHODS Ultra-high resolution, MWI data was collected from five mouse brains with variable levels of myelination, using a mGRE sequence. Imaging data was acquired using a 7T preclinical MRI system. A self-labelled, encoder-decoder network was implemented in TensorFlow for calculation of myelin water fraction (MWF) based on the mGRE signal decay. A simulated MWI phantom was also created to evaluate the performance of MWF estimation. RESULTS Compared to NLLS, SLED demonstrated improved MWF estimation, in terms of both stability and accuracy in phantom tests. In addition, SLED produced less noisy MWF maps from high resolution MR microscopy images of mouse brain tissue. It specifically resulted in lower noise amplification for all mouse genotypes that were imaged and yielded mean MWF values in white matter ROIs that were highly correlated with those derived from standard NLLS fitting. Lastly, SLED also exhibited higher tolerance to low SNR data. CONCLUSION Due to its unsupervised and self-labeling nature, SLED offers a unique alternative to analyze gradient echo-based MWI data, providing accurate and stable MWF estimations.
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Affiliation(s)
- Hanwen Liu
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Vladimir Grouza
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Marius Tuznik
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Katherine A Siminovitch
- Departments of Medicine and Immunology, University of Toronto, Toronto, ON, Canada; Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Hooman Bagheri
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Alan Peterson
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Department of Human Genetics, McGill University, Montreal, QC, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
| | - David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.
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13
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Kitzler HH, Wahl H, Kuntke P, Deoni SCL, Ziemssen T, Linn J, Köhler C. Exploring in vivo lesion myelination dynamics: Longitudinal Myelin Water Imaging in early Multiple Sclerosis. Neuroimage Clin 2022; 36:103192. [PMID: 36162236 PMCID: PMC9668603 DOI: 10.1016/j.nicl.2022.103192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 08/31/2022] [Accepted: 09/09/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Multiple Sclerosis (MS) lesions are pathologically heterogeneous and the temporal behavior in terms of growth and myelination status of individual lesions is highly variable, especially in the early phase of the disease. Thus, monitoring the development of individual lesion myelination by using quantitative magnetic resonance myelin water imaging (MWI) could be valuable to capture the variability of disease pathology and get an individual insight into the subclinical disease activity. OBJECTIVE The goal of this work was (1) to observe the variation and longitudinal change of in vivo lesion myelination by means of MWI and its parameter Myelin Water Fraction (MWF), and, (2) to identify individual lesion myelination patterns in early MS. METHODS In this study n = 12 patients obtained conventional MRI and quantitative MWI derived from multi-component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) within four weeks after presenting a clinically isolated syndrome and remained within the study if clinically definitive MS was diagnosed within the 12 months study period. Four MRI sessions were acquired at baseline, 3, 6, and 12 months. The short-term and long-term variability of MWF maps was evaluated by scan-rescan measures and the coefficient of variation was determined in four healthy controls. Tracking of individual lesions was performed using the Automatic Follow-up of Individual Lesions (AFIL) algorithm. Lesion volume and MWF were evaluated for every individual lesion in all patients. Median lesion MWF change was used to define lesion categories as decreasing, varying, increasing and invariant for MWF variation. RESULTS In total n = 386 T2 lesions were detected with a subset of n = 225 permanent lesions present at all four time-points. Among those, a heterogeneous lesion MWF reduction was found, with the majority of lesions bearing only mild MWF reduction, approximately a third with an intermediate MWF decrease and highest MWF reduction in acute-inflammatory active lesions. A moderate negative correlation was determined between individual lesion volumes and median MWF consistent across all time-points. Permanent lesions featured variable temporal dynamics with the majority of varying MWF (58 %), however decreasing (16 %), increasing (15 %) and invariant (11 %) subgroups could be identified resembling demyelinating activity and post-demyelinating inactivity known from histopathology studies. Inflammatory-active enhancing lesions showed a distinct pattern of MWF reduction followed by partial recovery after 3 months. This was similar in new enhancing lesions and those with a non-enhancing precursor lesion. CONCLUSION This work provides in vivo evidence for an individual evolution of early demyelinated MS lesions measured by means of MWF imaging. Our results support the hypothesis, that MS lesions undergo multiple demyelination and remyelination episodes in the early acute phase. The in vivo MRI surrogate of myelin turnover bears capacity as a novel biomarker to select and potentially monitor personalized MS treatment.
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Affiliation(s)
- Hagen H Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany.
| | - Hannes Wahl
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Sean C L Deoni
- Department of Radiology, and Advanced Baby Imaging Lab, Warren Alpert Medical School at Brown University, Providence, RI, USA
| | - Tjalf Ziemssen
- Center of Cinical Neuroscience, Multiple Sclerosis Center, Department of Neurology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Jennifer Linn
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
| | - Caroline Köhler
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Germany
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14
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Ma YJ, Jang H, Lombardi AF, Corey-Bloom J, Bydder GM. Myelin water imaging using a short-TR adiabatic inversion-recovery (STAIR) sequence. Magn Reson Med 2022; 88:1156-1169. [PMID: 35613378 PMCID: PMC9867567 DOI: 10.1002/mrm.29287] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 01/26/2023]
Abstract
PURPOSE To develop a new myelin water imaging (MWI) technique using a short-TR adiabatic inversion-recovery (STAIR) sequence on a clinical 3T MR scanner. METHODS Myelin water (MW) in the brain has both a much shorter T1 and a much shorter T2 * than intracellular/extracellular water. A STAIR sequence with a short TR was designed to efficiently suppress long T1 signals from intracellular/extracellular water, and therefore allow selective imaging of MW, which has a much shorter T1 . Numerical simulation and phantom studies were performed to investigate the effectiveness of long T1 signal suppression. TheT2 * in white matter (WM) was measured with STAIR and compared with T2 * measured with a conventional gradient recall echo in in vivo study. Four healthy volunteers and 4 patients with multiple sclerosis were recruited for qualitative and quantitative MWI. Apparent MW fraction was generated to compare MW in normal WM in volunteers to MW in lesions in patients with multiple sclerosis. RESULTS Both simulation and phantom studies showed that when TR was sufficiently short (eg, 250 ms), the STAIR sequence effectively suppressed long T1 signals from tissues with a broad range of T1 s using a single TR/TI combination. The volunteer study showed a short T2 * of 9.5 ± 1.7 ms in WM, which is similar to reported values for MW. Lesions in patients with multiple sclerosis showed a significantly lower apparent MW fraction (4.5% ± 1.0%) compared with that of normal WM (9.2% ± 1.5%) in healthy volunteers (p < 0.05). CONCLUSIONS The STAIR sequence provides selective MWI in brain and can quantify reductions in MW content in patients with multiple sclerosis.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Alecio F. Lombardi
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jody Corey-Bloom
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
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15
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Haacke EM, Bernitsas E, Subramanian K, Utriainen D, Palutla VK, Yerramsetty K, Kumar P, Sethi SK, Chen Y, Latif Z, Jella P, Gharabaghi S, Wang Y, Zhang X, Comley RA, Beaver J, Luo Y. A Comparison of Magnetic Resonance Imaging Methods to Assess Multiple Sclerosis Lesions: Implications for Patient Characterization and Clinical Trial Design. Diagnostics (Basel) 2021; 12:diagnostics12010077. [PMID: 35054244 PMCID: PMC8775217 DOI: 10.3390/diagnostics12010077] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/20/2021] [Accepted: 12/22/2021] [Indexed: 11/16/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a sensitive imaging modality for identifying inflammatory and/or demyelinating lesions, which is critical for a clinical diagnosis of MS and evaluating drug responses. There are many unique means of probing brain tissue status, including conventional T1 and T2 weighted imaging (T1WI, T2WI), T2 fluid attenuated inversion recovery (FLAIR), magnetization transfer, myelin water fraction, diffusion tensor imaging (DTI), phase-sensitive inversion recovery and susceptibility weighted imaging (SWI), but no study has combined all of these modalities into a single well-controlled investigation. The goals of this study were to: compare different MRI measures for lesion visualization and quantification; evaluate the repeatability of various imaging methods in healthy controls; compare quantitative susceptibility mapping (QSM) with myelin water fraction; measure short-term longitudinal changes in the white matter of MS patients and map out the tissue properties of the white matter hyperintensities using STAGE (strategically acquired gradient echo imaging). Additionally, the outcomes of this study were anticipated to aid in the choice of an efficient imaging protocol reducing redundancy of information and alleviating patient burden. Of all the sequences used, T2 FLAIR and T2WI showed the most lesions. To differentiate the putative demyelinating lesions from inflammatory lesions, the fusion of SWI and T2 FLAIR was used. Our study suggests that a practical and efficient imaging protocol combining T2 FLAIR, T1WI and STAGE (with SWI and QSM) can be used to rapidly image MS patients to both find lesions and study the demyelinating and inflammatory characteristics of the lesions.
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Affiliation(s)
- Ewart Mark Haacke
- The MRI Institute for Biomedical Research, Bingham Farms, MI 48025, USA; (D.U.); (S.K.S.)
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
- Department of Neurology, Wayne State University, Detroit, MI 48201, USA; (E.B.); (Y.C.)
- SpinTech Inc., Bingham Farms, MI 48025, USA
- MR Innovations Inc., Bingham Farms, MI 48025, USA;
- Correspondence:
| | - Evanthia Bernitsas
- Department of Neurology, Wayne State University, Detroit, MI 48201, USA; (E.B.); (Y.C.)
| | - Karthik Subramanian
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
| | - David Utriainen
- The MRI Institute for Biomedical Research, Bingham Farms, MI 48025, USA; (D.U.); (S.K.S.)
- SpinTech Inc., Bingham Farms, MI 48025, USA
| | - Vinay Kumar Palutla
- MR Medical Imaging Innovations India Pvt. Ltd., Hyderabad 500081, India; (V.K.P.); (K.Y.); (P.K.)
| | - Kiran Yerramsetty
- MR Medical Imaging Innovations India Pvt. Ltd., Hyderabad 500081, India; (V.K.P.); (K.Y.); (P.K.)
| | - Prashanth Kumar
- MR Medical Imaging Innovations India Pvt. Ltd., Hyderabad 500081, India; (V.K.P.); (K.Y.); (P.K.)
| | - Sean K. Sethi
- The MRI Institute for Biomedical Research, Bingham Farms, MI 48025, USA; (D.U.); (S.K.S.)
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
- SpinTech Inc., Bingham Farms, MI 48025, USA
| | - Yongsheng Chen
- Department of Neurology, Wayne State University, Detroit, MI 48201, USA; (E.B.); (Y.C.)
| | - Zahid Latif
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
| | - Pavan Jella
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
| | | | - Ying Wang
- Department of Radiology, Wayne State University, Detroit, MI 48201, USA; (K.S.); (Z.L.); (P.J.); (Y.W.)
- MR Innovations Inc., Bingham Farms, MI 48025, USA;
| | - Xiaomeng Zhang
- AbbVie Inc., North Chicago, IL 60064, USA; (X.Z.); (R.A.C.); (J.B.); (Y.L.)
| | - Robert A. Comley
- AbbVie Inc., North Chicago, IL 60064, USA; (X.Z.); (R.A.C.); (J.B.); (Y.L.)
| | - John Beaver
- AbbVie Inc., North Chicago, IL 60064, USA; (X.Z.); (R.A.C.); (J.B.); (Y.L.)
| | - Yanping Luo
- AbbVie Inc., North Chicago, IL 60064, USA; (X.Z.); (R.A.C.); (J.B.); (Y.L.)
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16
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Cortese R, Giorgio A, Severa G, De Stefano N. MRI Prognostic Factors in Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, and Myelin Oligodendrocyte Antibody Disease. Front Neurol 2021; 12:679881. [PMID: 34867701 PMCID: PMC8636325 DOI: 10.3389/fneur.2021.679881] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 10/08/2021] [Indexed: 11/25/2022] Open
Abstract
Several MRI measures have been developed in the last couple of decades, providing a number of imaging biomarkers that can capture the complexity of the pathological processes occurring in multiple sclerosis (MS) brains. Such measures have provided more specific information on the heterogeneous pathologic substrate of MS-related tissue damage, being able to detect, and quantify the evolution of structural changes both within and outside focal lesions. In clinical practise, MRI is increasingly used in the MS field to help to assess patients during follow-up, guide treatment decisions and, importantly, predict the disease course. Moreover, the process of identifying new effective therapies for MS patients has been supported by the use of serial MRI examinations in order to sensitively detect the sub-clinical effects of disease-modifying treatments at an earlier stage than is possible using measures based on clinical disease activity. However, despite this has been largely demonstrated in the relapsing forms of MS, a poor understanding of the underlying pathologic mechanisms leading to either progression or tissue repair in MS as well as the lack of sensitive outcome measures for the progressive phases of the disease and repair therapies makes the development of effective treatments a big challenge. Finally, the role of MRI biomarkers in the monitoring of disease activity and the assessment of treatment response in other inflammatory demyelinating diseases of the central nervous system, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte antibody disease (MOGAD) is still marginal, and advanced MRI studies have shown conflicting results. Against this background, this review focused on recently developed MRI measures, which were sensitive to pathological changes, and that could best contribute in the future to provide prognostic information and monitor patients with MS and other inflammatory demyelinating diseases, in particular, NMOSD and MOGAD.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Gianmarco Severa
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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17
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Sommer RC, Hata J, Rimkus CDM, Klein da Costa B, Nakahara J, Sato DK. Mechanisms of myelin repair, MRI techniques and therapeutic opportunities in multiple sclerosis. Mult Scler Relat Disord 2021; 58:103407. [DOI: 10.1016/j.msard.2021.103407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 10/29/2021] [Accepted: 11/13/2021] [Indexed: 11/16/2022]
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18
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Liu H, Joseph TS, Xiang QS, Tam R, Kozlowski P, Li DKB, MacKay AL, Kramer JLK, Laule C. A data-driven T 2 relaxation analysis approach for myelin water imaging: Spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS). Magn Reson Med 2021; 87:915-931. [PMID: 34490909 DOI: 10.1002/mrm.29000] [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: 08/31/2020] [Revised: 08/16/2021] [Accepted: 08/17/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE The decomposition of multi-exponential decay data into a T2 spectrum poses substantial challenges for conventional fitting algorithms, including non-negative least squares (NNLS). Based on a combination of the resolution limit constraint and machine learning neural network algorithm, a data-driven and highly tailorable analysis method named spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS) was proposed. THEORY AND METHODS The theory of SAME-ECOS was derived. Then, a paradigm was presented to demonstrate the SAME-ECOS workflow, consisting of a series of calculation, simulation, and model training operations. The performance of the trained SAME-ECOS model was evaluated using simulations and six in vivo brain datasets. The code is available at https://github.com/hanwencat/SAME-ECOS. RESULTS Using NNLS as the baseline, SAME-ECOS achieved over 15% higher overall cosine similarity scores in producing the T2 spectrum, and more than 10% lower mean absolute error in calculating the myelin water fraction (MWF), as well as demonstrated better robustness to noise in the simulation tests. Applying to in vivo data, MWF from SAME-ECOS and NNLS was highly correlated among all study participants. However, a distinct separation of the myelin water peak and the intra/extra-cellular water peak was only observed in the mean T2 spectra determined using SAME-ECOS. In terms of data processing speed, SAME-ECOS is approximately 30 times faster than NNLS, achieving a whole-brain analysis in 3 min. CONCLUSION Compared with NNLS, the SAME-ECOS method yields much more reliable T2 spectra in a dramatically shorter time, increasing the feasibility of multi-component T2 decay analysis in clinical settings.
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Affiliation(s)
- Hanwen Liu
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tigris S Joseph
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Qing-San Xiang
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - Piotr Kozlowski
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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19
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Hurtado Rúa SM, Kaunzner UW, Pandya S, Sweeney E, Tozlu C, Kuceyeski A, Nguyen TD, Gauthier SA. Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients. Eur J Neurol 2021; 29:237-246. [PMID: 34402140 DOI: 10.1111/ene.15067] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 08/13/2021] [Accepted: 08/14/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients. OBJECTIVE We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients. METHODS Ninety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA). RESULTS One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337). CONCLUSIONS These results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.
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Affiliation(s)
- Sandra M Hurtado Rúa
- Department of Mathematics and Statistics, Cleveland State University, Cleveland, Ohio, USA
| | - Ulrike W Kaunzner
- Department of Neurology, Weill Cornell Medicine, New York City, New York, USA
| | - Sneha Pandya
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Elizabeth Sweeney
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, USA
| | - Ceren Tozlu
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA.,Feil Family Brain and Mind Institute, Weill Cornell Medicine, New York City, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York City, New York, USA
| | - Susan A Gauthier
- Department of Neurology, Weill Cornell Medicine, New York City, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York City, New York, USA.,Feil Family Brain and Mind Institute, Weill Cornell Medicine, New York City, New York, USA
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20
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A proposal: How to study pro-myelinating proteins in MS. Autoimmun Rev 2021; 21:102924. [PMID: 34416371 DOI: 10.1016/j.autrev.2021.102924] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 08/14/2021] [Indexed: 12/15/2022]
Abstract
Multiple sclerosis (MS) is an inflammatory and degenerative disease of the CNS. An unmet need in MS is repair i.e.,promoting endogenous regeneration and remyelination after demyelinating inflammatory injury. Remyelination is critical in neuronal preservation and the prevention of clinical progression. There is a good deal of evidence for histological repair and remyelination in MS patients. Repair is driven by several prominent endogenous pro-myelinating proteinsincluding neural cellular adhesion molecule (N-CAM) and brain derived neurotrophic factor (BDNF) among others. To follow changes during acute re-myelination in vivo in MS subjects, non conventional MRI techniques are necessary such as quantitative susceptibility mapping (QSM) that detects the release of Fe from dying oligodendroglial cells and myelin water imaging (MWI) that detects water captured within newly formed myelin. The best time to monitor changes in pro-myelinating proteins and link those changes to imaging evolution is immediately after the acute inflammatory response in MS lesions (gadolinium enhancement [Gd+]) during an intense period of remyelination. We can monitor MS subjects with new Gd + lesions with periodic imaging along with sampling of blood and CSF and determine if myelin formation is linked with increases in pro-myelinating proteins. This would lead to potential therapeutic manipulation with directly administered proteins to promote CNS re-myelination in animal models and in early clinical trials.
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21
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Maekawa T, Hagiwara A, Yokoyama K, Hori M, Andica C, Fujita S, Kamagata K, Wada A, Abe O, Tomizawa Y, Hattori N, Aoki S. Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics. Neuroradiology 2021; 64:465-471. [PMID: 34383123 DOI: 10.1007/s00234-021-02781-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/30/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.
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Affiliation(s)
- Tomoko Maekawa
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Kazumasa Yokoyama
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
- Department of Diagnostic Radiology, Toho University Omori Medical Center, 6-11-1, Omori-Nishi, Ota-Ku, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shohei Fujita
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
- Departmen of Radiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Akihiko Wada
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Osamu Abe
- Departmen of Radiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yuji Tomizawa
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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22
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Vavasour IM, Chang KL, Combes AJE, Meyers SM, Kolind SH, Rauscher A, Li DKB, Traboulsee A, MacKay AL, Laule C. Water content changes in new multiple sclerosis lesions have a minimal effect on the determination of myelin water fraction values. J Neuroimaging 2021; 31:1119-1125. [PMID: 34310789 DOI: 10.1111/jon.12908] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/07/2021] [Accepted: 07/07/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND AND PURPOSE Myelin water fraction (MWF) is a histopathologically validated in vivo myelin marker. As MWF is the proportion of water with a short T2 relative to the total water, increases in water from edema and inflammation may confound MWF determination in multiple sclerosis (MS) lesions. Total water content (TWC) measurement enables calculation of absolute myelin water content (MWC) and can be used to distinguish edema/inflammation from demyelination. We assessed what influence changes in total water might have on MWF by calculating MWC values in new MS lesions. METHODS 3T 32-echo T2 relaxation data were collected monthly for 6 months from six relapsing-remitting MS participants. TWC was determined and multiplied with MWF images to calculate corrected MWC images. The effect of this water content correction was examined in 20 new lesions by comparing mean MWF and MWC over time. RESULTS On average, at lesion first appearance, lesion TWC increased by 6.4% (p = .003; range: -1% to +21%), MWF decreased by 24% (p = .006; range: -70% to +12%), and MWC decreased by 20% (p = .026; range: -68% to +21%), relative to prelesion values. Average TWC in lesions then gradually decreased, whereas MWF and MWC remained low. The shape of the MWF and MWC lesion evolution curves was nearly identical, differing only by an offset. CONCLUSION MWF mirrors MWC and is able to monitor myelin in new lesions. Even after taking into account water content increases, MWC still decreased at lesion first appearance attributed to demyelination.
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Affiliation(s)
- Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - Kimberley L Chang
- Department of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Anna J E Combes
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sandra M Meyers
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiation Medicine and Applied Sciences, University of California, San Diego, California, USA
| | - Shannon H Kolind
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Rauscher
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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23
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Panou Τ, Kavroulakis E, Mastorodemos V, Pouli S, Kalaitzakis G, Spyridaki E, Maris TG, Simos P, Papadaki E. Myelin content changes in Clinically Isolated Syndrome and Relapsing- Remitting Multiple Sclerosis: Associations with lesion type and severity of visuomotor impairment. Mult Scler Relat Disord 2021; 54:103108. [PMID: 34198031 DOI: 10.1016/j.msard.2021.103108] [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: 03/13/2021] [Revised: 05/26/2021] [Accepted: 06/20/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Cognitive disturbances occur in patients with Relapsing Remitting Multiple Sclerosis (RR-MS) and Clinically Isolated Syndrome (CIS). The Multi-Echo-Spin-Echo (MESE) T2-weighted sequence quantifies demyelination, the pathological hallmark of MS, but has not been used for the documentation of the potential relationship between anatomically specific demyelinating changes and cognitive impairment in MS. PURPOSE To identify markers of regional demyelination in patients with RR-MS and CIS in relation to clinical variables and severity of cognitive impairment. METHODS AND MATERIALS 37 RR-MS patients, 39 CIS patients and 52 healthy controls (HC) were examined using the MESE sequence. Long T2 and myelin water fraction (MWF) values were measured, serving as indices of intra/extracellular water content and myelin content, respectively, in focal white matter lesions and 12 normal appearing white matter (NAWM) areas of the patients and HC. A comprehensive neuropsychological assessment was administered to all patients. RESULTS RR-MS patients showed widespread long T2 increases and MWF reductions in NAWM, compared to the respective values of HC (p < 0.001), which correlated with total lesion volume. Among RR-MS patients illness duration correlated negatively with MWF in right hemisphere frontal and periventricular NAWM areas (and positively with corresponding long T2 values). MWF values were lower in the CIS, as compared to the HC group, in the temporal, frontal and periventricular NAWM areas. Focal demyelinating lesions displayed variable higher T2 and lower MWF values, compared to NAWM, closely corresponding to their intensity on T1 sequences. Reduced MWF values and increased long T2 values in right periventricular NAWM were significantly associated with poor visuomotor performance. CONCLUSION The MESE sequence affords accurate estimation of myelin and water content in NAWM and focal lesions in RR-MS and CIS patients, by means of the MWF and long T2 values, respectively, providing a sensitive index of demyelination associated with visuomotor deficits.
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Affiliation(s)
- Τheodora Panou
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Styliani Pouli
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Georgios Kalaitzakis
- Department of Medical Physics, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eirini Spyridaki
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Thomas G Maris
- Department of Medical Physics, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece; Institute of Computer Science, Foundation of Research and Technology-Hellas, Voutes, Heraklion, Greece
| | - Panagiotis Simos
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece; Institute of Computer Science, Foundation of Research and Technology-Hellas, Voutes, Heraklion, Greece
| | - Efrosini Papadaki
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece; Institute of Computer Science, Foundation of Research and Technology-Hellas, Voutes, Heraklion, Greece.
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24
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - 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
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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25
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Vavasour IM, Sun P, Graf C, Yik JT, Kolind SH, Li DK, Tam R, Sayao AL, Schabas A, Devonshire V, Carruthers R, Traboulsee A, Moore GW, Song SK, Laule C. Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging. Mult Scler 2021; 28:418-428. [PMID: 34132126 DOI: 10.1177/13524585211023345] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T1 and T2 relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS. OBJECTIVE To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes. METHODS 103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T1, T2, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes. RESULTS A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures. CONCLUSION Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.
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Affiliation(s)
- Irene M Vavasour
- Department of Radiology, The University of British Columbia, UBC Hospital, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada
| | - Peng Sun
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Carina Graf
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Jackie T Yik
- Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - David Kb Li
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Ana-Luiza Sayao
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alice Schabas
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Virginia Devonshire
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Robert Carruthers
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Gr Wayne Moore
- Department of Medicine, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Sheng-Kwei Song
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Cornelia Laule
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada/International Collaboration on Repair Discoveries (ICORD), The University of British Columbia, Vancouver, BC, Canada/Department of Physics & Astronomy, The University of British Columbia, Vancouver, BC, Canada/Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
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26
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Papadaki E, Mastorodemos V, Panou T, Pouli S, Spyridaki E, Kavroulakis E, Kalaitzakis G, Maris TG, Simos P. T2 Relaxometry Evidence of Microstructural Changes in Diffusely Abnormal White Matter in Relapsing-Remitting Multiple Sclerosis and Clinically Isolated Syndrome: Impact on Visuomotor Performance. J Magn Reson Imaging 2021; 54:1077-1087. [PMID: 33960066 DOI: 10.1002/jmri.27661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/08/2021] [Accepted: 04/08/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Although diffusely abnormal white matter (DAWM) is commonly seen in multiple sclerosis (MS), it is rarely considered in clinical/imaging studies. PURPOSE To evaluate quantitative markers of microstructural changes in DAWM of patients with clinically isolated syndrome (CIS) and relapsing-remitting MS (RR-MS) in relation to MS lesions and degree of neurocognitive impairment, by using a multi-echo spin echo (MESE) Proton Density PD-to-T2 sequence. STUDY TYPE Prospective, cross-sectional. POPULATION Thirty-seven RR-MS patients, 33 CIS patients, and 52 healthy controls. FIELD STRENGTH/SEQUENCE 1.5 T/T1-, T2-weighted, fluid-attenuated inversion recovery, and MESE sequences. ASSESSMENT Long T2, short T2, and myelin water fraction (MWF) values were estimated as indices of intra/extracellular water content and myelin content, respectively, in DAWM, posterior periventricular normal appearing white matter (NAWM), and focal MS lesions, classified according to their signal intensity on T1 sequences. Patients were, also, administered a battery of neuropsychological tests. STATISTICAL TESTS Comparisons of T2 and MWF values in DAWM, NAWM, and MS lesions were examined, using two-way mixed analyses of variance. Associations of Grooved Pegboard performance with T2 and MWF values in DAWM and NAWM were assessed using Pearson correlation coefficients. RESULTS T2 and MWF values of DAWM were intermediate between the respective values of NAWM and T1 hypointense focal lesions, while there was no difference between the respective values of DAWM and T1-isointense lesions. T2 values in DAWM were strongly associated with visuomotor performance in CIS patients. DATA CONCLUSION Intra/extracellular water and myelin water content of DAWM are similar to those of T1-isointense lesions and predict visuomotor performance in CIS patients. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Efrosini Papadaki
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
- Institute of Computer Science, Foundation of Research and Technology-Hellas, Heraklion, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Theodora Panou
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Styliani Pouli
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eirini Spyridaki
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Georgios Kalaitzakis
- Department of Medical Physics, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Thomas G Maris
- Institute of Computer Science, Foundation of Research and Technology-Hellas, Heraklion, Greece
- Department of Medical Physics, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Panagiotis Simos
- Institute of Computer Science, Foundation of Research and Technology-Hellas, Heraklion, Greece
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
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27
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Lynn JD, Anand C, Arshad M, Homayouni R, Rosenberg DR, Ofen N, Raz N, Stanley JA. Microstructure of Human Corpus Callosum across the Lifespan: Regional Variations in Axon Caliber, Density, and Myelin Content. Cereb Cortex 2021; 31:1032-1045. [PMID: 32995843 PMCID: PMC7906774 DOI: 10.1093/cercor/bhaa272] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/21/2020] [Accepted: 08/21/2020] [Indexed: 12/13/2022] Open
Abstract
The myeloarchitecture of the corpus callosum (CC) is characterized as a mosaic of distinct differences in fiber density of small- and large-diameter axons along the anterior-posterior axis; however, regional and age differences across the lifespan are not fully understood. Using multiecho T2 magnetic resonance imaging combined with multi-T2 fitting, the myelin water fraction (MWF) and geometric-mean of the intra-/extracellular water T2 (geomT2IEW) in 395 individuals (7-85 years; 41% males) were examined. The approach was validated where regional patterns along the CC closely resembled the histology; MWF matched mean axon diameter and geomT2IEW mirrored the density of large-caliber axons. Across the lifespan, MWF exhibited a quadratic association with age in all 10 CC regions with evidence of a positive linear MWF-age relationship among younger participants and minimal age differences in the remainder of the lifespan. Regarding geomT2IEW, a significant linear age × region interaction reflected positive linear age dependence mostly prominent in the regions with the highest density of small-caliber fibers-genu and splenium. In all, these two indicators characterize distinct attributes that are consistent with histology, which is a first. In addition, these results conform to rapid developmental progression of CC myelination leveling in middle age as well as age-related degradation of axon sheaths in older adults.
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Affiliation(s)
- Jonathan D Lynn
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
| | - Chaitali Anand
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
| | - Muzamil Arshad
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
| | - Roya Homayouni
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
| | - David R Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
- Lifespan Cognitive Neuroscience, Merrill Palmer Skillman Institute, Wayne State University, Detroit MI 14195, USA
| | - Naftali Raz
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - Jeffrey A Stanley
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
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Chan KS, Marques JP. Multi-compartment relaxometry and diffusion informed myelin water imaging – Promises and challenges of new gradient echo myelin water imaging methods. Neuroimage 2020; 221:117159. [DOI: 10.1016/j.neuroimage.2020.117159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 07/06/2020] [Accepted: 07/07/2020] [Indexed: 01/08/2023] Open
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Pandya S, Kaunzner UW, Hurtado Rúa SM, Nealon N, Perumal J, Vartanian T, Nguyen TD, Gauthier SA. Impact of Lesion Location on Longitudinal Myelin Water Fraction Change in Chronic Multiple Sclerosis Lesions. J Neuroimaging 2020; 30:537-543. [PMID: 32579281 DOI: 10.1111/jon.12716] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 04/02/2020] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND AND PURPOSE To examine the impact of lesion location on longitudinal myelin water fraction (MWF) changes in chronic multiple sclerosis (MS) lesions. Relative hypoxia, due to vascular watershed regions of the cerebrum, has been implicated in lesion development but impact on ongoing demyelination is unknown. METHODS Forty-eight patients with relapsing-remitting and secondary progressive MS had two MWF scans with fast acquisition, spiral trajectory, and T2prep (FAST-T2) sequence, at an interval of 2.0 (±.3) years. Lesion location was identified based upon cerebral lobe and relation to the ventricles. Change in MWF was assessed using a mixed effects model, controlling for lesion location and patient covariates. RESULTS Average age was 42.3 (±12) years, mean disease duration was 9.7 (±9.1) years, and median Expanded Disability Status Score (EDSS) was 2.5 (±2.3). The majority of 512 chronic lesions was located in the frontal and parietal lobes (75.6%) and more often periventricular (44.7%). All occipital lesions were periventricular. The average lesion MWF decreased from baseline (.07 ± .03) to 2 years (.06 ±.03) P < .01. Lesions within the occipital lobe showed a significant reduction in MWF as compared to other lobes. CONCLUSIONS Chronic lesions in the occipital lobe showed the greatest reduction in MWF. Neuroanatomical localization of lesions to the occipital horns of the lateral ventricles, a watershed region, may contribute to ongoing demyelination in this lesion type.
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Affiliation(s)
- Sneha Pandya
- Department of Radiology, Weil Cornell Medicine, New York City, NY
| | - Ulrike W Kaunzner
- Multiple Sclerosis Center, Weill Cornell Medicine, New York City, NY
| | - Sandra M Hurtado Rúa
- Department of Mathematics and Statistics, Cleveland State University, Cleveland, OH
| | - Nancy Nealon
- Multiple Sclerosis Center, Weill Cornell Medicine, New York City, NY
| | - Jai Perumal
- Multiple Sclerosis Center, Weill Cornell Medicine, New York City, NY
| | - Timothy Vartanian
- Multiple Sclerosis Center, Weill Cornell Medicine, New York City, NY
| | - Thanh D Nguyen
- Department of Radiology, Weil Cornell Medicine, New York City, NY
| | - Susan A Gauthier
- Department of Radiology, Weil Cornell Medicine, New York City, NY.,Multiple Sclerosis Center, Weill Cornell Medicine, New York City, NY
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Morris SR, Holmes RD, Dvorak AV, Liu H, Yoo Y, Vavasour IM, Mazabel S, Mädler B, Kolind SH, Li DKB, Siegel L, Beaulieu C, MacKay AL, Laule C. Brain Myelin Water Fraction and Diffusion Tensor Imaging Atlases for 9-10 Year-Old Children. J Neuroimaging 2020; 30:150-160. [PMID: 32064721 DOI: 10.1111/jon.12689] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 12/18/2019] [Accepted: 01/17/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND AND PURPOSE Myelin water imaging (MWI) and diffusion tensor imaging (DTI) provide information about myelin and axon-related brain microstructure, which can be useful for investigating normal brain development and many childhood brain disorders. While pediatric DTI atlases exist, there are no pediatric MWI atlases available for the 9-10 years old age group. As myelination and structural development occurs throughout childhood and adolescence, studies of pediatric brain pathologies must use age-specific MWI and DTI healthy control data. We created atlases of myelin water fraction (MWF) and DTI metrics for healthy children aged 9-10 years for use as normative data in pediatric neuroimaging studies. METHODS 3D-T1 , DTI, and MWI scans were acquired from 20 healthy children (mean age: 9.6 years, range: 9.2-10.3 years, 4 females). ANTs and FSL registration were used to create quantitative MWF and DTI atlases. Region of interest (ROI) analysis in nine white matter regions was used to compare pediatric MWF with adult MWF values from a recent study and to investigate the correlation between pediatric MWF and DTI metrics. RESULTS Adults had significantly higher MWF than the pediatric cohort in seven of the nine white matter ROIs, but not in the genu of the corpus callosum or the cingulum. In the pediatric data, MWF correlated significantly with mean diffusivity, but not with axial diffusivity, radial diffusivity, or fractional anisotropy. CONCLUSIONS Normative MWF and DTI metrics from a group of 9-10 year old healthy children provide a resource for comparison to pathologies. The age-specific atlases are ready for use in pediatric neuroimaging research and can be accessed: https://sourceforge.net/projects/pediatric-mri-myelin-diffusion/.
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Affiliation(s)
- Sarah R Morris
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | | | - Adam V Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries, Vancouver, BC, Canada
| | - Hanwen Liu
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries, Vancouver, BC, Canada
| | - Youngjin Yoo
- Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Silvia Mazabel
- Educational and Counseling Psychology, and Special Education, University of British Columbia, Vancouver, BC, Canada
| | | | - Shannon H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada.,Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada.,Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Linda Siegel
- Educational and Counseling Psychology, and Special Education, University of British Columbia, Vancouver, BC, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada
| | - Alex L MacKay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada.,Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
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31
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Lee J, Hyun JW, Lee J, Choi EJ, Shin HG, Min K, Nam Y, Kim HJ, Oh SH. So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging. J Magn Reson Imaging 2020; 53:360-373. [PMID: 32009271 DOI: 10.1002/jmri.27059] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/01/2020] [Accepted: 01/02/2020] [Indexed: 12/22/2022] Open
Abstract
Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T2 -, T2 *-, T1 -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.
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Affiliation(s)
- Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Jae-Won Hyun
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Jieun Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Eun-Jung Choi
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Hyeong-Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Kyeongseon Min
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Yoonho Nam
- Department of Radiology, Seoul Saint Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Ho Jin Kim
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, Korea.,Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
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32
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Liu H, Xiang QS, Tam R, Dvorak AV, MacKay AL, Kolind SH, Traboulsee A, Vavasour IM, Li DKB, Kramer JK, Laule C. Myelin water imaging data analysis in less than one minute. Neuroimage 2020; 210:116551. [PMID: 31978542 DOI: 10.1016/j.neuroimage.2020.116551] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 12/21/2019] [Accepted: 01/14/2020] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF). METHODS A NN was constructed and trained on MWI data acquired by a 32-echo 3D gradient and spin echo (GRASE) sequence. Ground truth labels were created by regularized non-negative least squares (NNLS) with stimulated echo corrections. Voxel-wise GRASE data from 5 brains (4 healthy, 1 multiple sclerosis (MS)) were used for NN training. The trained NN was tested on 2 healthy brains, 1 MS brain with segmented lesions, 1 healthy spinal cord, and 1 healthy brain acquired from a different scanner. RESULTS Production of whole brain MWF maps in approximately 33 s can be achieved by a trained NN without graphics card acceleration. For all testing regions, no visual differences between NN and NNLS MWF maps were observed, and no obvious regional biases were found. Quantitatively, all voxels exhibited excellent agreement between NN and NNLS (all R2>0.98, p < 0.001, mean absolute error <0.01). CONCLUSION The time for accurate MWF calculation can be dramatically reduced to less than 1 min by the proposed NN, addressing one of the barriers facing future clinical feasibility of MWI.
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Affiliation(s)
- Hanwen Liu
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada
| | - Qing-San Xiang
- Physics & Astronomy, University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - Roger Tam
- Radiology, University of British Columbia, Canada; Biomedical Engineering, University of British Columbia, Canada
| | - Adam V Dvorak
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada
| | - Alex L MacKay
- Physics & Astronomy, University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - Shannon H Kolind
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada; Medicine, University of British Columbia, Canada
| | | | - Irene M Vavasour
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada
| | - David K B Li
- Radiology, University of British Columbia, Canada; Medicine, University of British Columbia, Canada
| | - John K Kramer
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Kinesiology, University of British Columbia, Canada
| | - Cornelia Laule
- Physics & Astronomy, University of British Columbia, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Canada; Radiology, University of British Columbia, Canada; Pathology & Laboratory Medicine, University of British Columbia, Canada.
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Quantitative age-dependent differences in human brainstem myelination assessed using high-resolution magnetic resonance mapping. Neuroimage 2019; 206:116307. [PMID: 31669302 DOI: 10.1016/j.neuroimage.2019.116307] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 12/13/2022] Open
Abstract
Previous in-vivo magnetic resonance imaging (MRI)-based studies of age-related differences in the human brainstem have focused on volumetric morphometry. These investigations have provided pivotal insights into regional brainstem atrophy but have not addressed microstructural age differences. However, growing evidence indicates the sensitivity of quantitative MRI to microstructural tissue changes in the brain. These studies have largely focused on the cerebrum, with very few MR investigations addressing age-dependent differences in the brainstem, in spite of its central role in the regulation of vital functions. Several studies indicate early brainstem alterations in a myriad of neurodegenerative diseases and dementias. The paucity of MR-focused investigations is likely due in part to the challenges imposed by the small structural scale of the brainstem itself as well as of substructures within, requiring accurate high spatial resolution imaging studies. In this work, we applied our recently developed approach to high-resolution myelin water fraction (MWF) mapping, a proxy for myelin content, to investigate myelin differences with normal aging within the brainstem. In this cross-sectional investigation, we studied a large cohort (n = 125) of cognitively unimpaired participants spanning a wide age range (21-94 years) and found a decrease in myelination with age in most brainstem regions studied, with several regions exhibiting a quadratic association between myelin and age. We believe that this study is the first investigation of MWF differences with normative aging in the adult brainstem. Further, our results provide reference MWF values.
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Liu H, Rubino C, Dvorak AV, Jarrett M, Ljungberg E, Vavasour IM, Lee LE, Kolind SH, MacMillan EL, Traboulsee A, Lang DJ, Rauscher A, Li DKB, MacKay AL, Boyd LA, Kramer JLK, Laule C. Myelin Water Atlas: A Template for Myelin Distribution in the Brain. J Neuroimaging 2019; 29:699-706. [PMID: 31347238 DOI: 10.1111/jon.12657] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Revised: 06/28/2019] [Accepted: 07/06/2019] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND AND PURPOSE Myelin water imaging (MWI) is a magnetic resonance imaging technique that quantifies myelin in-vivo. Although MWI has been extensively applied to study myelin-related diseases in groups, clinical use in individual patients is challenging mainly due to population heterogeneity. The purpose of this study was twofold: (1) create a normative brain myelin water atlas depicting the population mean and regional variability of myelin content; and (2) apply the myelin atlas to assess the degree of demyelination in individuals with multiple sclerosis (MS). METHODS 3T MWI was performed on 50 healthy adults (25 M/25 F, mean age 25 years [range 17-42 years]). The myelin water atlas was created by averaging coregistered myelin water fraction (MWF) maps from all healthy individuals. To illustrate the preliminary utility of the atlas, white matter (WM) regional MWF variations were evaluated and voxel-wise z-score maps (z < -1.96) from the MWI of three MS participants were produced to assess individually the degree of demyelination. RESULTS The myelin water atlas demonstrated significant MWF variation across control WM. No significant MWF differences were found between male and female healthy participants. MS z-score maps revealed diffuse regions of demyelination in the two participants with Expanded Disability Status Scale (EDSS) = 2.0 but not in the participant with EDSS = 0. CONCLUSIONS The myelin water atlas can be used as a reference (URL: https://sourceforge.net/projects/myelin-water-atlas/) to demonstrate areas of demyelination in individual MS participants. Future studies will expand the atlas age range, account for education, and other variables that may affect myelination.
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Affiliation(s)
- Hanwen Liu
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cristina Rubino
- Rehabilitation Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Adam V Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael Jarrett
- Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Erin L MacMillan
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,MR Clinical Science, Philips Healthcare Canada, Markham, Ontario, Canada.,ImageTech Lab, Simon Fraser University, Surrey, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donna J Lang
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Rauscher
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander L MacKay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lara A Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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35
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Drenthen GS, Backes WH, Aldenkamp AP, Jansen JF. Applicability and reproducibility of 2D multi-slice GRASE myelin water fraction with varying acquisition acceleration. Neuroimage 2019; 195:333-339. [DOI: 10.1016/j.neuroimage.2019.04.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 03/20/2019] [Accepted: 04/03/2019] [Indexed: 12/12/2022] Open
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Baldassari LE, Feng J, Clayton BLL, Oh SH, Sakaie K, Tesar PJ, Wang Y, Cohen JA. Developing therapeutic strategies to promote myelin repair in multiple sclerosis. Expert Rev Neurother 2019; 19:997-1013. [PMID: 31215271 DOI: 10.1080/14737175.2019.1632192] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Introduction: Approved disease-modifying therapies for multiple sclerosis (MS) lessen inflammatory disease activity that causes relapses and MRI lesions. However, chronic inflammation and demyelination lead to axonal degeneration and neuronal loss, for which there currently is no effective treatment. There has been increasing interest in developing repair-promoting strategies, but there are important unanswered questions regarding the mechanisms and appropriate methods to evaluate these treatments. Areas covered: The rationale for remyelinating agents in MS is discussed, with an overview of both myelin physiology and endogenous repair mechanisms. This is followed by a discussion of the identification and development of potential remyelinating drugs. Potential biomarkers of remyelination are reviewed, including considerations regarding measuring remyelination in clinical trials. Information and data were obtained from a search of recent literature through PubMed. Peer-reviewed original articles and review articles were included. Expert opinion: There are several obstacles to the translation of potential remyelinating agents to clinical trials, particularly uncertainty regarding the most appropriate study population and method to monitor remyelination. Refinements in clinical trial design and outcome measurement, potentially via advanced imaging techniques, are needed to optimize detection of repair in patients with MS.
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Affiliation(s)
- Laura E Baldassari
- Mellen Center for MS Treatment and Research, Cleveland Clinic , Cleveland , OH , USA
| | - Jenny Feng
- Mellen Center for MS Treatment and Research, Cleveland Clinic , Cleveland , OH , USA
| | - Benjamin L L Clayton
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine , Cleveland , OH , USA
| | - Se-Hong Oh
- Department of Biomedical Engineering, Hankuk University of Foreign Studies , Yongin , Republic of Korea
| | - Ken Sakaie
- Imaging Institute, Cleveland Clinic , Cleveland , OH , USA
| | - Paul J Tesar
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine , Cleveland , OH , USA
| | - Yanming Wang
- Department of Radiology, Case Western Reserve University School of Medicine , Cleveland , OH , USA
| | - Jeffrey A Cohen
- Mellen Center for MS Treatment and Research, Cleveland Clinic , Cleveland , OH , USA
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37
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Dvorak AV, Ljungberg E, Vavasour IM, Liu H, Johnson P, Rauscher A, Kramer JLK, Tam R, Li DKB, Laule C, Barlow L, Briemberg H, MacKay AL, Traboulsee A, Kozlowski P, Cashman N, Kolind SH. Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage. NEUROIMAGE-CLINICAL 2019; 23:101896. [PMID: 31276928 PMCID: PMC6611998 DOI: 10.1016/j.nicl.2019.101896] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 06/08/2019] [Accepted: 06/11/2019] [Indexed: 12/13/2022]
Abstract
Background Rapid myelin water imaging (MWI) using a combined gradient and spin echo (GRASE) sequence can produce myelin specific metrics for the human brain. Spinal cord MWI could be similarly useful, but technical challenges have hindered routine application. GRASE rapid MWI was recently successfully implemented for imaging of healthy cervical spinal cord and may complement other advanced imaging methods, such as diffusion tensor imaging (DTI) and quantitative T1 (qT1). Objective To demonstrate the feasibility of cervical cord GRASE rapid MWI in multiple sclerosis (MS), primary lateral sclerosis (PLS) and neuromyelitis optica spectrum disorder (NMO), with comparison to DTI and qT1 metrics. Methods GRASE MWI, DTI and qT1 data were acquired in 2 PLS, 1 relapsing-remitting MS (RRMS), 1 primary-progressive MS (PPMS) and 2 NMO subjects, as well as 6 age (±3 yrs) and sex matched healthy controls (HC). Internal cord structure guided template registrations, used for region of interest (ROI) analysis. Z score maps were calculated for the difference between disease subject and mean HC metric values. Results PLS subjects had low myelin water fraction (MWF) in the lateral funiculi compared to HC. RRMS subject MWF was heterogeneous within the cord. The PPMS subject showed no trends in ROI results but had a region of low MWF Z score corresponding to a focal lesion. The NMO subject with a longitudinally extensive transverse myelitis lesion had low values for whole cord mean MWF of 12.8% compared to 24.3% (standard deviation 2.2%) for HC. The NMO subject without lesions also had low MWF compared to HC. DTI and qT1 metrics showed similar trends, corroborating the MWF results and providing complementary information. Conclusion GRASE is sufficiently sensitive to detect decreased myelin within MS spinal cord plaques, NMO lesions, and PLS diffuse spinal cord injury. Decreased MWF in PLS is consistent with demyelination secondary to motor neuron degeneration. GRASE MWI is a feasible method for rapid assessment of myelin content in the cervical spinal cord and provides complementary information to that of DTI and qT1 measures. Downstream myelin changes in motor tracts of primary lateral sclerosis spinal cord. Low myelin water fraction in multiple sclerosis and neuromyelitis optica cord lesions. Diffuse demyelination evidence in neuromyelitis optica normal-appearing white matter. Myelin water imaging provides complementary information to diffusion and T1 metrics.
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Affiliation(s)
- Adam V Dvorak
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada.
| | - Emil Ljungberg
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park PO89, London SE5 8AF, United Kingdom
| | - Irene M Vavasour
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada
| | - Hanwen Liu
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada
| | - Poljanka Johnson
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada
| | - Alexander Rauscher
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; Pediatrics, University of British Columbia, 4480 Oak Street BC Children's Hospital Vancouver, BC V6H 3V4, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; School of Kinesiology, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC V6T 1Z1, Canada
| | - Roger Tam
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; School of Biomedical Engineering, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - David K B Li
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; Pathology & Laboratory Medicine, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada
| | - Laura Barlow
- Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Hannah Briemberg
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Alex L MacKay
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada
| | - Anthony Traboulsee
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Piotr Kozlowski
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; UBC MRI Research Centre, University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Neil Cashman
- Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
| | - Shannon H Kolind
- Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada; Radiology, University of British Columbia, 2775 Laurel Street, Vancouver, BC V5Z 1M9, Canada; International Collaboration on Repair Discoveries, University of British Columbia, 818 West 10th Avenue, Vancouver, BC V5Z 1M9, Canada; Medicine (Neurology), University of British Columbia, 2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada
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Tiwari AD, Zhu J, You J, Eck B, Zhu J, Wang X, Wang X, Wang B, Silver J, Wilson D, Wu C, Wang Y. Novel 18F-Labeled Radioligands for Positron Emission Tomography Imaging of Myelination in the Central Nervous System. J Med Chem 2019; 62:4902-4914. [PMID: 31042384 DOI: 10.1021/acs.jmedchem.8b01354] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Myelin is the protective sheath that surrounds nerves in vertebrates to protect axons, which thereby facilitates impulse conduction. Damage to myelin is associated with many neurodegenerative diseases such as multiple sclerosis and also includes spinal cord injury (SCI). The small size of the spinal cord poses formidable challenges to in vivo monitoring of myelination, which we investigated via conducting a structure-activity relationship study to determine the optimum positron-emitting agent to use for imaging myelin using positron emission tomography (PET). From these studies, [18F]PENDAS was identified as the lead agent to use in conjunction with PET imaging to delineate the integrity of spinal cord myelin. A subsequent in vivo PET imaging study of [18F]PENDAS in rats with SCI showed promising pharmacokinetic results that justify further development of imaging markers for diagnosing myelin-related diseases. Additionally, [18F]PENDAS could be valuable in determining the efficacy of therapies that are currently under development.
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Affiliation(s)
| | | | | | | | | | - Xu Wang
- Department of Radiology , Binzhou Medical University , Binzhou , Shandong 256603 , China
| | - Xizhen Wang
- Department of Radiology , Weifang Medical University , Weifang , Shandong 261053 , China
| | - Bin Wang
- Department of Radiology , Binzhou Medical University , Binzhou , Shandong 256603 , China
| | | | | | | | - Yanming Wang
- Department of Radiology , Binzhou Medical University , Binzhou , Shandong 256603 , China
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Heckova E, Strasser B, Hangel GJ, Považan M, Dal-Bianco A, Rommer PS, Bednarik P, Gruber S, Leutmezer F, Lassmann H, Trattnig S, Bogner W. 7 T Magnetic Resonance Spectroscopic Imaging in Multiple Sclerosis: How Does Spatial Resolution Affect the Detectability of Metabolic Changes in Brain Lesions? Invest Radiol 2019; 54:247-254. [PMID: 30433892 PMCID: PMC7612616 DOI: 10.1097/rli.0000000000000531] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES The aim of this study was to assess the utility of increased spatial resolution of magnetic resonance spectroscopic imaging (MRSI) at 7 T for the detection of neurochemical changes in multiple sclerosis (MS)-related brain lesions. MATERIALS AND METHODS This prospective, institutional review board-approved study was performed in 20 relapsing-remitting MS patients (9 women/11 men; mean age ± standard deviation, 30.8 ± 7.7 years) after receiving written informed consent. Metabolic patterns in MS lesions were compared at 3 different spatial resolutions of free induction decay MRSI with implemented parallel imaging acceleration: 2.2 × 2.2 × 8 mm; 3.4 × 3.4 × 8 mm; and 6.8 × 6.8 × 8 mm voxel volumes, that is, matrix sizes of 100 × 100, 64 × 64, and 32 × 32, respectively. The quality of data was assessed by signal-to-noise ratio and Cramér-Rao lower bounds. Statistical analysis was performed using Wilcoxon signed-rank tests with correction for multiple testing. RESULTS Seventy-seven T2-hyperintense MS lesions were investigated (median volume, 155.7 mm; range, 10.8-747.0 mm). The mean metabolic ratios in lesions differed significantly between the 3 MRSI resolutions (ie, 100 × 100 vs 64 × 64, 100 × 100 vs 32 × 32, and 64 × 64 vs 32 × 32; P < 0.001). With the ultra-high resolution (100 × 100), we obtained 40% to 80% higher mean metabolic ratios and 100% to 150% increase in maximum metabolic ratios in the MS lesions compared with the lowest resolution (32 × 32), while maintaining good spectral quality (signal-to-noise ratio >12, Cramér-Rao lower bounds <20%) and measurement time of 6 minutes. There were 83% of MS lesions that showed increased myo-inositol/N-acetylaspartate with the 100 × 100 resolution, but only 66% were distinguishable with the 64 × 64 resolution and 35% with the 32 × 32 resolution. CONCLUSIONS Ultra-high-resolution MRSI (~2 × 2 × 8 mm voxel volume) can detect metabolic alterations in MS, which cannot be recognized by conventional MRSI resolutions, within clinically acceptable time.
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Affiliation(s)
- Eva Heckova
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Gilbert J. Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michal Považan
- Russell H. Morgan Department of Radiology and Radiological Science, The John Hopkins University School of Medicine, Baltimore, Maryland, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
| | | | - Paulus S. Rommer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Petr Bednarik
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Fritz Leutmezer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
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40
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Oh J, Ontaneda D, Azevedo C, Klawiter EC, Absinta M, Arnold DL, Bakshi R, Calabresi PA, Crainiceanu C, Dewey B, Freeman L, Gauthier S, Henry R, Inglese M, Kolind S, Li DKB, Mainero C, Menon RS, Nair G, Narayanan S, Nelson F, Pelletier D, Rauscher A, Rooney W, Sati P, Schwartz D, Shinohara RT, Tagge I, Traboulsee A, Wang Y, Yoo Y, Yousry T, Zhang Y, Robert Z, Sicotte NL, Reich DS. Imaging outcome measures of neuroprotection and repair in MS: A consensus statement from NAIMS. Neurology 2019; 92:519-533. [PMID: 30787160 PMCID: PMC6511106 DOI: 10.1212/wnl.0000000000007099] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 11/29/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To summarize current and emerging imaging techniques that can be used to assess neuroprotection and repair in multiple sclerosis (MS), and to provide a consensus opinion on the potential utility of each technique in clinical trial settings. METHODS Clinicians and scientists with expertise in the use of MRI in MS convened in Toronto, Canada, in November 2016 at a North American Imaging in Multiple Sclerosis (NAIMS) Cooperative workshop meeting. The discussion was compiled into a manuscript and circulated to all NAIMS members in attendance. Edits and feedback were incorporated until all authors were in agreement. RESULTS A wide spectrum of imaging techniques and analysis methods in the context of specific study designs were discussed, with a focus on the utility and limitations of applying each technique to assess neuroprotection and repair. Techniques were discussed under specific themes, and included conventional imaging, magnetization transfer ratio, diffusion tensor imaging, susceptibility-weighted imaging, imaging cortical lesions, magnetic resonance spectroscopy, PET, advanced diffusion imaging, sodium imaging, multimodal techniques, imaging of special regions, statistical considerations, and study design. CONCLUSIONS Imaging biomarkers of neuroprotection and repair are an unmet need in MS. There are a number of promising techniques with different strengths and limitations, and selection of a specific technique will depend on a number of factors, notably the question the trial seeks to answer. Ongoing collaborative efforts will enable further refinement and improved methods to image the effect of novel therapeutic agents that exert benefit in MS predominately through neuroprotective and reparative mechanisms.
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Affiliation(s)
- Jiwon Oh
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA.
| | - Daniel Ontaneda
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Christina Azevedo
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Eric C Klawiter
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Martina Absinta
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Douglas L Arnold
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Rohit Bakshi
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Peter A Calabresi
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Ciprian Crainiceanu
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Blake Dewey
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Leorah Freeman
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Susan Gauthier
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Roland Henry
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Mathilde Inglese
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Shannon Kolind
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - David K B Li
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Caterina Mainero
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Ravi S Menon
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Govind Nair
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Sridar Narayanan
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Flavia Nelson
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel Pelletier
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Alexander Rauscher
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - William Rooney
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Pascal Sati
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel Schwartz
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Russell T Shinohara
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Ian Tagge
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Anthony Traboulsee
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Yi Wang
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Youngjin Yoo
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Tarek Yousry
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Yunyan Zhang
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Zivadinov Robert
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Nancy L Sicotte
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel S Reich
- From the Division of Neurology (J.O.), St. Michael's Hospital, University of Toronto, Canada; Department of Neurology (J.O., P.A.C., B.D., D.S.R.), Johns Hopkins University, Baltimore, MD; Mellen Center for Multiple Sclerosis (D.O.), Cleveland Clinic, OH; Department of Neurology (C.A., D.P.), University of Southern California, Los Angeles; Department of Neurology (E.C.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Translational Neuroradiology Unit (M.A., G.N., P.S., D.S.R.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Brain Imaging Centre (D.L.A., S.N.), Montreal Neurological Institute, McGill University, Canada; Departments of Neurology (R.B.) and Radiology (R.B.), Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Biostatistics (C.C.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Neurology (L.F.), University of Texas Health Science Center at Houston; Department of Neurology (S.G., Y.W.), Weill Cornell Medical College, Cornell University, Ithaca, NY; Department of Neurology (R.H.), University of California at San Francisco; Department of Neurology (M.I., A.T.), Mount Sinai Hospital, New York, NY; Division of Neurology, Department of Medicine (S.K., D.K.B.L.), Department of Radiology (S.K., D.K.B.L., A.R.), Department of Physics and Astronomy (S.K., A.R., A.T., Y.Y.), MS/MRI Research Group (S.K., D.K.B.L., A.T., Y.Y.), MRI Research Centre (S.K., D.K.B.L., A.R.), and Department of Pediatrics (A.R.), University of British Columbia, Vancouver, Canada; A. A. Martinos Center for Biomedical Imaging (C.M.), Department of Radiology, Massachusetts General Hospital, Boston; Centre for Functional and Metabolic Mapping (R.S.M.), Robarts Research Institute, Western University, London, CA; Department of Neurology (F.N.), University of Minnesota, Minneapolis; Advanced Imaging Research Center (W.R., D.S., I.T.), Oregon Health & Science University, Portland; Department of Biostatistics, Epidemiology, and Informatics (R.T.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Division of Neuroradiology and Neurophysics (T.Y.), University College London Institute of Neurology, UK; Department of Radiology (Y.Z.) and Department of Clinical Neurosciences and Hotchkiss Brain Institute (Y.Z.), University of Calgary, Canada; and Department of Neurology (N.L.S.), Cedars-Sinai Medical Center, Los Angeles, CA
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Laule C, Moore GW. Myelin water imaging to detect demyelination and remyelination and its validation in pathology. Brain Pathol 2018; 28:750-764. [PMID: 30375119 PMCID: PMC8028667 DOI: 10.1111/bpa.12645] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Accepted: 07/09/2018] [Indexed: 12/11/2022] Open
Abstract
Damage to myelin is a key feature of multiple sclerosis (MS) pathology. Magnetic resonance imaging (MRI) has revolutionized our ability to detect and monitor MS pathology in vivo. Proton density, T1 and T2 can provide qualitative contrast weightings that yield superb in vivo visualization of central nervous system tissue and have proved invaluable as diagnostic and patient management tools in MS. However, standard clinical MR methods are not specific to the types of tissue damage they visualize, and they cannot detect subtle abnormalities in tissue that appears otherwise normal on conventional MRIs. Myelin water imaging is an MR method that provides in vivo measurement of myelin. Histological validation work in both human brain and spinal cord tissue demonstrates a strong correlation between myelin water and staining for myelin, validating myelin water as a marker for myelin. Myelin water varies throughout the brain and spinal cord in healthy controls, and shows good intra- and inter-site reproducibility. MS plaques show variably decreased myelin water fraction, with older lesions demonstrating the greatest myelin loss. Longitudinal study of myelin water can provide insights into the dynamics of demyelination and remyelination in plaques. Normal appearing brain and spinal cord tissues show reduced myelin water, an abnormality which becomes progressively more evident over a timescale of years. Diffusely abnormal white matter, which is evident in 20%-25% of MS patients, also shows reduced myelin water both in vivo and postmortem, and appears to originate from a primary lipid abnormality with relative preservation of myelin proteins. Active research is ongoing in the quest to refine our ability to image myelin and its perturbations in MS and other disorders of the myelin sheath.
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Affiliation(s)
- Cornelia Laule
- RadiologyUniversity of British ColumbiaVancouverBCCanada
- Pathology & Laboratory MedicineUniversity of British ColumbiaVancouverBCCanada
- Physics & AstronomyUniversity of British ColumbiaVancouverBCCanada
- International Collaboration on Repair Discoveries (ICORD)University of British ColumbiaVancouverBCCanada
| | - G.R. Wayne Moore
- Pathology & Laboratory MedicineUniversity of British ColumbiaVancouverBCCanada
- International Collaboration on Repair Discoveries (ICORD)University of British ColumbiaVancouverBCCanada
- Medicine (Neurology)University of British ColumbiaVancouverBCCanada
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Jafari-Khouzani K, Paynabar K, Hajighasemi F, Rosen B. Effect of Region of Interest Size on the Repeatability of Quantitative Brain Imaging Biomarkers. IEEE Trans Biomed Eng 2018; 66:864-872. [PMID: 30059291 DOI: 10.1109/tbme.2018.2860928] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In the repeatability analysis, when the measurement is the mean value of a parametric map within a region of interest (ROI), the ROI size becomes important as by increasing the size, the measurement will have a smaller variance. This is important in decision-making in prospective clinical studies of brain when the ROI size is variable, e.g., in monitoring the effect of treatment on lesions by quantitative MRI, and in particular when the ROI is small, e.g., in the case of brain lesions in multiple sclerosis. Thus, methods to estimate repeatability measures for arbitrary sizes of ROI are desired. We propose a statistical model of the values of parametric map within the ROI and a method to approximate the model parameters, based on which we estimate a number of repeatability measures including repeatability coefficient, coefficient of variation, and intraclass correlation coefficient for an ROI with an arbitrary size. We also show how this gives an insight into related problems such as spatial smoothing in voxel-wise analysis. Experiments are conducted on simulated data as well as on scan-rescan brain MRI of healthy subjects. The main application of this study is the adjustment of the decision threshold based on the lesion size in treatment monitoring.
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Bouhrara M, Reiter DA, Maring MC, Bonny JM, Spencer RG. Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI. J Neuroimaging 2018; 28:640-649. [PMID: 29999204 DOI: 10.1111/jon.12537] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 05/31/2018] [Accepted: 06/19/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND AND PURPOSE Myelin water fraction (MWF) mapping permits direct visualization of myelination patterns in the developing brain and in pathology. MWF is conventionally measured through multiexponential T2 analysis which is very sensitive to noise, leading to inaccuracies in derived MWF estimates. Although noise reduction filters may be applied during postprocessing, conventional filtering can introduce bias and obscure small structures and edges. Advanced nonblurring filters, while effective, exhibit a high level of complexity and the requirement for supervised implementation for optimal performance. The purpose of this paper is to demonstrate the ability of the recently introduced nonlocal estimation of multispectral magnitudes (NESMA) filter to greatly improve the determination of MWF parameter estimates from gradient and spin echo (GRASE) imaging data. METHODS We evaluated the performance of the NESMA filter for MWF mapping from clinical GRASE imaging data of the human brain, and compared the results to those calculated from unfiltered images. Numerical and in vivo analyses of the brains of three subjects, representing different ages, were conducted. RESULTS Our results demonstrated the potential of the NESMA filter to permit high-quality in vivo MWF mapping. Indeed, NESMA permits substantial reduction of random variation in derived MWF estimates while preserving accuracy and detail. CONCLUSIONS In vivo estimation of MWF in the human brain from GRASE imaging data was markedly improved through use of the NESMA filter. The use of NESMA may contribute to the goal of high-quality MWF mapping in clinically feasible imaging times.
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Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
| | - David A Reiter
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
| | - Michael C Maring
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
| | | | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
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King EM, Sabatier MJ, Hoque M, Kesar TM, Backus D, Borich MR. Myelin status is associated with change in functional mobility following slope walking in people with multiple sclerosis. Mult Scler J Exp Transl Clin 2018; 4:2055217318773540. [PMID: 29780611 PMCID: PMC5954324 DOI: 10.1177/2055217318773540] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 03/17/2018] [Accepted: 03/19/2018] [Indexed: 01/07/2023] Open
Abstract
Background The level of myelin disruption in multiple sclerosis patients may impact the
capacity for training-induced neuroplasticity and the magnitude of
therapeutic response to rehabilitation interventions. Downslope walking has
been shown to increase functional mobility in individuals with multiple
sclerosis, but it is unclear if myelin status influences therapeutic
response. Objective The current study aimed to examine the relationship between baseline myelin
status and change in functional mobility after a walking intervention. Methods The Timed Up and Go test was used to measure functional mobility before and
after completion of a repeated, six-session slope walking intervention in 16
participants with relapsing–remitting multiple sclerosis. Multi-component
T2 relaxation imaging was used to index myelin water fraction
of overall water content in brain tissue compartments. Results Results demonstrated that the ratio of the myelin water fraction in lesion to
normal-appearing white matter (myelin water fraction ratio) significantly
predicted 31% of the variance in change in Timed Up and Go score after the
downslope walking intervention, where less myelin disruption was associated
with greater intervention response. Conclusions Myelin water content fraction ratio may offer a neural biomarker of myelin to
identify potential responders to interventions targeting functional
impairments in multiple sclerosis.
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Affiliation(s)
- E M King
- Neuroscience Graduate Program, Emory University, USA.,Division of Physical Therapy, Emory University School of Medicine, USA
| | - M J Sabatier
- Division of Physical Therapy, Emory University School of Medicine, USA
| | - M Hoque
- Division of Physical Therapy, Emory University School of Medicine, USA
| | - T M Kesar
- Division of Physical Therapy, Emory University School of Medicine, USA
| | | | - M R Borich
- Division of Physical Therapy, Emory University School of Medicine, USA
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Bouhrara M, Reiter DA, Bergeron CM, Zukley LM, Ferrucci L, Resnick SM, Spencer RG. Evidence of demyelination in mild cognitive impairment and dementia using a direct and specific magnetic resonance imaging measure of myelin content. Alzheimers Dement 2018; 14:998-1004. [PMID: 29679574 DOI: 10.1016/j.jalz.2018.03.007] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 02/22/2018] [Accepted: 03/01/2018] [Indexed: 12/30/2022]
Abstract
INTRODUCTION We investigated brain demyelination in aging, mild cognitive impairment (MCI), and dementia using a direct magnetic resonance imaging marker of myelin. METHODS Brains of young and old controls, and old subjects with MCI, Alzheimer's disease, or vascular dementia were scanned using our recently developed myelin water fraction (MWF) mapping technique, which provides greatly improved accuracy over previous comparable methods. Maps of MWF, a direct and specific myelin measure, and relaxation times and magnetization transfer ratio, indirect and nonspecific measures, were constructed. RESULTS MCI subjects showed decreased MWF compared with old controls. Demyelination was greater in Alzheimer's disease or vascular dementia. As expected, decreased MWF was accompanied by decreased magnetization transfer ratio and increased relaxation times. The young subjects showed greater myelin content than the old subjects. DISCUSSION We believe this to be the first demonstration of myelin loss in MCI, Alzheimer's disease, and vascular dementia using a method that provides a quantitative magnetic resonance imaging-based measure of myelin. Our findings add to the emerging evidence that myelination may represent an important biomarker for the pathology of MCI and dementia. This study supports the investigation of the role of myelination in MCI and dementia through use of this quantitative magnetic resonance imaging approach in clinical studies of disease progression, and relationship of functional status to myelination status. Furthermore, mapping MWF may permit myelin to serve as a therapeutic target in clinical trials.
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Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
| | - David A Reiter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Christopher M Bergeron
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Linda M Zukley
- Clinical Research Core, Office of the Scientific Director, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institutes of Health, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
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Yao Y, Nguyen TD, Pandya S, Zhang Y, Hurtado Rúa S, Kovanlikaya I, Kuceyeski A, Liu Z, Wang Y, Gauthier SA. Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions. AJNR Am J Neuroradiol 2017; 39:303-310. [PMID: 29242359 DOI: 10.3174/ajnr.a5482] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 10/13/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE A hyperintense rim on susceptibility in chronic MS lesions is consistent with iron deposition, and the purpose of this study was to quantify iron-related myelin damage within these lesions as compared with those without rim. MATERIALS AND METHODS Forty-six patients had 2 longitudinal quantitative susceptibility mapping with automatic zero reference scans with a mean interval of 28.9 ± 11.4 months. Myelin water fraction mapping by using fast acquisition with spiral trajectory and T2 prep was obtained at the second time point to measure myelin damage. Mixed-effects models were used to assess lesion quantitative susceptibility mapping and myelin water fraction values. RESULTS Quantitative susceptibility mapping scans were on average 6.8 parts per billion higher in 116 rim-positive lesions compared with 441 rim-negative lesions (P < .001). All rim-positive lesions retained a hyperintense rim over time, with increasing quantitative susceptibility mapping values of both the rim and core regions (P < .001). Quantitative susceptibility mapping scans and myelin water fraction in rim-positive lesions decreased from rim to core, which is consistent with rim iron deposition. Whole lesion myelin water fractions for rim-positive and rim-negative lesions were 0.055 ± 0.07 and 0.066 ± 0.04, respectively. In the mixed-effects model, rim-positive lesions had on average 0.01 lower myelin water fraction compared with rim-negative lesions (P < .001). The volume of the rim at the initial quantitative susceptibility mapping scan was negatively associated with follow-up myelin water fraction (P < .01). CONCLUSIONS Quantitative susceptibility mapping rim-positive lesions maintained a hyperintense rim, increased in susceptibility, and had more myelin damage compared with rim-negative lesions. Our results are consistent with the identification of chronic active MS lesions and may provide a target for therapeutic interventions to reduce myelin damage.
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Affiliation(s)
- Y Yao
- From the Department of Radiology (Y.Y., Y.Z.), Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China.,Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.)
| | - T D Nguyen
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.)
| | - S Pandya
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.)
| | - Y Zhang
- From the Department of Radiology (Y.Y., Y.Z.), Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China
| | - S Hurtado Rúa
- Department of Mathematics (S.H.R.), Cleveland State University, Cleveland, Ohio
| | - I Kovanlikaya
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.)
| | - A Kuceyeski
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.)
| | - Z Liu
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.).,Department of Biomedical Engineering (Z.L., Y.W.), Cornell University, Ithaca, New York
| | - Y Wang
- Departments of Radiology (Y.Y., T.D.N., S.P., I.K., A.K., Z.L., Y.W.).,Department of Biomedical Engineering (Z.L., Y.W.), Cornell University, Ithaca, New York
| | - S A Gauthier
- Neurology (S.A.G.), Weill Cornell Medicine, New York, New York
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Stangel M, Kuhlmann T, Matthews PM, Kilpatrick TJ. Achievements and obstacles of remyelinating therapies in multiple sclerosis. Nat Rev Neurol 2017; 13:742-754. [PMID: 29146953 DOI: 10.1038/nrneurol.2017.139] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Remyelination in the CNS is the natural process of damage repair in demyelinating diseases such as multiple sclerosis (MS). However, remyelination becomes inadequate in many people with MS, which results in axonal degeneration and clinical disability. Enhancement of remyelination is a logical therapeutic goal; nevertheless, all currently licensed therapies for MS are immunomodulatory and do not support remyelination directly. Several molecular pathways have been identified as potential therapeutic targets to induce remyelination, and some of these have now been assessed in proof-of-concept clinical trials. However, trial design faces several obstacles: optimal clinical or paraclinical outcome measures to assess remyelination remain ill-defined, and identification of the ideal timing of therapy is also a crucial issue. In addition, realistic expectations are needed concerning the probable benefits of such therapies. Nevertheless, approaches that enhance remyelination are likely to be protective for axons and so could prevent long-term neurodegeneration. Future MS treatment paradigms, therefore, are likely to comprise a combinatorial approach that involves both immunomodulatory and regenerative treatments.
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Affiliation(s)
- Martin Stangel
- Clinical Neuroimmunology and Neurochemistry, Department of Neurology, Hannover Medical School, Carl-Neuberg-Straße 1, 30625 Hannover, Germany
| | - Tanja Kuhlmann
- Institute of Neuropathology, University Hospital Münster, Pottkamp 2, 48149 Münster, Germany
| | - Paul M Matthews
- Division of Brain Sciences, Department of Medicine, and UK Dementia Research Institute, Imperial College London, Burlington Danes, Hammersmith Hospital, DuCane Road, London W12 0NN, UK
| | - Trevor J Kilpatrick
- Department of Anatomy and Neuroscience and Melbourne Neuroscience Institute, University of Melbourne, 30 Royal Parade, Parkville, Victoria 3010, Australia
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Mahajan KR, Ontaneda D. The Role of Advanced Magnetic Resonance Imaging Techniques in Multiple Sclerosis Clinical Trials. Neurotherapeutics 2017; 14:905-923. [PMID: 28770481 PMCID: PMC5722766 DOI: 10.1007/s13311-017-0561-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Magnetic resonance imaging has been crucial in the development of anti-inflammatory disease-modifying treatments. The current landscape of multiple sclerosis clinical trials is currently expanding to include testing not only of anti-inflammatory agents, but also neuroprotective, remyelinating, neuromodulating, and restorative therapies. This is especially true of therapies targeting progressive forms of the disease where neurodegeneration is a prominent feature. Imaging techniques of the brain and spinal cord have rapidly evolved in the last decade to permit in vivo characterization of tissue microstructural changes, connectivity, metabolic changes, neuronal loss, glial activity, and demyelination. Advanced magnetic resonance imaging techniques hold significant promise for accelerating the development of different treatment modalities targeting a variety of pathways in MS.
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Affiliation(s)
- Kedar R Mahajan
- Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, 9500 Euclid Avenue, U-10, Cleveland, OH, 44195, USA
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, 9500 Euclid Avenue, U-10, Cleveland, OH, 44195, USA.
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Nguyen TD, Spincemaille P, Gauthier SA, Wang Y. Rapid whole brain myelin water content mapping without an external water standard at 1.5 T. Magn Reson Imaging 2017; 39:82-88. [DOI: 10.1016/j.mri.2016.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 12/20/2016] [Accepted: 12/21/2016] [Indexed: 12/18/2022]
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Gupta A, Al-Dasuqi K, Xia F, Askin G, Zhao Y, Delgado D, Wang Y. The Use of Noncontrast Quantitative MRI to Detect Gadolinium-Enhancing Multiple Sclerosis Brain Lesions: A Systematic Review and Meta-Analysis. AJNR Am J Neuroradiol 2017; 38:1317-1322. [PMID: 28522663 DOI: 10.3174/ajnr.a5209] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 02/22/2017] [Indexed: 11/07/2022]
Abstract
BACKGROUND Concerns have arisen about the long-term health effects of repeat gadolinium injections in patients with multiple sclerosis and the incomplete characterization of MS lesion pathophysiology that results from relying on enhancement characteristics alone. PURPOSE Our aim was to perform a systematic review and meta-analysis analyzing whether noncontrast MR imaging biomarkers can distinguish enhancing and nonenhancing brain MS lesions. DATA SOURCES Our sources were Ovid MEDLINE, Ovid Embase, and the Cochrane data base from inception to August 2016. STUDY SELECTION We included 37 journal articles on 985 patients with MS who had MR imaging in which T1-weighted postcontrast sequences were compared with noncontrast sequences obtained during the same MR imaging examination by using ROI analysis of individual MS lesions. DATA ANALYSIS We performed random-effects meta-analyses comparing the standard mean difference of each MR imaging metric taken from enhancing-versus-nonenhancing lesions. DATA SYNTHESIS DTI-based fractional anisotropy values are significantly different between enhancing and nonenhancing lesions (P = .02), with enhancing lesions showing decreased fractional anisotropy compared with nonenhancing lesions. Of the other most frequently studied MR imaging biomarkers (mean diffusivity, magnetization transfer ratio, or ADC), none were significantly different (P values of 0.30, 0.47, and 0.19. respectively) between enhancing and nonenhancing lesions. Of the limited studies providing diagnostic accuracy measures, gradient-echo-based quantitative susceptibility mapping had the best performance in discriminating enhancing and nonenhancing MS lesions. LIMITATIONS MR imaging techniques and patient characteristics were variable across studies. Most studies did not provide diagnostic accuracy measures. All imaging metrics were not studied in all 37 studies. CONCLUSIONS Noncontrast MR imaging techniques, such as DTI-based FA, can assess MS lesion acuity without gadolinium.
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Affiliation(s)
- A Gupta
- From the Department of Radiology (A.G., K.A.-D., F.X., Y.W.) .,Clinical and Translational Neuroscience Unit (A.G.), Feil Family Brain and Mind Research Institute
| | - K Al-Dasuqi
- From the Department of Radiology (A.G., K.A.-D., F.X., Y.W.)
| | - F Xia
- From the Department of Radiology (A.G., K.A.-D., F.X., Y.W.).,Department of Biomedical Engineering (F.X., Y.W.), Cornell University, Ithaca, New York
| | - G Askin
- Department of Healthcare Policy and Research (G.A., Y.Z.)
| | - Y Zhao
- Department of Healthcare Policy and Research (G.A., Y.Z.)
| | - D Delgado
- Samuel J. Wood Library and C.V. Starr Biomedical Information Center (D.D.), Weill Cornell Medicine, New York, New York
| | - Y Wang
- From the Department of Radiology (A.G., K.A.-D., F.X., Y.W.).,Department of Biomedical Engineering (F.X., Y.W.), Cornell University, Ithaca, New York
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