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Silvestri G, Roccatagliata L, Tazza F, Schiavi S, Coccia A, Bandettini Di Poggio M, Cellerino M, Signori A, Finocchi C, Uccelli A, Inglese M, Lapucci C. The "central vein sign" to differentiate multiple sclerosis from migraine. Headache 2025; 65:558-567. [PMID: 39834045 DOI: 10.1111/head.14902] [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: 06/19/2024] [Revised: 11/21/2024] [Accepted: 11/25/2024] [Indexed: 01/22/2025]
Abstract
OBJECTIVE To investigate, in two cohorts including patients with multiple sclerosis (MS) and migraine, (i) the prevalence of the "central vein sign" (CVS), (ii) the spatial distribution of positive CVS (CVS+) lesions, (iii) the threshold of CVS+ lesions able to distinguish MS from migraine with high sensitivity and specificity. METHODS A total of 70 patients with MS/clinically isolated syndrome and 50 age- and sex-matched patients with migraine underwent a 3-T magnetic resonance imaging scan. The CVS was evaluated according to current guidelines, excluding eight patients with migraine who did not show white matter (WM) lesions. A receiver operating characteristic curve analysis was performed to identify the best threshold in terms of proportion of CVS+ lesions and the absolute number of CVS+ lesions able to differentiate MS from migraine. RESULTS Lesion volume was different between CVS+ and CVS negative lesions (median 1043 vs. 176.5 mm3 for MS cohort; median 35.1 vs. 52.2 mm3 for migraine cohort; p < 0.001 for all). A higher proportion of CVS+ lesions was associated with a higher probability of being diagnosed as MS (adjusted odds ratio 1.09, 95% confidence interval [CI] 1.04-1.14; p < 0.001). CVS+ lesion volume and number were higher in MS with respect to migraine, both considering the whole brain and its subregions (p < 0.001). The proportion of CVS+ lesions in juxtacortical and infratentorial areas was higher in MS than in migraine (p = 0.015 and p = 0.034, respectively). The best CVS proportion-based threshold able to differentiate MS from migraine was 35.0% (sensitivity 97.1%, specificity 85.7%) with an area under the curve of 0.95 (95% CI 0.90-1.00). The "select 6" rule seemed to be preferable in terms of specificity with respect to the "select 3" rule. CONCLUSIONS A CVS proportion-based threshold of 35.0% is capable of distinguishing MS from migraine with high sensitivity and specificity. The "select 6" algorithm may be useful in the clinical setting.
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Affiliation(s)
| | - Luca Roccatagliata
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
- Department of Neuroradiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Francesco Tazza
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Alberto Coccia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | - Maria Cellerino
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Alessio Signori
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | | | - Antonio Uccelli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
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Durand-Dubief F, Shor N, Audoin B, Bourre B, Cohen M, Kremer S, Maillart E, Papeix C, Ruet A, Savatovsky J, Tourdias T, Ayrignac X, Ciron J, Collongues N, Laplaud D, Michel L, Deschamps R, Thouvenot E, Zephir H, Marignier R, Cotton F. MRI management of NMOSD and MOGAD: Proposals from the French Expert Group NOMADMUS. J Neuroradiol 2025; 52:101235. [PMID: 39626832 DOI: 10.1016/j.neurad.2024.101235] [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: 06/16/2024] [Revised: 11/23/2024] [Accepted: 11/23/2024] [Indexed: 12/15/2024]
Abstract
BACKGROUND Currently, there are no available recommendations or guidelines on how to perform MRI monitoring in the management of neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). The issue is to determine a valuable MRI monitoring protocol to be applied in the management of NMOSD and MOGAD, as previously proposed for the monitoring of multiple sclerosis. OBJECTIVES The objectives of this work are to establish proposals for a standardized and feasible MRI acquisition protocol, and to propose control time points for systematic MRI monitoring in the management of NMOSD and MOGAD. METHODS A steering committee composed of 7 neurologists and 5 neuroradiologists, experts in NMOSD and MOGAD from the French group NOMADMUS, defined 8 proposals based on their expertise and a review from the literature. These proposals were then submitted to a Rating Group composed of French NMOSD / MOGAD experts. RESULTS In the management of NMOSD and MOGAD, a consensus has been reached to perform systematic MRI of the brain, optic nerve and spinal cord, including cauda equina nerve roots, at the time of diagnosis, both without and after gadolinium administration. Moreover, it has been agreed to perform a systematic MRI scan 6 months after diagnosis, focusing on the area of interest, both without and after gadolinium administration. For long-term follow-up of NMOSD and MOGAD, and in the absence of clinical activity, it has been agreed to perform gadolinium-free MRI of the brain (+/- optic nerves) and spinal cord, every 36 months. Ideally, these MRI scans should be performed on the same MRI system, preferably a 3T MRI system for brain and optic nerve MRI, and at least a 1.5T MRI system for spinal cord MRI. CONCLUSIONS This expert consensus approach provides physicians with proposals for the MRI management of NMOSD and MOGAD.
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Affiliation(s)
- Françoise Durand-Dubief
- Service de Sclérose en Plaques, Pathologies de la substance blanche et Neuroinflammation, Hôpital Neurologique, Hospices Civils de Lyon, Bron, France; Creatis LRMN, CNRS UMR 5220, Université Claude Bernard Lyon 1, INSERM U630, Lyon, France.
| | - Natalia Shor
- Service de Neuroradiologie, Hôpital de la Pitie-Salpetrière, AP-HP, Paris, France
| | - Bertrand Audoin
- Service de Neurologie, Maladies Inflammatoires du Cerveau et de la Moelle Épinière (MICeME), Hôpital de la Timone, AP-HM, Marseille CEDEX 5, France
| | - Bertrand Bourre
- Service de Neurologie, Centre Hospitalier Universitaire Rouen, Rouen F-76000, France
| | - Mickael Cohen
- CRC-SEP, Neurologie Pasteur 2, CHU de Nice, Nice, France; Université Cote d'Azur, UMR2CA (URRIS), Nice, France
| | - Stéphane Kremer
- Service d'imagerie 2, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France; Engineering Science, Computer Science and Imaging Laboratory (ICube), Integrative Multimodal Imaging in Healthcare, UMR 7357, University of Strasbourg-CNRS, Strasbourg, France
| | - Elisabeth Maillart
- Service de Neurologie, Hôpital de la Pitie-Salpetrière, Centre de Références des Maladies Inflammatoires Rares du Cerveau Et de la Moelle épinière, AP-HP, Paris, France
| | - Caroline Papeix
- Service de Neurologie, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | - Aurélie Ruet
- Service de Neurologie et Maladies inflammatoires du Système nerveux Central, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France; Université de Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux, France
| | - Julien Savatovsky
- Service d'Imagerie Médicale, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | - Thomas Tourdias
- Neuroimagerie Diagnostique et Thérapeutique, Centre Hospitalier Universitaire de Bordeaux, Bordeaux F-33000, France; Université Bordeaux, INSERM, Neurocentre Magendie, U1215, Bordeaux F-3300, France
| | - Xavier Ayrignac
- Université de Montpellier, Montpellier, France; Département de Neurologie, CRC-SEP, CRMR LEUKOFRANCE, Hôpital Gui de Chauliac, Centre Hospitalier Universitaire de Montpellier, France
| | - Jonathan Ciron
- Service de Neurologie, CRC-SEP, Centre Hospitalier Universitaire de Toulouse, France
| | - Nicolas Collongues
- Service de Neurologie, Centre Hospitalier Universitaire de Strasbourg, Strasbourg, France; Center for Clinical Investigation, INSERM U1434, Strasbourg, France; Department of Pharmacology, Addictology, Toxicology, and Therapeutics, Strasbourg University, Strasbourg, France
| | - David Laplaud
- Center for Research in Transplantation and Translational Immunology, Nantes Université, INSERM, CHU de Nantes, UMR 1064, CIC INSERM 1413, Service de Neurologie, Nantes F-44000, France
| | - Laure Michel
- Service de Neurologie, Centre Hospitalier Universitaire de Rennes, Rennes, France; Clinical Neuroscience Centre, University Hospital, Rennes University, CIC_P1414 INSERM, Rennes, France
| | - Romain Deschamps
- Service de Neurologie, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | - Eric Thouvenot
- Service de Neurologie, Centre Hospitalier Universitaire de Nîmes, Nîmes, France; Institut de Génomique Fonctionnelle, Université Montpellier, CNRS INSERM, Montpellier, France
| | - Hélène Zephir
- CCMR MIRCEM, Université de Lille INSERM U1172, CHU de Lille, Lille, France; CCMR MIRCEM, CHU de Lille, Lille, France
| | - Romain Marignier
- Service de Sclérose en Plaques, Pathologies de la substance blanche et Neuroinflammation, Hôpital Neurologique, Hospices Civils de Lyon, Bron, France
| | - François Cotton
- Service de Radiologie, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre-Bénite, France; Creatis LRMN, CNRS UMR 5220, Université Claude Bernard Lyon 1, INSERM U630, Lyon, France
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Mirmosayyeb O, Yazdan Panah M, Moases Ghaffary E, Vaheb S, Ghoshouni H, Shaygannejad V, Pinter NK. Magnetic resonance imaging-based biomarkers of multiple sclerosis and neuromyelitis optica spectrum disorder: a systematic review and meta-analysis. J Neurol 2024; 272:77. [PMID: 39680165 DOI: 10.1007/s00415-024-12827-x] [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: 09/29/2024] [Accepted: 11/19/2024] [Indexed: 12/17/2024]
Abstract
BACKGROUND/OBJECTIVE Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are neuroinflammatory conditions with overlapping clinical and imaging features. Distinguishing between these diseases is crucial for appropriate diagnosis and management. Magnetic resonance imaging (MRI) may have the potential to differentiate these disorders. Nonetheless, studies exhibit inconsistencies regarding which MRI measurements most effectively distinguish between these disorders. Hence, this review aimed to evaluate the differences in MRI volumetry between people with MS (PwMS) and people with NMOSD (PwNMOSD). METHODS A systematic search was conducted across PubMed/MEDLINE, Embase, Scopus, and Web of Science up to May 12, 2024, to identify studies assessing conventional and volumetric MRI in PwMS and PwNMOSD. The standard mean difference (SMD) of MRI measurements and its 95% confidence interval (CI) were estimated using R version 4.4.0 with a random-effects model. RESULTS Forty-eight original studies that assessed conventional MRI measurements in 2592 PwMS and 1979 PwNMOSD were included. The meta-analysis revealed that PwMS had significantly higher T2 lesion volume (SMD = 1.51, 95% CI: 0.53 to 2.48, p = 0.002) and T1 lesion count (SMD = 1.08, 95% CI: 0.56 to 1.6, p < 0.001) than PwNMOSD. PwMS also exhibited significantly reduced thalamic volume (SMD = -1.26, 95% CI: -1.8 to -0.73, p < 0.001) and grey matter volume (GMV) (SMD = -0.65, 95% CI: -0.92 to -0.37, p < 0.001). Other MRI volumetry, such as the brain and putamen volumes, showed more pronounced atrophy in PwMS. CONCLUSION Significant differences in MRI volumetry between MS and NMOSD highlight the potential of MRI as a critical diagnostic tool. These findings emphasize the need for standardized MRI protocols and advanced imaging techniques to enhance diagnostic accuracy and clinical management of these conditions.
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Affiliation(s)
- Omid Mirmosayyeb
- Department of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St., Buffalo, NY, 14203, USA.
| | - Mohammad Yazdan Panah
- Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | | | - Saeed Vaheb
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hamed Ghoshouni
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Vahid Shaygannejad
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Nandor K Pinter
- Department of Radiology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
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Toljan K, Daboul L, Raza P, Martin ML, Cao Q, O’Donnell CM, Rodrigues P, Derbyshire J, Azevedo CJ, Bar-Or A, Caverzasi E, Calabresi PA, Cree BA, Freeman L, Henry RG, Longbrake EE, Oh J, Papinutto N, Pelletier D, Samudralwar RD, Schindler MK, Sotirchos ES, Sicotte NL, Solomon AJ, Shinohara RT, Reich DS, Sati P, Ontaneda D. Diagnostic performance of central vein sign versus oligoclonal bands for multiple sclerosis. Mult Scler 2024; 30:1268-1277. [PMID: 39234802 PMCID: PMC11421977 DOI: 10.1177/13524585241271988] [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] [Indexed: 09/06/2024]
Abstract
BACKGROUND Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy. OBJECTIVES The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS. METHODS Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months. RESULTS Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status. DISCUSSION Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB.
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Affiliation(s)
- Karlo Toljan
- Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Lynn Daboul
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Cleveland Clinic Lerner College of Medicine, Cleveland, OH, United States
- Department of Neurology, Brigham and Women’s Hospital, MA, United States
| | - Praneeta Raza
- Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Melissa L. Martin
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Quy Cao
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Carly M. O’Donnell
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | | | - John Derbyshire
- Functional MRI Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Christina J. Azevedo
- Department of Neurology, University of Southern California, Los Angeles, CA, United States
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Eduardo Caverzasi
- Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, CA, United States
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Peter A. Calabresi
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Bruce A.C. Cree
- Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, CA, United States
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Roland G. Henry
- Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, CA, United States
| | - Erin E Longbrake
- Department of Neurology, Yale University, New Haven, CT, United States
| | - Jiwon Oh
- Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, Canada
| | - Nico Papinutto
- Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, CA, United States
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, CA, United States
| | - Rohini D. Samudralwar
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Department of Neurology, University of Texas Health Science Center at Houston, TX, United States
| | - Matthew K. Schindler
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Elias S. Sotirchos
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Nancy L. Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Andrew J. Solomon
- Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, VT, United States
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Penn Statistics in Imaging and Visualization Endeavor, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
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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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Filippi M, Preziosa P, Margoni M, Rocca MA. Diagnostic Criteria for Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorders, and Myelin Oligodendrocyte Glycoprotein-immunoglobulin G-associated Disease. Neuroimaging Clin N Am 2024; 34:293-316. [PMID: 38942518 DOI: 10.1016/j.nic.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
The diagnostic workup of multiple sclerosis (MS) has evolved considerably. The 2017 revision of the McDonald criteria shows high sensitivity and accuracy in predicting clinically definite MS in patients with a typical clinically isolated syndrome and allows an earlier MS diagnosis. Neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein-immunoglobulin G-associated disease (MOGAD) are recognized as separate conditions from MS, with specific diagnostic criteria. New MR imaging markers may improve diagnostic specificity for these conditions, thus reducing the risk of misdiagnosis. This study summarizes the most recent updates regarding the application of MR imaging for the diagnosis of MS, NMOSD, and MOGAD.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Paolo Preziosa
- Neuroimaging Research Unit, 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
| | - Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, 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
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7
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Rimkus CDM, Otsuka FS, Nunes DM, Chaim KT, Otaduy MCG. Central Vein Sign and Paramagnetic Rim Lesions: Susceptibility Changes in Brain Tissues and Their Implications for the Study of Multiple Sclerosis Pathology. Diagnostics (Basel) 2024; 14:1362. [PMID: 39001252 PMCID: PMC11240827 DOI: 10.3390/diagnostics14131362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 05/29/2024] [Accepted: 06/03/2024] [Indexed: 07/16/2024] Open
Abstract
Multiple sclerosis (MS) is the most common acquired inflammatory and demyelinating disease in adults. The conventional diagnostic of MS and the follow-up of inflammatory activity is based on the detection of hyperintense foci in T2 and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and lesions with brain-blood barrier (BBB) disruption in the central nervous system (CNS) parenchyma. However, T2/FLAIR hyperintense lesions are not specific to MS and the MS pathology and inflammatory processes go far beyond focal lesions and can be independent of BBB disruption. MRI techniques based on the magnetic susceptibility properties of the tissue, such as T2*, susceptibility-weighted images (SWI), and quantitative susceptibility mapping (QSM) offer tools for advanced MS diagnostic, follow-up, and the assessment of more detailed features of MS dynamic pathology. Susceptibility-weighted techniques are sensitive to the paramagnetic components of biological tissues, such as deoxyhemoglobin. This capability enables the visualization of brain parenchymal veins. Consequently, it presents an opportunity to identify veins within the core of multiple sclerosis (MS) lesions, thereby affirming their venocentric characteristics. This advancement significantly enhances the accuracy of the differential diagnostic process. Another important paramagnetic component in biological tissues is iron. In MS, the dynamic trafficking of iron between different cells, such as oligodendrocytes, astrocytes, and microglia, enables the study of different stages of demyelination and remyelination. Furthermore, the accumulation of iron in activated microglia serves as an indicator of latent inflammatory activity in chronic MS lesions, termed paramagnetic rim lesions (PRLs). PRLs have been correlated with disease progression and degenerative processes, underscoring their significance in MS pathology. This review will elucidate the underlying physical principles of magnetic susceptibility and their implications for the formation and interpretation of T2*, SWI, and QSM sequences. Additionally, it will explore their applications in multiple sclerosis (MS), particularly in detecting the central vein sign (CVS) and PRLs, and assessing iron metabolism. Furthermore, the review will discuss their role in advancing early and precise MS diagnosis and prognostic evaluation, as well as their utility in studying chronic active inflammation and degenerative processes.
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Affiliation(s)
- Carolina de Medeiros Rimkus
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HV Amsterdam, The Netherlands
- Instituto D'Or de Ensino e Pesquisa (IDOR), Sao Paulo 01401-002, SP, Brazil
| | - Fábio Seiji Otsuka
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
| | - Douglas Mendes Nunes
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Grupo Fleury, Sao Paulo 04701-200, SP, Brazil
| | - Khallil Taverna Chaim
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
| | - Maria Concepción Garcia Otaduy
- Department of Radiology and Oncology, Hospital das Clínicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Sao Paulo 05403-010, SP, Brazil
- Laboratory of Medical Investigation in Magnetic Resonance-44 (LIM 44), University of Sao Paulo, Sao Paulo 05403-000, SP, Brazil
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Landes-Chateau C, Levraut M, Okuda DT, Themelin A, Cohen M, Kantarci OH, Siva A, Pelletier D, Mondot L, Lebrun-Frenay C. The diagnostic value of the central vein sign in radiologically isolated syndrome. Ann Clin Transl Neurol 2024; 11:662-672. [PMID: 38186317 DOI: 10.1002/acn3.51986] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/15/2023] [Accepted: 12/16/2023] [Indexed: 01/09/2024] Open
Abstract
OBJECTIVE The radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS). Increasing evidence suggests that the central vein sign (CVS) enhances lesion specificity, allowing for greater MS diagnostic accuracy. This study evaluated the diagnostic performance of the CVS in RIS. METHODS Patients were prospectively recruited in a single tertiary center for MS care. Participants with RIS were included and compared to a control group of sex and age-matched subjects. All participants underwent 3 Tesla magnetic resonance imaging, including postcontrast susceptibility-based sequences, and the presence of CVS was analyzed. Sensitivity and specificity were assessed for different CVS lesion criteria, defined by proportions of lesions positive for CVS (CVS+) or by the absolute number of CVS+ lesions. RESULTS 180 participants (45 RIS, 45 MS, 90 non-MS) were included, representing 5285 white matter lesions. Among them, 4608 were eligible for the CVS assessment (970 in RIS, 1378 in MS, and 2260 in non-MS). According to independent ROC comparisons, the proportion of CVS+ lesions performed similarly in diagnosing RIS from non-MS than MS from non-MS (p = 0.837). When a 6-lesion CVS+ threshold was applied, RIS lesions could be diagnosed with an accuracy of 87%. MS could be diagnosed with a sensitivity of 98% and a specificity of 83%. Adding OCBs or Kappa index to CVS biomarker increased the specificity to 100% for RIS diagnosis. INTERPRETATION This study shows evidence that CVS is an effective imaging biomarker in differentiating RIS from non-MS, with similar performances to those in MS.
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Affiliation(s)
| | - Michael Levraut
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Médecine Interne, Centre Hospitalier Universitaire de Nice, Hôpital l'Archet 1, Nice, France
| | - Darin T Okuda
- The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Albert Themelin
- Service de Radiologie, Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | - Mikael Cohen
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Neurologie, Centre de Ressource et de Compétence Sclérose en Plaques (CRC-SEP), Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | | | - Aksel Siva
- Istanbul University, Cerrahpasa School of Medicine, Istanbul, Turkey
| | | | - Lydiane Mondot
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Radiologie, Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
| | - Christine Lebrun-Frenay
- Université Cote d'Azur, UMR2CA (URRIS), Nice, France
- Service de Neurologie, Centre de Ressource et de Compétence Sclérose en Plaques (CRC-SEP), Centre Hospitalier Universitaire de Nice, Hôpital Pasteur 2, Nice, France
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9
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Gao C, Su L, Li H, Song T, Liu Y, Duan Y, Shi FD. Susceptibility-weighted image features in AQP4-negative-NMOSD versus MS. Mult Scler Relat Disord 2024; 82:105406. [PMID: 38176283 DOI: 10.1016/j.msard.2023.105406] [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: 10/01/2023] [Revised: 12/16/2023] [Accepted: 12/22/2023] [Indexed: 01/06/2024]
Abstract
OBJECTIVE To characterize the susceptibility-weighted image (SWI) features including paramagnetic rim and nodular lesions with signal intensity changes and central vein sign (CVS) associated with aquaporin 4 (AQP4)-immunoglobulin G (IgG)-negative neuromyelitis optica spectrum disorder (NMOSD), and explore whether they can be used as potential imaging biomarkers for differentiating multiple sclerosis (MS) from this disorder. METHODS We prospectively recruited NMOSD with AQP4-IgG-negative (AQP4- NMOSD) and IgG-positive (AQP4+ NMOSD), and MS subjects from the Clinical and Imaging Patterns of Neuroinflammation Diseases in China (CLUE) project (NCT0410683) between 2019 and 2021. The SWI features including paramagnetic rim and nodular lesions with signal intensity changes and CVS were analyzed and compared among groups, and the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined for distinguishing MS from AQP4- NMOSD. RESULTS We enrolled a total of 160 consecutive patients (22 AQP4- NMOSD, 65 AQP4+ NMOSD, and 73 MS). We observed paramagnetic rim lesion (0/120 lesions, 0 %) and nodular (1/120, 1 %) lesions with hypointense signals on SWI in the AQP4- NMOSD group. These characteristics were similar to those recorded from AQP4+ NMOSD patients (rim: 0/369 lesions, 0 %, P = 1.000; nodular: 10/369 lesions, 2.7 %, P = 1.000), but differed significantly from those observed in the MS group (rim: 162/1665 lesions, 9.7 %, P<0.001; nodular: 392/1665 lesions, 23.5 %, P < 0.001). AQP4- NMOSD patients had fewer average CVS+ rate (12 %) than MS patients (46 %, p<0.001), similar to AQP4+ NMOSD (13 %, p = 1.000). The SWI imaging features denoting lesions with paramagnetic rim or nodular hypointense SWI signals showed 90.4 % sensitivity, 95.5 % specificity, 98.5 % PPV, and 75 % NPV, and the criteria with≥3 CVS lesions showed sensitivity of 91.8 %, specificity of 90.9 %%, PPV of 97.1 %, and NPV of 76.9 % in distinguishing MS from AQP4- NMOSD. DISCUSSION The SWI imaging features including lesions with paramagnetic rim or nodular hypointense SWI signals and 3 CVS lesions carries useful information in distinguishing MS from AQP4- NMOSD.
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Affiliation(s)
- Chenyang Gao
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, PR China
| | - Lei Su
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, PR China
| | - Hongfang Li
- Center for Neurology, Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China/China National Clinical Research Center for Neurological Diseases, Beijing, PR China
| | - Tian Song
- Center for Neurology, Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China/China National Clinical Research Center for Neurological Diseases, Beijing, PR China
| | - Yaou Liu
- Center for Neurology, Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China/China National Clinical Research Center for Neurological Diseases, Beijing, PR China
| | - Yunyun Duan
- Center for Neurology, Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China/China National Clinical Research Center for Neurological Diseases, Beijing, PR China
| | - Fu-Dong Shi
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin Medical University, Tianjin, PR China; Center for Neurology, Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China/China National Clinical Research Center for Neurological Diseases, Beijing, PR China.
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10
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Cagol A, Cortese R, Barakovic M, Schaedelin S, Ruberte E, Absinta M, Barkhof F, Calabrese M, Castellaro M, Ciccarelli O, Cocozza S, De Stefano N, Enzinger C, Filippi M, Jurynczyk M, Maggi P, Mahmoudi N, Messina S, Montalban X, Palace J, Pontillo G, Pröbstel AK, Rocca MA, Ropele S, Rovira À, Schoonheim MM, Sowa P, Strijbis E, Wattjes MP, Sormani MP, Kappos L, Granziera C. Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis. JAMA Neurol 2024; 81:143-153. [PMID: 38079177 PMCID: PMC10714285 DOI: 10.1001/jamaneurol.2023.4737] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/06/2023] [Indexed: 02/13/2024]
Abstract
Importance Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures MS/CIS vs non-MS conditions. Main Outcomes and Measures Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Health Sciences, University of Genova, Genova, Italy
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Medical Image Analysis Center, Basel, Switzerland
| | - Martina Absinta
- Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- National Institute for Health and Care Research (NIHR) University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Sirio Cocozza
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - 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
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maciej Jurynczyk
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Pietro Maggi
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
- Neuroinflammation Imaging Lab, Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Nima Mahmoudi
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Silvia Messina
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - 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, Ontario, Canada
| | - Jacqueline Palace
- Department of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Giuseppe Pontillo
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Multiple Sclerosis Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Anne-Katrin Pröbstel
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Departments of Biomedicine and Clinical Research, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - Maria A. Rocca
- Neuroimaging Research Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, Istituto di Ricovero e Cura a Carattere Scientifico, San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Stefan Ropele
- 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
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Menno M. Schoonheim
- Multiple Sclerosis Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Eva Strijbis
- Multiple Sclerosis Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, Amsterdam, the Netherlands
| | - Mike P. Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Maria Pia Sormani
- Department of Health Sciences, University of Genova, Genova, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Policlinico San Martino, Genova, Italy
| | - Ludwig Kappos
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland
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11
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Belov SE, Boyko AN, Dolgushin MB. [The central vein sign in the differential diagnosis of multiple sclerosis]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:58-65. [PMID: 39175241 DOI: 10.17116/jnevro202412407258] [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: 08/24/2024]
Abstract
OBJECTIVE To carry out a clinical and radiological assessment of the central vein sign (CVS) as a diagnostic marker for multiple sclerosis (MS) and other demyelinating and non-demyelinating diseases with focal brain damage, using clinical and laboratory examination data, as well as MRI. MATERIAL AND METHODS The results of clinical and neuroradiological examination of 107 patients diagnosed with MS or with other diseases accompanied by focal brain damage according to MRI data were analyzed. RESULTS CVS is a sensitive but low-specific diagnostic marker of MS. According to our data, the sensitivity and specificity of 40 and 50% of the threshold of perivenular lesions in the diagnosis of MS are the same and amount to 100% and 39.4%, respectively. Neither the type of MS course, nor the severity of the course, nor the intake of DMT (disease modifying treatment), affect the proportion of foci with CVS. The spread of the proportion of foci with CVS in patients with MS was 60-100%. The proportion of foci with CVS is below 40 and 50% of the threshold in patients with demyelinating and non-demyelinating diseases (NMOSD, migraine, systemic lupus erythematosus, Susak disease, CLIPPERS), which allows for differential diagnosis with MS. The proportion of foci with CVS comparable to MS in patients with acute disseminated encephalomyelitis, small vessel disease, as well as in patients with radiologically isolated syndrome does not allow using this symptom in the differential diagnosis of these conditions. CONCLUSION The use of CVS as a diagnostic marker of MS is possible only in combination with the already existing diagnostic criteria of MS.
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Affiliation(s)
- S E Belov
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - A N Boyko
- Pirogov Russian National Research Medical University, Moscow, Russia
- Federal Center for Brain Research and Neurotechnology, Moscow, Russia
| | - M B Dolgushin
- Federal Center for Brain Research and Neurotechnology, Moscow, Russia
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12
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Cacciaguerra L, Rocca MA, Filippi M. Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders. Korean J Radiol 2023; 24:1260-1283. [PMID: 38016685 PMCID: PMC10700997 DOI: 10.3348/kjr.2023.0360] [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: 04/26/2023] [Revised: 08/09/2023] [Accepted: 08/21/2023] [Indexed: 11/30/2023] Open
Abstract
Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.
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Affiliation(s)
- Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy.
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13
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Gill AJ, Schorr EM, Gadani SP, Calabresi PA. Emerging imaging and liquid biomarkers in multiple sclerosis. Eur J Immunol 2023; 53:e2250228. [PMID: 37194443 PMCID: PMC10524168 DOI: 10.1002/eji.202250228] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/10/2023] [Accepted: 05/12/2023] [Indexed: 05/18/2023]
Abstract
The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.
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Affiliation(s)
- Alexander J. Gill
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Emily M. Schorr
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Sachin P. Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, MD, US
- Department of Neuroscience, Baltimore, MD, US
- Department of Ophthalmology, Baltimore, MD, US
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14
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Jarius S, Aktas O, Ayzenberg I, Bellmann-Strobl J, Berthele A, Giglhuber K, Häußler V, Havla J, Hellwig K, Hümmert MW, Kleiter I, Klotz L, Krumbholz M, Kümpfel T, Paul F, Ringelstein M, Ruprecht K, Senel M, Stellmann JP, Bergh FT, Tumani H, Wildemann B, Trebst C. Update on the diagnosis and treatment of neuromyelits optica spectrum disorders (NMOSD) - revised recommendations of the Neuromyelitis Optica Study Group (NEMOS). Part I: Diagnosis and differential diagnosis. J Neurol 2023:10.1007/s00415-023-11634-0. [PMID: 37022481 DOI: 10.1007/s00415-023-11634-0] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/17/2023] [Accepted: 02/18/2023] [Indexed: 04/07/2023]
Abstract
The term 'neuromyelitis optica spectrum disorders' (NMOSD) is used as an umbrella term that refers to aquaporin-4 immunoglobulin G (AQP4-IgG)-positive neuromyelitis optica (NMO) and its formes frustes and to a number of closely related clinical syndromes without AQP4-IgG. NMOSD were originally considered subvariants of multiple sclerosis (MS) but are now widely recognized as disorders in their own right that are distinct from MS with regard to immunopathogenesis, clinical presentation, optimum treatment, and prognosis. In part 1 of this two-part article series, which ties in with our 2014 recommendations, the neuromyelitis optica study group (NEMOS) gives updated recommendations on the diagnosis and differential diagnosis of NMOSD. A key focus is on differentiating NMOSD from MS and from myelin oligodendrocyte glycoprotein antibody-associated encephalomyelitis (MOG-EM; also termed MOG antibody-associated disease, MOGAD), which shares significant similarity with NMOSD with regard to clinical and, partly, radiological presentation, but is a pathogenetically distinct disease. In part 2, we provide updated recommendations on the treatment of NMOSD, covering all newly approved drugs as well as established treatment options.
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Affiliation(s)
- Sven Jarius
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany.
| | - Orhan Aktas
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ilya Ayzenberg
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Judith Bellmann-Strobl
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- NeuroCure Clinical Research Center, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, and Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University Munich, Klinikum rechts der Isar, Munich, Germany
| | - Katrin Giglhuber
- Department of Neurology, School of Medicine, Technical University Munich, Klinikum rechts der Isar, Munich, Germany
| | - Vivien Häußler
- Department of Neurology and Institute of Neuroimmunology and MS (INIMS), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joachim Havla
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- Data Integration for Future Medicine (DIFUTURE) Consortium, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Kerstin Hellwig
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Martin W Hümmert
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Ingo Kleiter
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
- Marianne-Strauß-Klinik, Behandlungszentrum Kempfenhausen für Multiple Sklerose Kranke, Berg, Germany
| | - Luisa Klotz
- Department of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Markus Krumbholz
- Department of Neurology and Pain Treatment, Immanuel Klinik Rüdersdorf, University Hospital of the Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany
- Faculty of Health Sciences Brandenburg, Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany
- Department of Neurology and Stroke, University Hospital of Tübingen, Tübingen, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Friedemann Paul
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- NeuroCure Clinical Research Center, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, and Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Marius Ringelstein
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Neurology, Center for Neurology and Neuropsychiatry, LVR-Klinikum, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Makbule Senel
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Jan-Patrick Stellmann
- Department of Neurology and Institute of Neuroimmunology and MS (INIMS), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- APHM, Hopital de la Timone, CEMEREM, Marseille, France
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
| | | | | | - Brigitte Wildemann
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany
| | - Corinna Trebst
- Department of Neurology, Hannover Medical School, Hannover, Germany.
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15
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Lapucci C, Tazza F, Rebella S, Boffa G, Sbragia E, Bruschi N, Mancuso E, Mavilio N, Signori A, Roccatagliata L, Cellerino M, Schiavi S, Inglese M. Central vein sign and diffusion MRI differentiate microstructural features within white matter lesions of multiple sclerosis patients with comorbidities. Front Neurol 2023; 14:1084661. [PMID: 36970546 PMCID: PMC10030505 DOI: 10.3389/fneur.2023.1084661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 01/30/2023] [Indexed: 03/29/2023] Open
Abstract
Introduction The Central Vein Sign (CVS) has been suggested as a potential biomarker to improve diagnostic specificity in multiple sclerosis (MS). Nevertheless, the impact of comorbidities on CVS performance has been poorly investigated so far. Despite the similar features shared by MS, migraine and Small Vessel Disease (SVD) at T2-weighted conventional MRI sequences, ex-vivo studies demonstrated their heterogeneous histopathological substrates. If in MS, inflammation, primitive demyelination and axonal loss coexist, in SVD demyelination is secondary to ischemic microangiopathy, while the contemporary presence of inflammatory and ischemic processes has been suggested in migraine. The aims of this study were to investigate the impact of comorbidities (risk factors for SVD and migraine) on the global and subregional assessment of the CVS in a large cohort of MS patients and to apply the Spherical Mean Technique (SMT) diffusion model to evaluate whether perivenular and non-perivenular lesions show distinctive microstructural features. Methods 120 MS patients stratified into 4 Age Groups performed 3T brain MRI. WM lesions were classified in "perivenular" and "non-perivenular" by visual inspection of FLAIR* images; mean values of SMT metrics, indirect estimators of inflammation, demyelination and fiber disruption (EXTRAMD: extraneurite mean diffusivity, EXTRATRANS: extraneurite transverse diffusivity and INTRA: intraneurite signal fraction, respectively) were extracted. Results Of the 5303 lesions selected for the CVS assessment, 68.7% were perivenular. Significant differences were found between perivenular and non-perivenular lesion volume in the whole brain (p < 0.001) and between perivenular and non-perivenular lesion volume and number in all the four subregions (p < 0.001 for all). The percentage of perivenular lesions decreased from youngest to oldest patients (79.7%-57.7%), with the deep/subcortical WM of oldest patients as the only subregion where the number of non-perivenular was higher than the number of perivenular lesions. Older age and migraine were independent predictors of a higher percentage of non-perivenular lesions (p < 0.001 and p = 0.013 respectively). Whole brain perivenular lesions showed higher inflammation, demyelination and fiber disruption than non perivenular lesions (p = 0.001, p = 0.001 and p = 0.02 for EXTRAMD, EXTRATRANS and INTRA respectively). Similar findings were found in the deep/subcortical WM (p = 0.001 for all). Compared to non-perivenular lesions, (i) perivenular lesions located in periventricular areas showed a more severe fiber disruption (p = 0.001), (ii) perivenular lesions located in juxtacortical and infratentorial regions exhibited a higher degree of inflammation (p = 0.01 and p = 0.05 respectively) and (iii) perivenular lesions located in infratentorial areas showed a higher degree of demyelination (p = 0.04). Discussion Age and migraine have a relevant impact in reducing the percentage of perivenular lesions, particularly in the deep/subcortical WM. SMT may differentiate perivenular lesions, characterized by higher inflammation, demyelination and fiber disruption, from non perivenular lesions, where these pathological processes seemed to be less pronounced. The development of new non-perivenular lesions, especially in the deep/subcortical WM of older patients, should be considered a "red flag" for a different -other than MS- pathophysiology.
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Affiliation(s)
- Caterina Lapucci
- HNSR, IRRCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Francesco Tazza
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | - Giacomo Boffa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Elvira Sbragia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Nicolò Bruschi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Elisabetta Mancuso
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Nicola Mavilio
- Department of Neuroradiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Alessio Signori
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Luca Roccatagliata
- Department of Neuroradiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Maria Cellerino
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino IRCCS, Genoa, Italy
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16
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Cortese R, Prados Carrasco F, Tur C, Bianchi A, Brownlee W, De Angelis F, De La Paz I, Grussu F, Haider L, Jacob A, Kanber B, Magnollay L, Nicholas RS, Trip A, Yiannakas M, Toosy AT, Hacohen Y, Barkhof F, Ciccarelli O. Differentiating Multiple Sclerosis From AQP4-Neuromyelitis Optica Spectrum Disorder and MOG-Antibody Disease With Imaging. Neurology 2023; 100:e308-e323. [PMID: 36192175 PMCID: PMC9869760 DOI: 10.1212/wnl.0000000000201465] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 09/09/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Relapsing-remitting multiple sclerosis (RRMS), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may have overlapping clinical features. There is an unmet need for imaging markers that differentiate between them when serologic testing is unavailable or ambiguous. We assessed whether imaging characteristics typical of MS discriminate RRMS from AQP4-NMOSD and MOGAD, alone and in combination. METHODS Adult, nonacute patients with RRMS, APQ4-NMOSD, and MOGAD and healthy controls were prospectively recruited at the National Hospital for Neurology and Neurosurgery (London, United Kingdom) and the Walton Centre (Liverpool, United Kingdom) between 2014 and 2019. They underwent conventional and advanced brain, cord, and optic nerve MRI and optical coherence tomography (OCT). RESULTS A total of 91 consecutive patients (31 RRMS, 30 APQ4-NMOSD, and 30 MOGAD) and 34 healthy controls were recruited. The most accurate measures differentiating RRMS from AQP4-NMOSD were the proportion of lesions with the central vein sign (CVS) (84% vs 33%, accuracy/specificity/sensitivity: 91/88/93%, p < 0.001), followed by cortical lesions (median: 2 [range: 1-14] vs 1 [0-1], accuracy/specificity/sensitivity: 84/90/77%, p = 0.002) and white matter lesions (mean: 39.07 [±25.8] vs 9.5 [±14], accuracy/specificity/sensitivity: 78/84/73%, p = 0.001). The combination of higher proportion of CVS, cortical lesions, and optic nerve magnetization transfer ratio reached the highest accuracy in distinguishing RRMS from AQP4-NMOSD (accuracy/specificity/sensitivity: 95/92/97%, p < 0.001). The most accurate measures favoring RRMS over MOGAD were white matter lesions (39.07 [±25.8] vs 1 [±2.3], accuracy/specificity/sensitivity: 94/94/93%, p = 0.006), followed by cortical lesions (2 [1-14] vs 1 [0-1], accuracy/specificity/sensitivity: 84/97/71%, p = 0.004), and retinal nerve fiber layer thickness (RNFL) (mean: 87.54 [±13.83] vs 75.54 [±20.33], accuracy/specificity/sensitivity: 80/79/81%, p = 0.009). Higher cortical lesion number combined with higher RNFL thickness best differentiated RRMS from MOGAD (accuracy/specificity/sensitivity: 84/92/77%, p < 0.001). DISCUSSION Cortical lesions, CVS, and optic nerve markers achieve a high accuracy in distinguishing RRMS from APQ4-NMOSD and MOGAD. This information may be useful in clinical practice, especially outside the acute phase and when serologic testing is ambiguous or not promptly available. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that selected conventional and advanced brain, cord, and optic nerve MRI and OCT markers distinguish adult patients with RRMS from AQP4-NMOSD and MOGAD.
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Affiliation(s)
- Rosa Cortese
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Ferran Prados Carrasco
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Carmen Tur
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Alessia Bianchi
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Wallace Brownlee
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Floriana De Angelis
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Isabel De La Paz
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Francesco Grussu
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Lukas Haider
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Anu Jacob
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Baris Kanber
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Lise Magnollay
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Richard S Nicholas
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Anand Trip
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Marios Yiannakas
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Ahmed T Toosy
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Yael Hacohen
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Frederik Barkhof
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands
| | - Olga Ciccarelli
- From the Department of Neuroinflammation (R.C., F.P.C., C.T., A.B., W.B., F.D.A., I.D.L.P., F.G., L.H., L.M., A.T., M.Y., A.T.T., Y.H.R.C.P.C.H., F.B., O.C.), Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London; Department of Medicine (R.C.), Surgery and Neuroscience, University of Siena, Italy; Department of Medical Physics and Biomedical Engineering (F.P.C., B.K., F.B.), Centre for Medical Imaging Computing, University College of London; Universitat Oberta de Catalunya (F.P.C.), Barcelona, Spain; MS Centre of Catalonia (Cemcat) (C.T.), Vall d'Hebron Institute of Research, Spain; Radiomics Group (F.G.), Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Barcelona, Spain; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; NMO Clinical Service at the Walton Centre (A.J.), Liverpool, United Kingdom; Division of Multiple Sclerosis and Autoimmune Neurology (A.J.), Neurological Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates; Division of Brain Sciences (R.S.N.), Department of Medicine, Imperial College London; National Institute for Health Research (NIHR) (A.T., F.B., O.C.), University College London Hospitals (UCLH), Biomedical Research Centre; and Department of Radiology and Nuclear Medicine (F.B.), Amsterdam University Medical Centre, the Netherlands.
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17
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Yavaş HG, Sağtaş E. Central vein sign: comparison of multiple sclerosis and leukoaraiosis. Turk J Med Sci 2022; 52:1933-1942. [PMID: 36945994 PMCID: PMC10390208 DOI: 10.55730/1300-0144.5541] [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: 05/09/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Leukoaraiosis produces white matter lesions (WML) similar to multiple sclerosis (MS) on brain magnetic resonance imaging (MRI), and the distinction between these two conditions is difficult radiologically. This study aimed to investigate the role of the central vein sign (CVS) in susceptibility-weighted imaging (SWI) sequence in distinguishing MS lesions from leukoaraiosis lesions in Turkish population. METHODS In this prospective study, axial SWI and sagittal three-dimensional fluid-attenuated inversion recovery (3DFLAIR) were obtained in 374 consecutive patients. The study consisted of 169 (89 MS patients, 80 patients with leukoaraiosis) patients according to the inclusion and exclusion criteria. Two observers evaluated MR images by consensus, and observers were unaware of the patient's clinical findings. Locations (periventricular, juxtacortical, and deep white matter) and the presence of CVS were investigated for each of the lesions. Differences between patients in the leukoaraiosis and MS groups were investigated using the Mann-Whitney U test or chi-square analysis. In addition, receiver operating characteristic (ROC) analysis was used to analyze the diagnostic performance of CVS. RESULTS A total of 1908 WMLs (1265 MS lesions, 643 leukoaraiosis) were detected in 169 patients. The CVS was significantly higher in the MS lesions (p < 0.001). The CVS positivity rate in periventricular WMLs was higher than in juxtacortical WMLs or deep WMLs, both for all patients and for patients with MS (p < 0.001). The area under the curve (AUC) of the ROC analysis was 0.88 (95% confidence interval 0.83-0.93) for CVS in the distinction of MS lesions and leukoaraiosis. DISCUSSION The presence of CVS in the SWI sequence can be used as an auxiliary finding for the diagnosis of MS in the differentiation of MS and leukoaraiosis lesions.
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Affiliation(s)
- Hüseyin Gökhan Yavaş
- Department of Radiology, Ahi Evran University Kırşehir Education and Research Hospital, Kırşehir, Turkey
| | - Ergin Sağtaş
- Department of Radiology, Faculty of Medicine, Pamukkale University, Denizli, Turkey
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18
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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19
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Kolb H, Al-Louzi O, Beck ES, Sati P, Absinta M, Reich DS. From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions. Neuroimage Clin 2022; 36:103194. [PMID: 36170753 PMCID: PMC9668624 DOI: 10.1016/j.nicl.2022.103194] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 12/14/2022]
Abstract
Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.
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Affiliation(s)
- Hadar Kolb
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel,Corresponding author at: Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv-Yaffo, Israel.
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S. Beck
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA,Institute of Experimental Neurology (INSPE), IRCSS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy,Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
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20
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Abstract
PURPOSE OF REVIEW This article reviews the cardinal clinical features, distinct immunopathology, current diagnostic criteria, relapse-related risk factors, emerging biomarkers, and evolving treatment strategies pertaining to neuromyelitis optica spectrum disorders (NMOSD). RECENT FINDINGS The discovery of the pathogenic aquaporin-4 (AQP4)-IgG autoantibody and characterization of NMOSD as an autoimmune astrocytopathy have spearheaded the identification of key immunologic therapeutic targets in this disease, including but not limited to the complement system, the interleukin 6 (IL-6) receptor, and B cells. Accordingly, four recent randomized controlled trials have demonstrated the efficacy of three new NMOSD therapies, namely eculizumab, satralizumab, and inebilizumab. SUMMARY Currently, NMOSD poses both diagnostic and treatment challenges. It is debated whether individuals who are seropositive for myelin oligodendrocyte glycoprotein (MOG)-IgG belong within the neuromyelitis optica spectrum. This discussion is fueled by disparities in treatment responses between patients who are AQP4-IgG seropositive and seronegative, suggesting different immunopathologic mechanisms may govern these conditions. As our understanding regarding the immune pathophysiology of NMOSD expands, emerging biomarkers, including serum neurofilament light chain and glial fibrillary acidic protein (GFAP), may facilitate earlier relapse detection and inform long-term treatment decisions. Future research focal points should include strategies to optimize relapse management, restorative treatments that augment neurologic recovery, and practical solutions that promote equitable access to approved therapies for all patients with NMOSD.
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21
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Shadmani G, Simkins TJ, Assadsangabi R, Apperson M, Hacein-Bey L, Raslan O, Ivanovic V. Autoimmune diseases of the brain, imaging and clinical review. Neuroradiol J 2022; 35:152-169. [PMID: 34490814 PMCID: PMC9130615 DOI: 10.1177/19714009211042879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
There is an extensive spectrum of autoimmune entities that can involve the central nervous system, which has expanded with the emergence of new imaging modalities and several clinicopathologic entities. Clinical presentation is usually non-specific, and imaging has a critical role in the workup of these diseases. Immune-mediated diseases of the brain are not common in daily practice for radiologists and, except for a few of them such as multiple sclerosis, there is a vague understanding about differentiating them from each other based on the radiological findings. In this review, we aim to provide a practical diagnostic approach based on the unique radiological findings for each disease. We hope our diagnostic approach will help radiologists expand their basic understanding of the discussed disease entities and narrow the differential diagnosis in specific clinical scenarios. An understanding of unique imaging features of these disorders, along with laboratory evaluation, may enable clinicians to decrease the need for tissue biopsy.
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Affiliation(s)
- Ghazal Shadmani
- Department of Radiology, Section of
Neuroradiology, University of California Davis Medical Center, USA
| | - Tyrell J Simkins
- Department of Neurology
(Neuroimmunulogy), University of California Davis Medical center, USA
| | - Reza Assadsangabi
- Department of Radiology, Section of
Neuroradiology, University of California Davis Medical Center, USA
| | - Michelle Apperson
- Department of Neurology
(Neuroimmunulogy), University of California Davis Medical center, USA
| | - Lotfi Hacein-Bey
- Department of Radiology, Section of
Neuroradiology, University of California Davis Medical Center, USA
| | - Osama Raslan
- Department of Radiology, Section of
Neuroradiology, University of California Davis Medical Center, USA
| | - Vladimir Ivanovic
- Department of Radiology, Section of
Neuroradiology, University of California Davis Medical Center, USA
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22
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Chaaban L, Safwan N, Moussa H, El‐Sammak S, Khoury S, Hannoun S. Central vein sign: A putative diagnostic marker for multiple sclerosis. Acta Neurol Scand 2022; 145:279-287. [PMID: 34796472 DOI: 10.1111/ane.13553] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/04/2021] [Accepted: 11/03/2021] [Indexed: 11/29/2022]
Abstract
The presence of a "central vein sign" (CVS) has been introduced as a biomarker for the diagnosis of multiple sclerosis (MS) and shown to have the ability to accurately differentiate MS from other white matter diseases (MS mimics). Following the development of susceptibility-based magnetic resonance venography that allowed the in vivo detection of CVS, a standard CVS definition was established by introducing the "40% rule" that assesses the number of MS lesions with CVS as a fraction of the total number of lesions to differentiate MS lesions from other types of lesions. The "50% rule," the "three-lesion criteria," and the "six-lesion criteria" were later introduced and defined. Each of these rules had high levels of sensitivity, specificity, and accuracy in differentiating MS from other diseases, which has been recognized by the Magnetic Resonance Imaging in MS (MAGNIMS) group and the Consortium of MS Centers task force. The North American Imaging in Multiple Sclerosis Cooperative even provided statements and recommendations aiming to refine, standardize and evaluate the CVS in MS. Herein, we review the existing literature on CVS and evaluate its added value in the diagnosis of MS and usefulness in differentiating it from other vasculopathies. We also review the histopathology of CVS and identify available automated CVS assessment methods as well as define the role of vascular comorbidities in the diagnosis of MS.
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Affiliation(s)
- Lara Chaaban
- Department of Agriculture and Food Sciences American University of Beirut Beirut Lebanon
| | - Nancy Safwan
- Department of Agriculture and Food Sciences American University of Beirut Beirut Lebanon
| | - Hussein Moussa
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
| | - Sally El‐Sammak
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
| | - Samia J. Khoury
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
- Faculty of Medicine Abu‐Haidar Neuroscience Institute American University of Beirut Medical Center Beirut Lebanon
| | - Salem Hannoun
- Nehme and Therese Tohme Multiple Sclerosis Center American University of Beirut Medical Center Beirut Lebanon
- Medical Imaging Sciences Program Division of Health Professions Faculty of Health Sciences American University of Beirut Beirut Lebanon
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23
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Reichl M, Wittayer M, Weber CE, Platten M, Gass A, Eisele P. Consistency of the "central vein sign" in chronic multiple sclerosis lesions. Mult Scler Relat Disord 2022; 58:103530. [PMID: 35066270 DOI: 10.1016/j.msard.2022.103530] [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: 12/21/2021] [Revised: 01/05/2022] [Accepted: 01/14/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND In recent years, there has been an increasing interest in the central vein sign (CVS) as a new imaging marker and previous cross-sectional studies demonstrated that the CVS has the potential to discriminate multiple sclerosis (MS) lesions from non-MS lesions. The aim of this study was to investigate the consistency of the CVS in a longitudinal magnetic resonance imaging (MRI) data set. METHODS 3T MRI datasets from seventy-one people with MS acquired at baseline and after 12 months-follow-up were analyzed. Chronic lesions were identified on fluid-attenuated inversion recovery (FLAIR) images. Co-registered susceptibility-weighted/FLAIR images were analyzed for the presence of a CVS at baseline and follow-up. RESULTS A total of 183 chronic lesions were included in the final analysis. At baseline MRI, a CVS was detectable in 141/183 (77%) lesions. Overall, the CVS was consistent in 114/141 (81%) lesions (Cohen's kappa = 0.46, standard error = 0.07). CONCLUSION The CVS is a rather stable feature in chronic MS lesions and therefore represents a robust imaging marker that could increase the specificity of MRI in MS.
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Affiliation(s)
- Matthias Reichl
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Claudia E Weber
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Philipp Eisele
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.
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24
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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: 1.0] [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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25
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Juryńczyk M, Klimiec-Moskal E, Kong Y, Hurley S, Messina S, Yeo T, Jenkinson M, Leite MI, Palace J. Elucidating distinct clinico-radiologic signatures in the borderland between neuromyelitis optica and multiple sclerosis. J Neurol 2022; 269:269-279. [PMID: 34043042 PMCID: PMC8738499 DOI: 10.1007/s00415-021-10619-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 05/14/2021] [Accepted: 05/18/2021] [Indexed: 10/31/2022]
Abstract
BACKGROUND Separating antibody-negative neuromyelitis optica spectrum disorders (NMOSD) from multiple sclerosis (MS) in borderline cases is extremely challenging due to lack of biomarkers. Elucidating different pathologies within the likely heterogenous antibody-negative NMOSD/MS overlap syndrome is, therefore, a major unmet need which would help avoid disability from inappropriate treatment. OBJECTIVE In this study we aimed to identify distinct subgroups within the antibody-negative NMOSD/MS overlap syndrome. METHODS Twenty-five relapsing antibody-negative patients with NMOSD features underwent a prospective brain and spinal cord MRI. Subgroups were identified by an unsupervised algorithm based on pre-selected NMOSD/MS discriminators. RESULTS Four subgroups were identified. Patients from Group 1 termed "MS-like" (n = 6) often had central vein sign and cortical lesions (83% and 67%, respectively). All patients from Group 2 ("spinal MS-like", 8) had short-segment myelitis and no MS-like brain lesions. Group 3 ("classic NMO-like", 6) had high percentage of bilateral optic neuritis and longitudinally extensive transverse myelitis (LETM, 80% and 60%, respectively) and normal brain appearance (100%). Group 4 ("NMO-like with brain involvement", 5) typically had a history of NMOSD-like brain lesions and LETM. When compared with other groups, Group 4 had significantly decreased fractional anisotropy in non-lesioned tracts (0.46 vs. 0.49, p = 0.003) and decreased thalamus volume (0.84 vs. 0.98, p = 0.04). CONCLUSIONS NMOSD/MS cohort contains distinct subgroups likely corresponding to different pathologies and requiring tailored treatment. We propose that non-conventional MRI might help optimise diagnosis in these challenging patients.
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Affiliation(s)
- Maciej Juryńczyk
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK.
- Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.
| | - Elżbieta Klimiec-Moskal
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK
- Department of Neurology, Jagiellonian University Medical College, Kraków, Poland
| | - Yazhuo Kong
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Samuel Hurley
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Silvia Messina
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK
| | - Tianrong Yeo
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Maria Isabel Leite
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK
| | - Jacqueline Palace
- Department of Clinical Neurology, Nuffield Department of Clinical Neuroscienes, University of Oxford, Oxford, UK.
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26
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Moccia M, Haider L, Eshaghi A, van de Pavert SHP, Brescia Morra V, Patel A, Wheeler-Kingshott CAM, Barkhof F, Ciccarelli O. B Cells in the CNS at Postmortem Are Associated With Worse Outcome and Cell Types in Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:e1108. [PMID: 34759021 PMCID: PMC8587731 DOI: 10.1212/nxi.0000000000001108] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 09/08/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND OBJECTIVES To define the clinical and pathologic correlations of compartmentalized perivascular B cells in postmortem progressive multiple sclerosis (MS) brains. METHODS Brain slices were acquired from 11 people with secondary progressive (SP) MS, 5 people with primary progressive (PP) MS, and 4 controls. Brain slices were immunostained for B lymphocytes (CD20), T lymphocytes (CD3), cytotoxic T lymphocytes (CD8), neuronal neurofilaments (NF200), myelin (SMI94), macrophages/microglia (CD68 and IBA1), astrocytes (glial fibrillary acidic protein [GFAP]), and mitochondria (voltage-dependent anion channel and cytochrome c oxidase subunit 4). Differences in CD20 immunostaining intensity between disease groups and associations between CD20 immunostaining intensity and both clinical variables and other immunostaining intensities were explored with linear mixed regression models and Cox regression models, as appropriate. RESULTS CD20 immunostaining intensity was higher in PPMS (Coeff = 0.410; 95% confidence interval [CI] = 0.046, 0.774; p = 0.027) and SPMS (Coeff = 0.302; 95% CI = 0.020, 0.585; p = 0.036) compared with controls. CD20 immunostaining intensity was higher in cerebellar, spinal cord, and pyramidal onset (Coeff = 0.274; 95% CI = 0.039, 0.510; p = 0.022) compared with optic neuritis and sensory onset. Higher CD20 immunostaining intensity was associated with younger age at onset (hazard ratio [HR] = 1.033; 95% CI = 1.013, 1.053; p = 0.001), SP conversion (HR = 1.056; 95% CI = 1.022, 1.091; p = 0.001), wheelchair dependence (HR = 1.472; 95% CI = 1.108, 1.954; p = 0.008), and death (HR = 1.684; 95% CI = 1.238, 2.291; p = 0.001). Higher immunostaining intensity for CD20 was associated with higher immunostaining intensity for CD3 (Coeff = 0.114; 95% CI = 0.005, 0.224; p = 0.040), CD8 (Coeff = 0.275; 95% CI = 0.200, 0.350; p < 0.001), CD68 (Coeff = 0.084; 95% CI = 0.023, 0.144; p = 0.006), GFAP (Coeff = 0.002; 95% CI = 0.001, 0.004; p = 0.030), and damaged mitochondria (Coeff = 3.902; 95% CI = 0.891, 6.914; p = 0.011). DISCUSSION Perivascular B cells were associated with worse clinical outcomes and CNS-compartmentalized inflammation. Our findings further support the concept of targeting compartmentalized B-cell inflammation in progressive MS.
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Affiliation(s)
- Marcello Moccia
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Lukas Haider
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Arman Eshaghi
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Steven Harry Pieter van de Pavert
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Vincenzo Brescia Morra
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Amy Patel
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Claudia Angela Michela Wheeler-Kingshott
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Frederik Barkhof
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
| | - Olga Ciccarelli
- From the Queen Square MS Centre (M.M., L.H., A.E., S.H.P.v.d.P., A.P., C.A.M.W.-K., O.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom; Multiple Sclerosis Clinical Care and Research Unit (M.M., V.B.M.), Department of Neurosciences, Federico II University, Naples, Italy; Department of Biomedical Imaging and Image Guided Therapy (L.H.), Medical University of Vienna, Austria; Translational Imaging Group F.B., UCL Institute of Healthcare Engineering, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam, the Netherlands; and National Institute for Health Research (O.C.), University College London Hospitals Biomedical Research Centre, United Kingdom
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27
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Belov S, Boyko A. A symptom of the central vein in various diseases and protocols of MRI examination. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:19-26. [DOI: 10.17116/jnevro202212207219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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28
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Zrzavy T, Leutmezer F, Rommer P, Bsteh G, Kornek B, Berger T, Prayer D, Thurnher M, Haider L. Imaging features to distinguish AQP4-positive NMOSD and MS at disease onset: A retrospective analysis in a single-center cohort. Eur J Radiol 2021; 146:110063. [PMID: 34922119 DOI: 10.1016/j.ejrad.2021.110063] [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: 09/11/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 11/03/2022]
Abstract
PURPOSE To compare the diagnostic performance of imaging criteria that differentiate AQP4+ Neuromyelitis Optica Spectrum Disorders (NMOSD) and Multiple Sclerosis (MS) at disease onset (DO) and follow-up (FU). METHODS We retrospectively analyzed MRI scans at DO (defined as the first 60 days of patient-reported symptom onset) in 10 AQP4+NMOSD and 25 (time to MRI matched) relapsing-remitting MS patients from a monocentric cohort. RESULTS The Matthews criteria were met in 20% of AQP4+NMOSD patients at DO vs. 33% at FU, and in 96% of RRMS patients vs.100% at FU. Specificity (SP) and sensitivity (SE) were thus high at both time-points: SP-DO: 96%; SP-FU:100%; and SE-DO: 80%; SE-FU: 67%, with similar area under the curve (AUC) values at DO: 88% [95% CI 74%-100%] and FU: 83% [95% CI 67%-100%]. The Cacciaguerra criteria were met in 90% of AQP4+NMOSD patients at DO vs. 88.9% at FU and in 24% of RRMS patients vs. 14% at FU; SP-DO: 87%; SP-FU: 86%; and SE-DO: 90%; SE-FU: 89%, with similar AUC values at DO: 88% [95% CI 76%-98%] and FU: 87% [95% CI 74%-98%]. CONCLUSIONS While diagnostic MRI criteria were developed on data acquired years after disease onset, our study demonstrates their high applicability at the earliest disease stages, thus emphasising their valuable use in clinical practice.
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Affiliation(s)
- Tobias Zrzavy
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Fritz Leutmezer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Paulus Rommer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Gabriel Bsteh
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Barbara Kornek
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Thomas Berger
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Majda Thurnher
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Haider
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria; NMR Research Unit, Queens Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College London, Austria.
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29
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Lin TY, Chien C, Lu A, Paul F, Zimmermann HG. Retinal optical coherence tomography and magnetic resonance imaging in neuromyelitis optica spectrum disorders and MOG-antibody associated disorders: an updated review. Expert Rev Neurother 2021; 21:1101-1123. [PMID: 34551653 DOI: 10.1080/14737175.2021.1982697] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein IgG antibody-associated disorders (MOGAD) comprise two groups of rare neuroinflammatory diseases that cause attack-related damage to the central nervous system (CNS). Clinical attacks are often characterized by optic neuritis, transverse myelitis, and to a lesser extent, brainstem encephalitis/area postrema syndrome. Retinal optical coherence tomography (OCT) is a non-invasive technique that allows for in vivo thickness quantification of the retinal layers. Apart from OCT, magnetic resonance imaging (MRI) plays an increasingly important role in NMOSD and MOGAD diagnosis based on the current international diagnostic criteria. Retinal OCT and brain/spinal cord/optic nerve MRI can help to distinguish NMOSD and MOGAD from other neuroinflammatory diseases, particularly from multiple sclerosis, and to monitor disease-associated CNS-damage. AREAS COVERED This article summarizes the current status of imaging research in NMOSD and MOGAD, and reviews the clinical relevance of OCT, MRI and other relevant imaging techniques for differential diagnosis, screening and monitoring of the disease course. EXPERT OPINION Retinal OCT and MRI can visualize and quantify CNS damage in vivo, improving our understanding of NMOSD and MOGAD pathology. Further efforts on the standardization of these imaging techniques are essential for implementation into clinical practice and as outcome parameters in clinical trials.
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Affiliation(s)
- Ting-Yi Lin
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Angelo Lu
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Hanna G Zimmermann
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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Rovira À, Auger C. Beyond McDonald: updated perspectives on MRI diagnosis of multiple sclerosis. Expert Rev Neurother 2021; 21:895-911. [PMID: 34275399 DOI: 10.1080/14737175.2021.1957832] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) is an essential paraclinical test to establish an accurate and early diagnosis of multiple sclerosis (MS), which is based on the application of the McDonald criteria. AREAS COVERED The objective of this article is to analyze, based on publicly available database since the publication of the 2017 McDonald diagnostic criteria, the clinical impact of these criteria, to discuss the potential inclusion within these criteria of the optic nerve to demonstrate dissemination in space, and to guide the acquisition and interpretation of MRI scans for diagnostic purposes. Finally, the authors will review emerging MRI features that could improve the specificity of MRI in the diagnosis of MS and consequently minimize the misdiagnosis of this disease. EXPERT OPINION Although the optic nerve has not been included as one of the topographies required to demonstrate demyelinating lesion disseminated in space in the 2017 McDonald criteria, new studies seem to show some improvement in the sensitivity of these criteria when this topography is considered. New radiological findings such as the central vein sign and iron rims, should be considered within the typical MRI features of this disease with the objective of minimizing MRI-based diagnostic errors.
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Affiliation(s)
- Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Hospital Universitari Vall d'Hebron, Universitat Autònoma De Barcelona, Barcelona, Spain.,Vall d´Hebron Research Institute, Barcelona, Spain
| | - Cristina Auger
- Section of Neuroradiology (Department of Radiology), Hospital Universitari Vall d'Hebron, Universitat Autònoma De Barcelona, Barcelona, Spain.,Vall d´Hebron Research Institute, Barcelona, Spain
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31
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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: 359] [Impact Index Per Article: 89.8] [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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Abstract
OBJECTIVE. Tumefactive demyelination mimics primary brain neoplasms on imaging, often necessitating brain biopsy. This article reviews the literature for the clinical and radiologic findings of tumefactive demyelination in various disease processes to facilitate identification of tumefactive demyelination on imaging. CONCLUSION. Both clinical and radiologic findings must be integrated to distinguish tumefactive demyelinating lesions from similarly appearing lesions on imaging. Further research on the immunopathogenesis of tumefactive demyelination and associated conditions will elucidate their interrelationship.
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Solomon JM, Paul F, Chien C, Oh J, Rotstein DL. A window into the future? MRI for evaluation of neuromyelitis optica spectrum disorder throughout the disease course. Ther Adv Neurol Disord 2021; 14:17562864211014389. [PMID: 34035837 PMCID: PMC8111516 DOI: 10.1177/17562864211014389] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/12/2021] [Indexed: 12/12/2022] Open
Abstract
Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing, inflammatory disease of the central nervous system marked by relapses often associated with poor recovery and long-term disability. Magnetic resonance imaging (MRI) is recognized as an important tool for timely diagnosis of NMOSD as, in combination with serologic testing, it aids in distinguishing NMOSD from possible mimics. Although the role of MRI for disease monitoring after diagnosis is not as well established, MRI may provide important prognostic information and help differentiate between relapses and pseudorelapses. Increasing evidence of subclinical disease activity and the emergence of newly approved, highly effective immunotherapies for NMOSD adjure us to re-evaluate MRI as a tool to guide optimal treatment selection and escalation throughout the disease course. In this article we review the role of MRI in NMOSD diagnosis, prognostication, disease monitoring, and treatment selection.
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Affiliation(s)
- Jacqueline M. Solomon
- University of Toronto, Department of Medicine, Toronto, ON, Canada
- St. Michael’s Hospital, Toronto, ON, Canada
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité Universitaetsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité Universitaetsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité Universitaetsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jiwon Oh
- University of Toronto, Department of Medicine, Toronto, ON, Canada
- St. Michael’s Hospital, Toronto, ON, Canada
| | - Dalia L. Rotstein
- St. Michael’s Hospital, 30 Bond Street, Shuter 3-018, Toronto, ON, M5B 1W8, Canada
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Abstract
PURPOSE OF REVIEW To summarize recent evidence from the application of susceptibility-based MRI sequences to investigate the 'central vein sign' (CVS) and 'iron rim' as biomarkers to improve the diagnostic work-up of multiple sclerosis (MS) and predict disease severity. RECENT FINDINGS The CVS is a specific biomarker for MS being detectable from the earliest phase of the disease. A threshold of 40% of lesions with the CVS can be optimal to distinguish MS from non-MS patients. Iron rim lesions, reflecting chronic active lesions, develop in relapsing-remitting MS patients and persist in progressive MS. They increase in size in the first few years after their formation and then stabilize. Iron rim lesions can distinguish MS from non-MS patients but not the different MS phenotypes. The presence of at least four iron rim lesions is associated with an earlier clinical disability, higher prevalence of clinically progressive MS and more severe brain atrophy. Automated methods for CVS and iron rim lesion detection are under development to facilitate their quantification. SUMMARY The assessment of the CVS and iron rim lesions is feasible in the clinical scenario and provides MRI measures specific to MS pathological substrates, improving diagnosis and prognosis of these patients.
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Ciotti JR, Eby NS, Brier MR, Wu GF, Chahin S, Cross AH, Naismith RT. Central vein sign and other radiographic features distinguishing myelin oligodendrocyte glycoprotein antibody disease from multiple sclerosis and aquaporin-4 antibody-positive neuromyelitis optica. Mult Scler 2021; 28:49-60. [PMID: 33870786 DOI: 10.1177/13524585211007086] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) can radiographically mimic multiple sclerosis (MS) and aquaporin-4 (AQP4) antibody-positive neuromyelitis optica spectrum disorder (NMOSD). Central vein sign (CVS) prevalence has not yet been well-established in MOGAD. OBJECTIVE Characterize the magnetic resonance imaging (MRI) appearance and CVS prevalence of MOGAD patients in comparison to matched cohorts of MS and AQP4+ NMOSD. METHODS Clinical MRIs from 26 MOGAD patients were compared to matched cohorts of MS and AQP4+ NMOSD. Brain MRIs were assessed for involvement within predefined regions of interest. CVS was assessed by overlaying fluid-attenuated inversion recovery (FLAIR) and susceptibility-weighted sequences. Topographic analyses were performed on spinal cord and orbital MRIs when available. RESULTS MOGAD patients had fewer brain lesions and average CVS+ rate of 12.1%, compared to 44.4% in MS patients (p = 0.0008). MOGAD spinal cord and optic nerve involvement was lengthier than MS (5.8 vs 1.0 vertebral segments, p = 0.020; 3.0 vs 0.5 cm, p < 0.0001). MOGAD patients tended to have bilateral/anterior optic nerve pathology with perineural contrast enhancement, contrasting with posterior optic nerve involvement in NMOSD. CONCLUSION CVS+ rate and longer segments of involvement in the spinal cord and optic nerve can differentiate MOGAD from MS, but do not discriminate as well between MOGAD and AQP4+ NMOSD.
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Affiliation(s)
- John R Ciotti
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Noah S Eby
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Matthew R Brier
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Gregory F Wu
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Salim Chahin
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne H Cross
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Robert T Naismith
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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Kaisey M, Solomon AJ, Guerrero BL, Renner B, Fan Z, Ayala N, Luu M, Diniz MA, Sati P, Sicotte NL. Preventing multiple sclerosis misdiagnosis using the "central vein sign": A real-world study. Mult Scler Relat Disord 2020; 48:102671. [PMID: 33444958 DOI: 10.1016/j.msard.2020.102671] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/15/2020] [Accepted: 11/30/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND Misdiagnosis of multiple sclerosis (MS) is common and often occurs due to misattribution of non-MS magnetic resonance imaging (MRI) lesions to MS demyelination. A recently developed MRI biomarker, the central vein sign (CVS), has demonstrated high specificity for MS lesions and may thus help prevent misdiagnosis. OBJECTIVE This study explores the potential "real world" diagnostic value of CVS by comparing CVS in patients with MS and patients previously misdiagnosed with MS. METHODS Fifteen patients with MS and 15 misdiagnosed with MS were prospectively recruited to undergo 3T brain MRI. T2-weighted fluid-attenuated inversion recovery (FLAIR) and T2*-weighted segmented echo-planar-imaging (T2*-EPI) were acquired. The generated FLAIR* images were analyzed by two independent raters. The percentage of lesions with CVS was calculated for each patient. RESULTS A CVS lesion threshold of 29% or higher resulted in high sensitivity (0.79) and specificity (0.88) for MS and correctly identified 87% of patients previously misdiagnosed with MS. Interrater reliability for CVS was high with a Cohen's kappa coefficient of 0.86. CONCLUSION This study demonstrates the ability of CVS to differentiate between patients with MS and patients with an MS misdiagnosis resulting from standard MRI and clinical evaluation. Clinical application of CVS may reduce MS misdiagnosis.
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Affiliation(s)
- Marwa Kaisey
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Andrew J Solomon
- Larner College of Medicine at the University of Vermont, Department of Neurological Sciences, 1 South Prospect Street, Arnold, Level 2, Burlington, Vermont 05401, USA.
| | - Brooke L Guerrero
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Brian Renner
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Zhaoyang Fan
- Cedars-Sinai Biomedical Imaging Research Institute, 116 N Robertson Blvd, Los Angeles, CA 90048, USA.
| | - Natalie Ayala
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Michael Luu
- Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA.
| | - Marcio A Diniz
- Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA.
| | - Pascal Sati
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
| | - Nancy L Sicotte
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA.
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Etemadifar M, Ashourizadeh H, Nouri H, Kargaran PK, Salari M, Rayani M, Aghababaee A, Abhari AP. MRI signs of CNS demyelinating diseases. Mult Scler Relat Disord 2020; 47:102665. [PMID: 33310421 DOI: 10.1016/j.msard.2020.102665] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 11/25/2020] [Accepted: 11/28/2020] [Indexed: 11/27/2022]
Abstract
The differential diagnosis of the central nervous system (CNS) demyelinating diseases can be greatly facilitated by visualization and appreciation of pathognomonic radiological signs, visualized on magnetic resonance imaging (MRI) sequences. Given the distinct therapeutic approaches for each of these diseases, a decisive and reliable diagnosis in patients presenting with demyelination-associated symptoms is of crucial value. Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are major examples of such conditions, each possessing a number of MRI signs, closely associated with the disorder. This pictorial review aims to describe seventeen pathognomonic MRI signs associated with several CNS demyelinating disorders including MS, NMOSD, myelin oligodendrocyte glycoprotein-associated disease, Baló's concentric sclerosis, metachromatic leukodystrophy, progressive multifocal leukoencephalopathy, and neurosarcoidosis.
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Affiliation(s)
- Masoud Etemadifar
- Department of Neurosurgery, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Helia Ashourizadeh
- Functional Neurosurgery Research Center, Shohada Tajrish Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hosein Nouri
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran; Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Isfahan, Iran.
| | - Parisa K Kargaran
- Departments of Cardiovascular Medicine, Center for Regenerative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Mehri Salari
- Department of Neurological Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Milad Rayani
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ali Aghababaee
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Amir Parsa Abhari
- Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran; Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Isfahan, Iran
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Castellaro M, Tamanti A, Pisani AI, Pizzini FB, Crescenzo F, Calabrese M. The Use of the Central Vein Sign in the Diagnosis of Multiple Sclerosis: A Systematic Review and Meta-analysis. Diagnostics (Basel) 2020; 10:diagnostics10121025. [PMID: 33260401 PMCID: PMC7760678 DOI: 10.3390/diagnostics10121025] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 11/26/2020] [Accepted: 11/26/2020] [Indexed: 02/01/2023] Open
Abstract
Background: The central vein sign (CVS) is a radiological feature proposed as a multiple sclerosis (MS) imaging biomarker able to accurately differentiate MS from other white matter diseases of the central nervous system. In this work, we evaluated the pooled proportion of the CVS in brain MS lesions and to estimate the diagnostic performance of CVS to perform a diagnosis of MS and propose an optimal cut-off value. Methods: A systematic search was performed on publicly available databases (PUBMED/MEDLINE and Web of Science) up to 24 August 2020. Analysis of the proportion of white matter MS lesions with a central vein was performed using bivariate random-effect models. A meta-regression analysis was performed and the impact of using particular sequences (such as 3D echo-planar imaging) and post-processing techniques (such as FLAIR*) was investigated. Pooled sensibility and specificity were estimated using bivariate models and meta-regression was performed to address heterogeneity. Inclusion and publication bias were assessed using asymmetry tests and a funnel plot. A hierarchical summary receiver operating curve (HSROC) was used to estimate the summary accuracy in diagnostic performance. The Youden index was employed to estimate the optimal cut-off value using individual patient data. Results: The pooled proportion of lesions showing a CVS in the MS population was 73%. The use of the CVS showed a remarkable diagnostic performance in MS cases, providing a pooled specificity of 92% and a sensitivity of 95%. The optimal cut-off value obtained from the individual patient data pooled together was 40% with excellent accuracy calculated by the area under the ROC (0.946). The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. The 1.5 Tesla (T) scanners showed a lower (58%) proportion of MS lesions with a CVS compared to both 3T (74%) and 7T (82%). Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; moreover, the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial.
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Affiliation(s)
- Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
- Correspondence:
| | - Agnese Tamanti
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | - Anna Isabella Pisani
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | | | - Francesco Crescenzo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (A.T.); (A.I.P.); (F.C.); (M.C.)
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Sinnecker T, Clarke MA, Meier D, Enzinger C, Calabrese M, De Stefano N, Pitiot A, Giorgio A, Schoonheim MM, Paul F, Pawlak MA, Schmidt R, Kappos L, Montalban X, Rovira À, Evangelou N, Wuerfel J. Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis. JAMA Neurol 2020; 76:1446-1456. [PMID: 31424490 DOI: 10.1001/jamaneurol.2019.2478] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance The central vein sign has been proposed as a specific imaging biomarker for distinguishing between multiple sclerosis (MS) and not MS, mainly based on findings from ultrahigh-field magnetic resonance imaging (MRI) studies. The diagnostic value of the central vein sign in a multicenter setting with a variety of clinical 3 tesla (T) MRI protocols, however, remains unknown. Objective To evaluate the sensitivity and specificity of various central vein sign lesion criteria for differentiating MS from non-MS conditions using 3T brain MRI with various commonly used pulse sequences. Design, Setting, and Participants This large multicenter, cross-sectional study enrolled participants (n = 648) of ongoing observational studies and patients included in neuroimaging research databases of 8 neuroimaging centers in Europe. Patient enrollment and MRI data collection were performed between January 1, 2010, and November 30, 2016. Data analysis was conducted between January 1, 2016, and April 30, 2018. Investigators were blinded to participant diagnosis by a novel blinding procedure. Main Outcomes and Measures Occurrence of central vein sign was detected on 3T T2*-weighted or susceptibility-weighted imaging. Sensitivity and specificity were assessed for these MRI sequences and for different central vein sign lesion criteria, which were defined by the proportion of lesions with central vein sign or by absolute numbers of lesions with central vein sign. Results A total of 606 participants were included in the study after exclusion of 42 participants. Among the 606 participants, 413 (68.2%) were women. Patients with clinically isolated syndrome and relapsing-remitting MS (RRMS) included 235 women (66.6%) and had a median (range) age of 37 (14.7-61.4) years, a median (range) disease duration of 2 (0-33) years, and a median (range) Expanded Disability Status Scale score of 1.5 (0-6.5). Patients without MS included 178 women (70.4%) and had a median (range) age of 54 (18-83) years. A total of 4447 lesions were analyzed in a total of 487 patients: 690 lesions in 98 participants with clinically isolated syndrome, 2815 lesions in 225 participants with RRMS, 54 lesions in 13 participants with neuromyelitis optica spectrum disorder, 54 lesions in 14 participants with systemic lupus erythematosus, 121 lesions in 29 participants with migraine or cluster headache, 240 lesions in 20 participants with diabetes, and 473 lesions in 88 participants with other types of small-vessel disease. The sensitivity was 68.1% and specificity was 82.9% for distinguishing MS from not MS using a 35% central vein sign proportion threshold. The 3 central vein sign lesion criteria had a sensitivity of 61.9% and specificity of 89.0%. Sensitivity was higher when an optimized T2*-weighted sequence was used. Conclusions and Relevance In this study, use of the central vein sign at 3T MRI yielded a high specificity and a moderate sensitivity in differentiating MS from not MS; international, multicenter studies may be needed to ascertain whether the central vein sign-based criteria can accurately detect MS.
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Affiliation(s)
- Tim Sinnecker
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland.,Medical Image Analysis Center, Basel, Switzerland.,Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Margareta A Clarke
- School of Psychology, University of Nottingham, Nottingham, United Kingdom.,Clinical Neurology, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - Dominik Meier
- Medical Image Analysis Center, Basel, Switzerland.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Christian Enzinger
- Division of Neuroradiology, Vascular and Interventional Radiology, Departments of Neurology and Radiology, Medical University of Graz, Graz, Austria
| | - Massimiliano Calabrese
- Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Alain Pitiot
- Laboratory of Image and Data Analysis, Ilixa Ltd, London, United Kingdom
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Friedemann Paul
- Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Mikolaj A Pawlak
- Department of Neurology and Cerebrovascular Disorders, Poznan University of Medical Sciences, Poznan, Poland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Xavier Montalban
- Section of Neuroradiology, Department of Radiology (IDI), VHIR, Barcelona, Spain.,Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), VHIR, Barcelona, Spain
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, United Kingdom
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland.,Neurocure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.,Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany
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40
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Investigation of the “central vein sign” in infratentorial multiple sclerosis lesions. Mult Scler Relat Disord 2020; 45:102409. [DOI: 10.1016/j.msard.2020.102409] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 07/14/2020] [Accepted: 07/16/2020] [Indexed: 11/20/2022]
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41
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Carnero Contentti E, Rojas JI, Cristiano E, Marques VD, Flores-Rivera J, Lana-Peixoto M, Navas C, Papais-Alvarenga R, Sato DK, Soto de Castillo I, Correale J. Latin American consensus recommendations for management and treatment of neuromyelitis optica spectrum disorders in clinical practice. Mult Scler Relat Disord 2020; 45:102428. [DOI: 10.1016/j.msard.2020.102428] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 02/06/2023]
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42
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Kabaeva AR, Boyko AN, Kulakova OG, Favorova OO. [Radiologically isolated syndrome: prognosis and predictors of conversion to multiple sclerosis]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 120:7-12. [PMID: 32844624 DOI: 10.17116/jnevro20201200727] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Increased sensitivity and availability of magnetic resonance imaging (MRI) in neurological routine practice led to the fact that more and more experts began to encounter changes typical for multiple sclerosis (MS) according to MRI in the absence of anamnestic and clinical indications of damage to the central nervous system (CNS). This nosological form has been defined as a radiologically isolated syndrome (RIS). More and more RIS cases convert to MS (up to 30% in the first 5 years after RIS diagnosis). At the moment, there are no biological markers that allow combining RIS and MS into one pathological process and early treatment with disease-modifying drugs (DMT). Prospective studies are actively being conducted to identify demographic, clinical, neuroimaging and biochemical conversion predictors. The identification of the molecular biological RIS features, combining these changes with MS, is an urgent scientific task and will allow timely initiation of therapy of the pathological process already at the subclinical stage.
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Affiliation(s)
- A R Kabaeva
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - A N Boyko
- Pirogov Russian National Research Medical University, Moscow, Russia.,Federal Center of Cerebrovascular Pathology and Stroke, Moscow, Russia
| | - O G Kulakova
- Pirogov Russian National Research Medical University, Moscow, Russia.,Institute of Experimental Cardiology of National Medical Research Center of Cardiology, Moscow, Russia
| | - O O Favorova
- Pirogov Russian National Research Medical University, Moscow, Russia.,Institute of Experimental Cardiology of National Medical Research Center of Cardiology, Moscow, Russia
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43
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Auger C, Rovira À. New concepts about the role of magnetic resonance imaging in the diagnosis and follow-up of multiple sclerosis. RADIOLOGIA 2020. [DOI: 10.1016/j.rxeng.2020.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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44
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Nuevos conceptos sobre el papel de la resonancia magnética en el diagnóstico y seguimiento de la esclerosis múltiple. RADIOLOGIA 2020; 62:349-359. [DOI: 10.1016/j.rx.2020.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/26/2020] [Accepted: 07/02/2020] [Indexed: 11/24/2022]
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45
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Lv A, Zhang Z, Fu Y, Yan Y, Yang L, Zhu W. Dawson's Fingers in Cerebral Small Vessel Disease. Front Neurol 2020; 11:669. [PMID: 32849175 PMCID: PMC7396560 DOI: 10.3389/fneur.2020.00669] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Accepted: 06/03/2020] [Indexed: 12/12/2022] Open
Abstract
To explore Dawson's fingers in cerebral small vessel disease (CSVD) and factors related to the development of Dawson's finger, we collected and analyzed clinical data of 65 patients with CSVD. We found a venous abnormality feature called Dawson's fingers around the ventricles in magnetic resonance images (MRIs) of 20 out of 65 patients with CSVD (30. 8%). A significant association between Dawson's fingers and diabetes mellitus (DM) was also detected (30 vs. 8.9%, P < 0.05). CSVD patients with Dawson's fingers had significantly increased cerebral microbleeds (CMB) (44.2 vs. 75.0%, p < 0.05), lacunae (66.7 vs. 95.0%, p < 0.05), and white matter hyperintensity (WMH) (p < 0.05) damage, and these patients exhibited significant cognitive domain impairment as assessed via Montreal Cognitive Assessment (MoCA) (18.9 ± 1.8 vs. 24.0 ± 0.8, p < 0.05) and Mini-Mental State Examination (MMSE) (24.5 ± 1.1 vs. 26.6 ± 0.6, p < 0.05). Our results show a distinctly high incidence of Dawson's fingers in CSVD patients and identify a significant association with DM, thus yielding insights about the appropriate use of Dawson's fingers, a venous imaging marker, to explore the basic pathophysiology of CSVD.
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Affiliation(s)
- Aowei Lv
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Zaiqiang Zhang
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ying Fu
- Central Laboratory, Department of Neurology and Institute of Neurology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yaping Yan
- Key Laboratory of the Ministry of Education for Medicinal Resources and Natural Pharmaceutical Chemistry, National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest of China, College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Li Yang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Wenli Zhu
- Central Laboratory, Department of Neurology and Institute of Neurology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
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46
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Kuchling J, Paul F. Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders. Front Neurol 2020; 11:450. [PMID: 32625158 PMCID: PMC7311777 DOI: 10.3389/fneur.2020.00450] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 04/28/2020] [Indexed: 12/12/2022] Open
Abstract
Multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) are autoimmune central nervous system conditions with increasing incidence and prevalence. While MS is the most frequent inflammatory CNS disorder in young adults, NMOSD is a rare disease, that is pathogenetically distinct from MS, and accounts for approximately 1% of demyelinating disorders, with the relative proportion within the demyelinating CNS diseases varying widely among different races and regions. Most immunomodulatory drugs used in MS are inefficacious or even harmful in NMOSD, emphasizing the need for a timely and accurate diagnosis and distinction from MS. Despite distinct immunopathology and differences in disease course and severity there might be considerable overlap in clinical and imaging findings, posing a diagnostic challenge for managing neurologists. Differential diagnosis is facilitated by positive serology for AQP4-antibodies (AQP4-ab) in NMOSD, but might be difficult in seronegative cases. Imaging of the brain, optic nerve, retina and spinal cord is of paramount importance when managing patients with autoimmune CNS conditions. Once a diagnosis has been established, imaging techniques are often deployed at regular intervals over the disease course as surrogate measures for disease activity and progression and to surveil treatment effects. While the application of some imaging modalities for monitoring of disease course was established decades ago in MS, the situation is unclear in NMOSD where work on longitudinal imaging findings and their association with clinical disability is scant. Moreover, as long-term disability is mostly attack-related in NMOSD and does not stem from insidious progression as in MS, regular follow-up imaging might not be useful in the absence of clinical events. However, with accumulating evidence for covert tissue alteration in NMOSD and with the advent of approved immunotherapies the role of imaging in the management of NMOSD may be reconsidered. By contrast, MS management still faces the challenge of implementing imaging techniques that are capable of monitoring progressive tissue loss in clinical trials and cohort studies into treatment algorithms for individual patients. This article reviews the current status of imaging research in MS and NMOSD with an emphasis on emerging modalities that have the potential to be implemented in clinical practice.
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Affiliation(s)
- Joseph Kuchling
- Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- NeuroCure Clinical Research Center, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- NeuroCure Clinical Research Center, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt–Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
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47
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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: 312] [Impact Index Per Article: 62.4] [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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48
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Maggi P, Fartaria MJ, Jorge J, La Rosa F, Absinta M, Sati P, Meuli R, Du Pasquier R, Reich DS, Cuadra MB, Granziera C, Richiardi J, Kober T. CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis. NMR IN BIOMEDICINE 2020; 33:e4283. [PMID: 32125737 PMCID: PMC7754184 DOI: 10.1002/nbm.4283] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/22/2020] [Accepted: 02/05/2020] [Indexed: 05/28/2023]
Abstract
The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS+ ) and 448 CVS-negative (CVS- ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS+ /CVS- lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.
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Affiliation(s)
- Pietro Maggi
- Department of Neurology, Lausanne University Hospital, Lausanne, Switzerland
- Department of Neurology, Saint-Luc University Hospital, Brussels, Belgium
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédéral de Lausanne, Switzerland
| | - João Jorge
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), École Polytechnique Fédéral de Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Renaud Du Pasquier
- Department of Neurology, Lausanne University Hospital, Lausanne, Switzerland
| | - Daniel S. Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), École Polytechnique Fédéral de Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Medical Image Analysis Laboratory (MIAL), Centre d’Imagerie BioMédicale (CIBM), Lausanne, Switzerland
| | - 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 Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jonas Richiardi
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory (LTS5), École Polytechnique Fédéral de Lausanne, Switzerland
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49
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Diagnostic and therapeutic issues of inflammatory diseases of the elderly. Rev Neurol (Paris) 2020; 176:739-749. [PMID: 32312496 DOI: 10.1016/j.neurol.2020.03.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 03/05/2020] [Accepted: 03/06/2020] [Indexed: 11/24/2022]
Abstract
Inflammatory diseases of the central nervous system (CNS) mainly occur during early adulthood and multiple sclerosis (MS) represents the overwhelming majority of these disorders. Nevertheless, MS only rarely begins after 50 years and a diagnosis of late-onset MS should only be done when clinical as well as radiological and biological findings are typical of MS since the probability of misdiagnosis is higher in elderly patients. Indeed, in patients aged over 50 years, along with a relative decrease of MS incidence, other inflammatory diseases of the CNS but also differential diagnoses including neoplastic as well as infectious disorders should be thoroughly searched to avoid diagnostic mistakes and the prescription of inadequate and potentially harmful immunomodulatory/immunosuppressive therapies. Moreover, aging is associated with diverse immune changes also known as immunosenescence resulting in, notably, higher risk of comorbidities (including vascular diseases) and infections which need to be considered when planning medical treatments of elderly patients with inflammatory diseases of the CNS. Herein, therapeutic and diagnostic challenges faced by neurologists are reviewed to ease patient management.
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50
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