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Seehafer S, Schmill LP, Aludin S, Huhndorf M, Larsen N, Jansen O, Stürner K, Peters S. Automatic lesion detection at Multiple Sclerosis patients - Comparison of 2D- and 3D-FLAIR-datasets. Mult Scler Relat Disord 2024; 88:105728. [PMID: 38909527 DOI: 10.1016/j.msard.2024.105728] [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: 12/18/2023] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 06/25/2024]
Abstract
BACKGROUND Multiple Sclerosis (MS) is a common autoimmune inflammatory disease of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows a sensitive assessment of the CNS and is established for diagnostic, prognostic and (therapy-) monitoring purposes. Especially lesion counting in T2- or Fluid Attenuated Inversion Recovery (FLAIR)-weighted images plays a decisive role in clinical routine. Software-packages allowing an automatic evaluation of image data are increasingly established aiming a faster and improved workflow. These programs allow e.g. the counting, spatial attribution and volumetry of MS-lesions in FLAIR-weighted images. Research has shown that 3D-FLAIR-sequences are superior to 2D-FLAIR-sequences in visual evaluation of lesion burden in MS. An influence on the automatic analysis is expectable but not yet systematically studied. This work will therefore investigate the influence of 2D- and 3D datasets on the results of an automatic assessment. MATERIAL AND METHODS In this prospective study, 80 Multiple Sclerosis patients underwent a clinically indicated routine MRI examination. The clinical routine protocol already including a 3D-FLAIR sequence was adapted by an additional 2D-FLAIR sequence also conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. To obtain a quantitative analysis for assessment of amount, dissemination and volume of the lesions, the acquired MR images were post-processed using the CE-certified Software mdbrain (mediaire, Berlin, Germany). The resulting data were statistically analysed using the paired t-test for normally distributed data and the Wilcoxon-signed-rank-test for not normally distributed data respectively. Demographic data and data such as the subtype, duration, severity and therapy of the disease were collected, pseudonymized and evaluated. RESULTS There is a significant difference concerning the total number and lesion volume with more lesions being detected (2D: 29.7, +/- 20.22 sd; 3D: 40.1 +/- 31.67 sd; p < 0.0001) but lower total volume (2D: 6.24 +/- 6.11 sd; 3D: 5.39 +/- 6.37 sd; p < 0.0001) when using the 3D- sequence. Especially significantly more small lesions in the unspecific white matter and infratentorial region were detected by using the 3D-FLAIR sequence (p < 0.0001) compared to the 2D-FLAIR image. Main reason for the lower total volume in the 3D-FLAIR sequence was the calculated volume for periventricular lesions which was significantly beneath the calculated volume from the 2D-FLAIR sequence (p < 0.0001). CONCLUSION Automatic lesion counting and volumetry is feasible with both 2D- and 3D-weightend FLAIR images. Still, it leads to partly significant differences even between two sequences that both are conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. This study contributes valuable insights into the impact of using different input data from the same patient for automated MS lesion evaluation.
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Affiliation(s)
- Svea Seehafer
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany.
| | - Lars-Patrick Schmill
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Schekeb Aludin
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Monika Huhndorf
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Naomi Larsen
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Olav Jansen
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Klarissa Stürner
- Department of Neurology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
| | - Sönke Peters
- Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), D-24105 Kiel, Germany
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Tillema JM. Imaging of Central Nervous System Demyelinating Disorders. Continuum (Minneap Minn) 2023; 29:292-323. [PMID: 36795881 DOI: 10.1212/con.0000000000001246] [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: 02/18/2023]
Abstract
OBJECTIVE This article summarizes neuroimaging findings in demyelinating disease, the most common being multiple sclerosis. Revisions to criteria and treatment options have been ongoing, and MRI plays a pivotal role in diagnosis and disease monitoring. The common antibody-mediated demyelinating disorders with their respective classic imaging features are reviewed, as well as the differential diagnostic considerations on imaging. LATEST DEVELOPMENTS The clinical criteria of demyelinating disease rely heavily on imaging with MRI. With novel antibody detection, the range of clinical demyelinating syndromes has expanded, most recently with myelin oligodendrocyte glycoprotein-IgG antibodies. Imaging has improved our understanding of the pathophysiology of multiple sclerosis and disease progression, and further research is underway. The importance of increased detection of pathology outside of the classic lesions will have an important role as therapeutic options are expanding. ESSENTIAL POINTS MRI has a crucial role in the diagnostic criteria and differentiation among common demyelinating disorders and syndromes. This article reviews the typical imaging features and clinical scenarios that assist in accurate diagnosis, differentiation between demyelinating diseases and other white matter diseases, the importance of standardized MRI protocols in clinical practice, and novel imaging techniques.
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Sundermann B, Billebaut B, Bauer J, Iacoban CG, Alykova O, Schülke C, Gerdes M, Kugel H, Neduvakkattu S, Bösenberg H, Mathys C. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions. ROFO-FORTSCHR RONTG 2022; 194:1195-1203. [PMID: 35798335 DOI: 10.1055/a-1800-8789] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
BACKGROUND Recently introduced MRI techniques facilitate accelerated examinations or increased resolution with the same duration. Further techniques offer homogeneous image quality in regions with anatomical transitions. The question arises whether and how these techniques can be adopted for routine diagnostic imaging. METHODS Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered. RESULTS AND CONCLUSIONS Compressed sensing and simultaneous multi-slice imaging are novel acceleration techniques with different yet complimentary applications. They do not suffer from classical signal-to-noise-ratio penalties. Combining 3 D and acceleration techniques facilitates new broader examination protocols, particularly for clinical brain imaging. In further regions of the nervous systems mainly specific applications appear to benefit from recent technological improvements. KEY POINTS · New acceleration techniques allow for faster or higher resolution examinations.. · New brain imaging approaches have evolved, including more universal examination protocols.. · Other regions of the nervous system are dominated by targeted applications of recently introduced MRI techniques.. CITATION FORMAT · Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8789.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany.,Research Center Neurosensory Science, University of Oldenburg, Germany.,Clinic for Radiology, University Hospital Münster, Germany
| | - Benoit Billebaut
- Clinic for Radiology, University Hospital Münster, Germany.,School for Radiologic Technologists, University Hospital Münster, Germany
| | - Jochen Bauer
- Clinic for Radiology, University Hospital Münster, Germany
| | - Catalin George Iacoban
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Olga Alykova
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | | | - Maike Gerdes
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Harald Kugel
- Clinic for Radiology, University Hospital Münster, Germany
| | | | - Holger Bösenberg
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, Medical Campus University of Oldenburg, Germany.,Research Center Neurosensory Science, University of Oldenburg, Germany.,Department of Diagnostic and Interventional Radiology, University of Düsseldorf, Germany
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Gaitán MI, Paday Formenti ME, Calandri I, Ysrraelit MC, Yañez P, Correale J. The central vein sign is present in most infratentorial multiple sclerosis plaques. Mult Scler Relat Disord 2022; 58:103484. [PMID: 35007822 DOI: 10.1016/j.msard.2021.103484] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/27/2021] [Accepted: 12/31/2021] [Indexed: 01/02/2023]
Abstract
BACKGROUND AND PURPOSE There is growing evidence supporting the presence of the central vein sign (CVS) in the supratentorial brain as an imaging biomarker for multiple sclerosis (MS) diagnosis. Recently, using optimized susceptibility-weighted angiography (SWAN-venule), we detected CVS in 86% of supratentorial white matter lesions (WMLs) in the clinical setting on images obtained in a 3T MRI scanner. Despite the relevance of the infratentorial compartment, CVS prevalence in infratentorial MS plaques has not been investigated in detail. Our objective was to determine the proportion of MS infratentorial lesions showing CVS positivity. MATERIALS AND METHODS We included subjects with MS and other brain diseases showing at least one infratentorial lesion larger than 3 mm on 3D-FLAIR. Patients were scanned in a 3T MRI scanner (GE Medical Systems, discovery-MR750), applying a comprehensive protocol including post-contrast 3D-FLAIR and SWAN-venule sequences. CVS presence was confirmed by two trained raters. RESULTS Thirty MRIs of subjects with MS were analyzed. One hundred and one infratentorial lesions were detected on FLAIR, and 86% were centered by a vein. Fifteen MRIs from the non-MS group were analyzed, 19 lesions were visible ion FLAIR and 16% were positive for the CVS. CONCLUSIONS SWAN-venule detects infratentorial lesions and highlights the central vein in MS plaques at 3T MRI. As occurs in the supratentorial brain, most infratentorial lesions are perivenular.
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Affiliation(s)
- María Inés Gaitán
- Department of Neurology, FLENI. Buenos Aires, Argentina; María Inés Gaitán, Montañeses 2325, ZC, 1428, Buenos Aires City, Argentina.
| | | | | | | | - Paulina Yañez
- Department of Radiology, FLENI. Buenos Aires, Argentina
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Nguyen TH, Vaussy A, Le Gaudu V, Aboab J, Espinoza S, Curajos I, Heron E, Habas C. The brainstem in multiple sclerosis: MR identification of tracts and nuclei damage. Insights Imaging 2021; 12:151. [PMID: 34674050 PMCID: PMC8531176 DOI: 10.1186/s13244-021-01101-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 08/23/2021] [Indexed: 01/04/2023] Open
Abstract
Objective To evaluate the 3D Fast Gray Acquisition T1 Inversion Recovery (FGATIR) sequence for MRI identification of brainstem tracts and nuclei damage in multiple sclerosis (MS) patients. Methods From april to december 2020, 10 healthy volunteers and 50 patients with remitted-relapsing MS (58% female, mean age 36) underwent MR imaging in the Neuro-imaging department of the C.H.N.O. des Quinze-Vingts, Paris, France. MRI was achieved on a 3 T system (MAGNETOM Skyra) using a 64-channel coil. 3D FGATIR sequence was first performed on healthy volunteers to classify macroscopically identifiable brainstem structures. Then, FGATIR was assessed in MS patients to locate brainstem lesions detected with Proton Density/T2w (PD/T2w) sequence. Results In healthy volunteers, FGATIR allowed a precise visualization of tracts and nuclei according to their myelin density. Including FGATIR in MR follow-up of MS patients helped to identify structures frequently involved in the inflammatory process. Most damaged tracts were the superior cerebellar peduncle and the transverse fibers of the pons. Most frequently affected nuclei were the vestibular nuclei, the trigeminal tract, the facial nerve and the solitary tract. Conclusion Combination of FGATIR and PD/T2w sequences opened prospects to define MS elective injury in brainstem tracts and nuclei, with particular lesion features suggesting variations of the inflammatory process within brainstem structures. In a further study, hypersignal quantification and microstructure information should be evaluated using relaxometry and diffusion tractography. Technical improvements would bring novel parameters to train an artificial neural network for accurate automated labeling of MS lesions within the brainstem.
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Affiliation(s)
- Thien Huong Nguyen
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France.
| | | | - Violette Le Gaudu
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Jennifer Aboab
- Department of Internal Medicine, C.H.N.O. des Quinze-Vingts, Paris, France
| | - Sophie Espinoza
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Irina Curajos
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Emmanuel Heron
- Department of Internal Medicine, C.H.N.O. des Quinze-Vingts, Paris, France
| | - Christophe Habas
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
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Ngamsombat C, Gonçalves Filho ALM, Longo MGF, Cauley SF, Setsompop K, Kirsch JE, Tian Q, Fan Q, Polak D, Liu W, Lo WC, Gilberto González R, Schaefer PW, Rapalino O, Conklin J, Huang SY. Evaluation of Ultrafast Wave-Controlled Aliasing in Parallel Imaging 3D-FLAIR in the Visualization and Volumetric Estimation of Cerebral White Matter Lesions. AJNR Am J Neuroradiol 2021; 42:1584-1590. [PMID: 34244127 DOI: 10.3174/ajnr.a7191] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 03/29/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND PURPOSE Our aim was to evaluate an ultrafast 3D-FLAIR sequence using Wave-controlled aliasing in parallel imaging encoding (Wave-FLAIR) compared with standard 3D-FLAIR in the visualization and volumetric estimation of cerebral white matter lesions in a clinical setting. MATERIALS AND METHODS Forty-two consecutive patients underwent 3T brain MR imaging, including standard 3D-FLAIR (acceleration factor = 2, scan time = 7 minutes 50 seconds) and resolution-matched ultrafast Wave-FLAIR sequences (acceleration factor = 6, scan time = 2 minutes 45 seconds for the 20-channel coil; acceleration factor = 9, scan time = 1 minute 50 seconds for the 32-channel coil) as part of clinical evaluation for demyelinating disease. Automated segmentation of cerebral white matter lesions was performed using the Lesion Segmentation Tool in SPM. Student t tests, intraclass correlation coefficients, relative lesion volume difference, and Dice similarity coefficients were used to compare volumetric measurements among sequences. Two blinded neuroradiologists evaluated the visualization of white matter lesions, artifacts, and overall diagnostic quality using a predefined 5-point scale. RESULTS Standard and Wave-FLAIR sequences showed excellent agreement of lesion volumes with an intraclass correlation coefficient of 0.99 and mean Dice similarity coefficient of 0.97 (SD, 0.05) (range, 0.84-0.99). Wave-FLAIR was noninferior to standard FLAIR for visualization of lesions and motion. The diagnostic quality for Wave-FLAIR was slightly greater than for standard FLAIR for infratentorial lesions (P < .001), and there were fewer pulsation artifacts on Wave-FLAIR compared with standard FLAIR (P < .001). CONCLUSIONS Ultrafast Wave-FLAIR provides superior visualization of infratentorial lesions while preserving overall diagnostic quality and yields white matter lesion volumes comparable with those estimated using standard FLAIR. The availability of ultrafast Wave-FLAIR may facilitate the greater use of 3D-FLAIR sequences in the evaluation of patients with suspected demyelinating disease.
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Affiliation(s)
- C Ngamsombat
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Department of Radiology (C.N.), Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand
| | - A L M Gonçalves Filho
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - M G F Longo
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - S F Cauley
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - K Setsompop
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - J E Kirsch
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - Q Tian
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - Q Fan
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - D Polak
- Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Department of Physics and Astronomy (D.P.), Heidelberg University, Heidelberg, Germany.,Siemens Healthcare GmbH, (D.P., W.-C.L.), Erlangen, Germany
| | - W Liu
- Siemens Shenzhen Magnetic Resonance Ltd (W.L.), Shenzhen, China
| | - W-C Lo
- Siemens Healthcare GmbH, (D.P., W.-C.L.), Erlangen, Germany
| | - R Gilberto González
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - P W Schaefer
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - O Rapalino
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - J Conklin
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.).,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts
| | - S Y Huang
- From the Department of (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.) .,Athinoula A. Martinos Center for Biomedical Imaging (C.N., A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F, D.P., J.C., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (A.L.M.G.F., M.G.F.L., S.F.C., K.S., J.E.K., Q.T., Q.F., R.G.G., P.W.S., O.R., J.C., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
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Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, Fazekas F, Filippi M, Frederiksen J, Gasperini C, Hacohen Y, Kappos L, Li DKB, Mankad K, Montalban X, Newsome SD, Oh J, Palace J, Rocca MA, Sastre-Garriga J, Tintoré M, Traboulsee A, Vrenken H, Yousry T, Barkhof F, Rovira À. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 2021; 20:653-670. [PMID: 34139157 DOI: 10.1016/s1474-4422(21)00095-8] [Citation(s) in RCA: 307] [Impact Index Per Article: 102.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 02/15/2021] [Accepted: 03/12/2021] [Indexed: 12/11/2022]
Abstract
The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.
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Affiliation(s)
- Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Olga Ciccarelli
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Brenda Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicola de Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria; Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jette Frederiksen
- Department of Neurology, Rigshospitalet Glostrup, University Hospital of Copenhagen, Glostrup, Denmark
| | - Claudio Gasperini
- Department of Neurology, San Camillo-Forlanini Hospital, Roma, Italy
| | - Yael Hacohen
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; Department of Paediatric Neurology, Great Ormond Street Hospital for Children, London, UK
| | - Ludwig Kappos
- Department of Neurology and Research Center for Clinical Neuroimmunology and Neuroscience, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Kshitij Mankad
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain; Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jiwon Oh
- Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anthony Traboulsee
- Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, London, UK; Neuroradiological Academic Unit, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands; Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.
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Almutairi AD, Hassan HA, Suppiah S, Alomair OI, Alshoaibi A, Almutairi H, Mahmud R. Lesion load assessment among multiple sclerosis patient using DIR, FLAIR, and T2WI sequences. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [DOI: 10.1186/s43055-020-00312-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Magnetic resonance imaging (MRI) is one of the diagnostic imaging modalities employing in lesion detection in neurological disorders such as multiple sclerosis (MS). Advances in MRI techniques such as double inversion recovery (DIR) made it more sensitive to distinguish lesions in the brain. To investigate the lesion load on different anatomical regions of the brain with MS using DIR, fluid attenuated inversion recovery (FLAIR) and T2-weighted imaging (T2WI) sequences. A total of 97 MS patients were included in our retrospective study, confirmed by neurologist. The patients were randomly selected from the major hospital in Saudi Arabia. All images were obtained using 3T Scanner (Siemens Skyra). The images from the DIR, FLAIR, and T2WI sequence were compared on axial planes with identical anatomic position and the number of lesions was assigned to their anatomical region.
Results
Comparing the lesion load measurement at various brain anatomical regions showed a significant difference among those three methods (p < 0.05).
Conclusion
DIR is a valuable MRI sequence for better delineation, greater contrast measurements and the increasing total number of MS lesions in MRI, compared with FLAIR, and T2WI and DIR revealed more intracortical lesions as well; therefore, in MS patients, it is recommended to add DIR sequence in daily routine imaging sequences.
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Gabr RE, Lincoln JA, Kamali A, Arevalo O, Zhang X, Sun X, Hasan KM, Narayana PA. Sensitive Detection of Infratentorial and Upper Cervical Cord Lesions in Multiple Sclerosis with Combined 3D FLAIR and T2-Weighted (FLAIR3) Imaging. AJNR Am J Neuroradiol 2020; 41:2062-2067. [PMID: 33033051 DOI: 10.3174/ajnr.a6797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 07/22/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Infratentorial and spinal cord lesions are important for diagnosing and monitoring multiple sclerosis, but they are difficult to detect on conventional MR imaging. We sought to improve the detection of infratentorial and upper cervical cord lesions using composite FLAIR3 images. MATERIALS AND METHODS 3D T2-weighted FLAIR and 3D T2-weighted images were acquired in 30 patients with MS and combined using the FLAIR3 formula. FLAIR3 was assessed against 3D T2-FLAIR by comparing the number of infratentorial and upper cervical cord lesions per subject using the Wilcoxon signed rank test. Intrarater and interrater reliability was evaluated using the intraclass correlation coefficient. The number of patients with and without ≥1 visible infratentorial/spinal cord lesion on 3D T2-FLAIR versus FLAIR3 was calculated to assess the potential impact on the revised MS diagnostic criteria. RESULTS Compared with 3D T2-FLAIR, FLAIR3 detected significantly more infratentorial (mean, 4.6 ± 3.6 versus 2.0 ± 1.8, P < .001) and cervical cord (mean, 1.58 ± 0.94 versus 0.46 ± 0.45, P < .001) lesions per subject. FLAIR3 demonstrated significantly improved interrater reliability (intraclass correlation coefficient = 0.77 [95% CI, 0.63-0.87] versus 0.60 [95% CI, 0.40-0.76] with 3D T2-FLAIR, P = .019) and a tendency toward a higher intrarater reliability (0.86 [95% CI, 0.73-0.93] versus 0.79 [95% CI, 0.61-0.89], P = .23). In our cohort, 20%-30% (47%-67%) of the subjects with MS had ≥ 1 infratentorial (cervical cord) lesion visible only on FLAIR3. CONCLUSIONS FLAIR3 provides higher sensitivity than T2-FLAIR for the detection of MS lesions in infratentorial brain parenchyma and the upper cervical cord.
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Affiliation(s)
- R E Gabr
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
| | | | - A Kamali
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
| | - O Arevalo
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
| | - X Zhang
- Center for Clinical and Translational Sciences, (X.Z.), University of Texas Health Science Center at Houston, Houston, Texas
| | - X Sun
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
| | - K M Hasan
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
| | - P A Narayana
- From the Departments of Diagnostic and Interventional Imaging (R.E.G., A.K., O.A., X.S., K.M.H., PA.N.)
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10
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Filippi M, Preziosa P, Banwell BL, Barkhof F, Ciccarelli O, De Stefano N, Geurts JJG, Paul F, Reich DS, Toosy AT, Traboulsee A, Wattjes MP, Yousry TA, Gass A, Lubetzki C, Weinshenker BG, Rocca MA. Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 2020; 142:1858-1875. [PMID: 31209474 PMCID: PMC6598631 DOI: 10.1093/brain/awz144] [Citation(s) in RCA: 288] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/19/2022] Open
Abstract
MRI has improved the diagnostic work-up of multiple sclerosis, but inappropriate image interpretation and application of MRI diagnostic criteria contribute to misdiagnosis. Some diseases, now recognized as conditions distinct from multiple sclerosis, may satisfy the MRI criteria for multiple sclerosis (e.g. neuromyelitis optica spectrum disorders, Susac syndrome), thus making the diagnosis of multiple sclerosis more challenging, especially if biomarker testing (such as serum anti-AQP4 antibodies) is not informative. Improvements in MRI technology contribute and promise to better define the typical features of multiple sclerosis lesions (e.g. juxtacortical and periventricular location, cortical involvement). Greater understanding of some key aspects of multiple sclerosis pathobiology has allowed the identification of characteristics more specific to multiple sclerosis (e.g. central vein sign, subpial demyelination and lesional rims), which are not included in the current multiple sclerosis diagnostic criteria. In this review, we provide the clinicians and researchers with a practical guide to enhance the proper recognition of multiple sclerosis lesions, including a thorough definition and illustration of typical MRI features, as well as a discussion of red flags suggestive of alternative diagnoses. We also discuss the possible place of emerging qualitative features of lesions which may become important in the near future.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Brenda L Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK.,National Institute for Health Research University College London Hospitals Biomedical Research Center, National Institute for Health Research, London, UK
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité -Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ahmed T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, UK
| | - Anthony Traboulsee
- MS/MRI Research Group, Djavad Mowafaghian Centre for Brain Health, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada.,Faculty of Medicine, Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mike P Wattjes
- Department of Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Tarek A Yousry
- Division of Neuroradiology and Neurophysics, UCL Institute of Neurology, London, UK.,Lysholm Department of Neuroradiology, London, UK
| | - Achim Gass
- Department of Neurology, Universitätsmedizin Mannheim, University of Heidelberg, Mannheim, Germany
| | - Catherine Lubetzki
- Sorbonne University, AP-HP Pitié-Salpétriére Hospital, Department of Neurology, 75013 Paris, France
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
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11
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Hu XY, Rajendran L, Lapointe E, Tam R, Li D, Traboulsee A, Rauscher A. Three-dimensional MRI sequences in MS diagnosis and research. Mult Scler 2019; 25:1700-1709. [DOI: 10.1177/1352458519848100] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).
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Affiliation(s)
- Xun Yang Hu
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Luckshi Rajendran
- Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Emmanuelle Lapointe
- Department of Medicine, Division of Neurology, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Roger Tam
- Department of Radiology, School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - David Li
- Department of Radiology, UBC Hospital, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Division of Neurology, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Alexander Rauscher
- Department of Radiology, The University of British Columbia, Vancouver, BC, Canada
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