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Li X, Zhang J, Zhang S, Shi S, Lu Y, Leng Y, Li C. Biomarkers for neuromyelitis optica: a visual analysis of emerging research trends. Neural Regen Res 2024; 19:2735-2749. [PMID: 38595291 PMCID: PMC11168523 DOI: 10.4103/nrr.nrr-d-24-00109] [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: 01/27/2024] [Revised: 02/04/2024] [Accepted: 02/19/2024] [Indexed: 04/11/2024] Open
Abstract
Neuromyelitis optica is an inflammatory demyelinating disease of the central nervous system that differs from multiple sclerosis. Over the past 20 years, the search for biomarkers for neuromyelitis optica has been ongoing. Here, we used a bibliometric approach to analyze the main research focus in the field of biomarkers for neuromyelitis optica. Research in this area is consistently increasing, with China and the United States leading the way on the number of studies conducted. The Mayo Clinic is a highly reputable institution in the United States, and was identified as the most authoritative institution in this field. Furthermore, Professor Wingerchuk from the Mayo Clinic was the most authoritative expert in this field. Keyword analysis revealed that the terms "neuromyelitis optica" (261 times), "multiple sclerosis" (220 times), "neuromyelitis optica spectrum disorder" (132 times), "aquaporin 4" (99 times), and "optical neuritis" (87 times) were the most frequently used keywords in literature related to this field. Comprehensive analysis of the classical literature showed that the majority of publications provide conclusive research evidence supporting the use of aquaporin-4-IgG and neuromyelitis optica-IgG to effectively diagnose and differentiate neuromyelitis optica from multiple sclerosis. Furthermore, aquaporin-4-IgG has emerged as a highly specific diagnostic biomarker for neuromyelitis optica spectrum disorder. Myelin oligodendrocyte glycoprotein-IgG is a diagnostic biomarker for myelin oligodendrocyte glycoprotein antibody-associated disease. Recent biomarkers for neuromyelitis optica include cerebrospinal fluid immunological biomarkers such as glial fibrillary acidic protein, serum astrocyte damage biomarkers like FAM19A5, serum albumin, and gamma-aminobutyric acid. The latest prospective clinical trials are exploring the potential of these biomarkers. Preliminary results indicate that glial fibrillary acidic protein is emerging as a promising candidate biomarker for neuromyelitis optica spectrum disorder. The ultimate goal of future research is to identify non-invasive biomarkers with high sensitivity, specificity, and safety for the accurate diagnosis of neuromyelitis optica.
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Affiliation(s)
- Xiangjun Li
- Department of Ophthalmology, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
| | - Jiandong Zhang
- Department of Ophthalmology, Changchun Bright Eye Hospital, Changchun, Jilin Province, China
| | - Siqi Zhang
- Department of Ophthalmology, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
| | - Shengling Shi
- Department of Ophthalmology, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
| | - Yi’an Lu
- Department of Ophthalmology, Changchun Bright Eye Hospital, Changchun, Jilin Province, China
| | - Ying Leng
- Department of Ophthalmology, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
| | - Chunyan Li
- Department of Endocrinology, Affiliated Hospital of Beihua University, Jilin, Jilin Province, China
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Karalius M, Mohan S, Paredes D, Rasool N, Bove R. Pearls & Oy-sters: Optic Neuritis as First Demyelinating Event During Pregnancy in 2 Young Hispanic Women: MS vs MOGAD. Neurology 2024; 103:e209706. [PMID: 39052965 DOI: 10.1212/wnl.0000000000209706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024] Open
Abstract
Optic neuritis (ON) can present as the first demyelinating attack in both multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), which may require different treatment depending on the final diagnosis. We present 2 young Hispanic women who presented with ON during pregnancy, one of whom was diagnosed with MS and the other with MOGAD. We describe key clinical features to help differentiate between MS and MOGAD including ON features, brain and spinal MRI, CSF profiles, and serum MOG and aquaporin-4 (AQP-4) antibodies, which all can help guide clinicians to an ultimate diagnosis. Pregnancy is usually considered an immunotolerant state because complex immunologic shifts arising to support tolerance of the developing fetus seem to decrease the risk of relapses. However, relapses may still occur during pregnancy, and relapse rates increase immediately postpartum. Our cases raise the possibility that young Hispanic patients may face increased risk of demyelinating disease activity even during the relatively immunotolerant state of pregnancy. A high index of suspicion for demyelinating disease should be maintained to accelerate diagnosis and prevent disability.
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Affiliation(s)
- Mary Karalius
- From the UCSF Weill Institute for Neurosciences (M.K., S.M., D.P., R.B.), Department of Neurology, University of California; and Department of Ophthalmology (N.R.), University of California, San Francisco
| | - Sonam Mohan
- From the UCSF Weill Institute for Neurosciences (M.K., S.M., D.P., R.B.), Department of Neurology, University of California; and Department of Ophthalmology (N.R.), University of California, San Francisco
| | - Danelvis Paredes
- From the UCSF Weill Institute for Neurosciences (M.K., S.M., D.P., R.B.), Department of Neurology, University of California; and Department of Ophthalmology (N.R.), University of California, San Francisco
| | - Nailyn Rasool
- From the UCSF Weill Institute for Neurosciences (M.K., S.M., D.P., R.B.), Department of Neurology, University of California; and Department of Ophthalmology (N.R.), University of California, San Francisco
| | - Riley Bove
- From the UCSF Weill Institute for Neurosciences (M.K., S.M., D.P., R.B.), Department of Neurology, University of California; and Department of Ophthalmology (N.R.), University of California, San Francisco
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Kizaki T, Kanazawa M, Ishiguro T, Natsumeda M, Tada M, Shimizu H, Okamoto K, Oishi M, Kakita A, Fujii Y, Onodera O. Indications for a brain biopsy in neurological diseases of unknown etiology: The role of magnetic resonance imaging findings and liquid biopsy in yielding definitive pathological diagnoses. J Neurol Sci 2024; 463:123150. [PMID: 39067261 DOI: 10.1016/j.jns.2024.123150] [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: 05/24/2024] [Revised: 07/19/2024] [Accepted: 07/21/2024] [Indexed: 07/30/2024]
Abstract
Brain biopsies are often considered for patients who cannot be diagnosed with various laboratory test results. However, physicians tend to be hesitant regarding their application in possibly non-neoplastic brain diseases, due to the invasiveness and risks. The aim was to determine the indications for brain biopsies in cases of neurological diseases of unknown etiology. We retrospectively evaluated diagnostic accuracy, laboratory findings (including a liquid biopsy for malignant lymphoma), magnetic resonance imaging (MRI) characteristics and the post-treatment outcomes of patients undergoing brain biopsies for neurological diseases of unknown etiology. The data of patients who had undergone a brain biopsy during their admission to Niigata University Hospital, between 2011 and 2024, were reviewed. Moreover, the laboratory data and MRI findings between patients with definitive and nonspecific biopsy diagnoses were compared. Twenty-six patients underwent a brain biopsy, and a definitive diagnosis was obtained in 14 patients (53.8%). Even in cases where a nonspecific diagnosis was made, biopsy findings helped rule out malignancy and guide clinical diagnosis and treatment decisions. The liquid biopsy for malignant lymphoma was performed in eight patients, with one yielding a positive result, consistent with primary central nervous system lymphoma. The sensitivity and specificity of liquid biopsy were 0.5 and 1, respectively. Diffusely contrasted cortical lesions and the presence of mass effects on MRI, were significantly associated with a definitive diagnosis, compared to a nonspecific diagnosis. In conclusion, brain MRI and liquid biopsies can assist in determining the appropriate indications for brain biopsies in neurological diseases of unknown etiology.
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Affiliation(s)
- Toshiya Kizaki
- Department of Neurology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Masato Kanazawa
- Department of Neurology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan.
| | - Takanobu Ishiguro
- Department of Neurology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Manabu Natsumeda
- Department of Neurosurgery, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Mari Tada
- Department of Pathology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Hiroshi Shimizu
- Department of Pathology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Kouichirou Okamoto
- Department of Neurosurgery, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Makoto Oishi
- Department of Neurosurgery, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Yukihiko Fujii
- Department of Neurosurgery, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
| | - Osamu Onodera
- Department of Neurology, Brain Research Institute, Niigata University, 1-757 Asahimachi-dori, Niigata 951-8585, Japan
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Stefan KA, Ciotti JR. MOG Antibody Disease: Nuances in Presentation, Diagnosis, and Management. Curr Neurol Neurosci Rep 2024; 24:219-232. [PMID: 38805147 DOI: 10.1007/s11910-024-01344-z] [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] [Accepted: 05/16/2024] [Indexed: 05/29/2024]
Abstract
PURPOSE OF REVIEW Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a distinct neuroinflammatory condition characterized by attacks of optic neuritis, transverse myelitis, and other demyelinating events. Though it can mimic multiple sclerosis and neuromyelitis optica spectrum disorder, distinct clinical and radiologic features which can discriminate these conditions are now recognized. This review highlights recent advances in our understanding of clinical manifestations, diagnosis, and treatment of MOGAD. RECENT FINDINGS Studies have identified subtleties of common clinical attacks and identified more rare phenotypes, including cerebral cortical encephalitis, which have broadened our understanding of the clinicoradiologic spectrum of MOGAD and culminated in the recent publication of proposed diagnostic criteria with a familiar construction to those diagnosing other neuroinflammatory conditions. These criteria, in combination with advances in antibody testing, should simultaneously lead to wider recognition and reduced incidence of misdiagnosis. In addition, recent observational studies have raised new questions about when to treat MOGAD chronically, and with which agent. MOGAD pathophysiology informs some of the relatively unique clinical and radiologic features which have come to define this condition, and similarly has implications for diagnosis and management. Further prospective studies and the first clinical trials of therapeutic options will answer several remaining questions about the peculiarities of this condition.
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Affiliation(s)
- Kelsey A Stefan
- Department of Neurology, University of South Florida, 13330 USF Laurel Drive, Tampa, FL, 33612, USA
| | - John R Ciotti
- Department of Neurology, University of South Florida, 13330 USF Laurel Drive, Tampa, FL, 33612, USA.
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Cortese R, Battaglini M, Prados F, Gentile G, Luchetti L, Bianchi A, Haider L, Jacob A, Palace J, Messina S, Paul F, Marignier R, Durand-Dubief F, de Medeiros Rimkus C, Apostolos Pereira SL, Sato DK, Filippi M, Rocca MA, Cacciaguerra L, Rovira À, Sastre-Garriga J, Arrambide G, Liu Y, Duan Y, Gasperini C, Tortorella C, Ruggieri S, Amato MP, Ulivelli M, Groppa S, Grothe M, Llufriu S, Sepulveda M, Lukas C, Bellenberg B, Schneider R, Sowa P, Celius EG, Pröbstel AK, Granziera C, Yaldizli Ö, Müller J, Stankoff B, Bodini B, Barkhof F, Ciccarelli O, De Stefano N. Grey Matter Atrophy and its Relationship with White Matter Lesions in Patients with Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease, Aquaporin-4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder, and Multiple Sclerosis. Ann Neurol 2024; 96:276-288. [PMID: 38780377 DOI: 10.1002/ana.26951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 04/16/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE To evaluate: (1) the distribution of gray matter (GM) atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD), and relapsing-remitting multiple sclerosis (RRMS); and (2) the relationship between GM volumes and white matter lesions in various brain regions within each disease. METHODS A retrospective, multicenter analysis of magnetic resonance imaging data included patients with MOGAD/AQP4+NMOSD/RRMS in non-acute disease stage. Voxel-wise analyses and general linear models were used to evaluate the relevance of regional GM atrophy. For significant results (p < 0.05), volumes of atrophic areas are reported. RESULTS We studied 135 MOGAD patients, 135 AQP4+NMOSD, 175 RRMS, and 144 healthy controls (HC). Compared with HC, MOGAD showed lower GM volumes in the temporal lobes, deep GM, insula, and cingulate cortex (75.79 cm3); AQP4+NMOSD in the occipital cortex (32.83 cm3); and RRMS diffusely in the GM (260.61 cm3). MOGAD showed more pronounced temporal cortex atrophy than RRMS (6.71 cm3), whereas AQP4+NMOSD displayed greater occipital cortex atrophy than RRMS (19.82 cm3). RRMS demonstrated more pronounced deep GM atrophy in comparison with MOGAD (27.90 cm3) and AQP4+NMOSD (47.04 cm3). In MOGAD, higher periventricular and cortical/juxtacortical lesions were linked to reduced temporal cortex, deep GM, and insula volumes. In RRMS, the diffuse GM atrophy was associated with lesions in all locations. AQP4+NMOSD showed no lesion/GM volume correlation. INTERPRETATION GM atrophy is more widespread in RRMS compared with the other two conditions. MOGAD primarily affects the temporal cortex, whereas AQP4+NMOSD mainly involves the occipital cortex. In MOGAD and RRMS, lesion-related tract degeneration is associated with atrophy, but this link is absent in AQP4+NMOSD. ANN NEUROL 2024;96:276-288.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- Queen Square MS Center, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- SIENA imaging SRL, Siena, Italy
| | - Ferran Prados
- Queen Square MS Center, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Center for Medical Imaging Computing, Medical Physics, and Biomedical Engineering, UCL, London, UK
- E-Health Center University Oberta de Catalunya, Barcelona, Spain
| | - Giordano Gentile
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- SIENA imaging SRL, Siena, Italy
| | - Ludovico Luchetti
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
- SIENA imaging SRL, Siena, Italy
| | - Alessia Bianchi
- Queen Square MS Center, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Lukas Haider
- Queen Square MS Center, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Anu Jacob
- NMO Clinical Service at the Walton Centre, Liverpool, UK
- Department of Neurology, Cleveland Clinic, Abu Dhabi, UAE
| | - Jacqueline Palace
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - Silvia Messina
- Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Romain Marignier
- Department of Neurology, Multiple Sclerosis, Myelin Disorders, and Neuro-inflammation, Pierre Wertheimer Neurological Hospital, Hospices Civils de Lyon, Lyon, France
| | - Françoise Durand-Dubief
- Department of Neurology, Multiple Sclerosis, Myelin Disorders, and Neuro-inflammation, Pierre Wertheimer Neurological Hospital, Hospices Civils de Lyon, Lyon, France
| | - Carolina de Medeiros Rimkus
- Department of Radiology and Oncology, Faculty of Medicine, University of São Paulo (FMUSP), São Paulo, Brazil
| | | | - Douglas Kazutoshi Sato
- Pontifical Catholic University of Rio Grande do Sul (PUCRS), School of Medicine, Porto Alegre, Brazil
| | - 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
| | - Maria Assunta 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
| | - Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Georgina Arrambide
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Claudio Gasperini
- Department of Neurosciences, S. Camillo-Forlanini Hospital, Rome, Italy
| | - Carla Tortorella
- Department of Neurosciences, S. Camillo-Forlanini Hospital, Rome, Italy
| | - Serena Ruggieri
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Maria Pia Amato
- Department Neurofarba, University of Florence, Florence, Italy
- IRCCS Don Carlo Gnocchi Foundation, Florence, Italy
| | - Monica Ulivelli
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Sergiu Groppa
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Matthias Grothe
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Sara Llufriu
- Service of Neurology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Center of Neuroimmunology, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), and Universitat de Barcelona, Barcelona, Spain
| | - Maria Sepulveda
- Service of Neurology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Center of Neuroimmunology, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), and Universitat de Barcelona, Barcelona, Spain
| | - Carsten Lukas
- Institute of Neuroradiology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Barbara Bellenberg
- Institute of Neuroradiology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ruth Schneider
- Institute of Neuroradiology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Elisabeth G Celius
- Department of Neurology, Oslo University Hospital and Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Anne-Katrin Pröbstel
- Department of Neurology, Biomedicine and Clinical Research, and Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Department of Neurology, Biomedicine and Clinical Research, and Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Özgür Yaldizli
- Department of Neurology, Biomedicine and Clinical Research, and Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
| | - Jannis Müller
- Department of Neurology, Biomedicine and Clinical Research, and Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Bruno Stankoff
- Sorbonne University, Paris Brain Institute, ICM, Pitié Salpêtrière Hospital, Paris, France
| | - Benedetta Bodini
- Sorbonne University, Paris Brain Institute, ICM, Pitié Salpêtrière Hospital, Paris, France
| | - Frederik Barkhof
- Center for Medical Imaging Computing, Medical Physics, and Biomedical Engineering, UCL, London, UK
- Radiology & Nuclear medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Olga Ciccarelli
- Queen Square MS Center, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Center, London, UK
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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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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7
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Sechi E. NMOSD and MOGAD. Continuum (Minneap Minn) 2024; 30:1052-1087. [PMID: 39088288 DOI: 10.1212/con.0000000000001454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2024]
Abstract
OBJECTIVE This article reviews the clinical features, MRI characteristics, diagnosis, and treatment of aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). The main differences between these disorders and multiple sclerosis (MS), the most common demyelinating disease of the central nervous system (CNS), are also highlighted. LATEST DEVELOPMENTS The past 20 years have seen important advances in understanding rare demyelinating CNS disorders associated with AQP4 IgG and myelin oligodendrocyte glycoprotein (MOG) IgG. The rapidly expanding repertoire of immunosuppressive agents approved for the treatment of AQP4-NMOSD and emerging as potentially beneficial in MOGAD mandates prompt recognition of these diseases. Most of the recent literature has focused on the identification of clinical and MRI features that help distinguish these diseases from each other and MS, simultaneously highlighting major diagnostic pitfalls that may lead to misdiagnosis. An awareness of the limitations of currently available assays for AQP4 IgG and MOG IgG detection is fundamental for identifying rare false antibody positivity and avoiding inappropriate treatments. For this purpose, diagnostic criteria have been created to help the clinician interpret antibody testing results and recognize the clinical and MRI phenotypes associated with AQP4-NMOSD and MOGAD. ESSENTIAL POINTS An awareness of the specific clinical and MRI features associated with AQP4-NMOSD and MOGAD and the limitations of currently available antibody testing assays is crucial for a correct diagnosis and differentiation from MS. The growing availability of effective treatment options will lead to personalized therapies and improved outcomes.
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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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9
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Hemond CC, Gaitán MI, Absinta M, Reich DS. New Imaging Markers in Multiple Sclerosis and Related Disorders: Smoldering Inflammation and the Central Vein Sign. Neuroimaging Clin N Am 2024; 34:359-373. [PMID: 38942521 PMCID: PMC11213979 DOI: 10.1016/j.nic.2024.03.004] [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: 06/30/2024]
Abstract
Concepts of multiple sclerosis (MS) biology continue to evolve, with observations such as "progression independent of disease activity" challenging traditional phenotypic categorization. Iron-sensitive, susceptibility-based imaging techniques are emerging as highly translatable MR imaging sequences that allow for visualization of at least 2 clinically useful biomarkers: the central vein sign and the paramagnetic rim lesion (PRL). Both biomarkers demonstrate high specificity in the discrimination of MS from other mimics and can be seen at 1.5 T and 3 T field strengths. Additionally, PRLs represent a subset of chronic active lesions engaged in "smoldering" compartmentalized inflammation behind an intact blood-brain barrier.
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Affiliation(s)
- Christopher C Hemond
- Department of Neurology, University of Massachusetts Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA; National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
| | - María I Gaitán
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Martina Absinta
- Translational Neuropathology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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10
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Manzano GS, Levy M, Salky R, Mateen FJ, Klawiter EC, Chitnis T, Vasileiou ES, Sotirchos ES, Gibbons E, Huda S, Jacob A, Matiello M. Assessment of international MOGAD diagnostic criteria in patients with overlapping MOG-associated disease and multiple sclerosis phenotypes. J Neurol 2024:10.1007/s00415-024-12585-w. [PMID: 39066792 DOI: 10.1007/s00415-024-12585-w] [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: 05/09/2024] [Revised: 07/11/2024] [Accepted: 07/13/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND The clinical spectrum and diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) has evolved in the setting of an optimized anti-MOG-IgG cell-based assay and expert consensus. The McDonald criteria for MS have been revised multiple times to improve the accuracy and specificity of diagnosis on a framework based on clinical presentation, MRI findings, and CSF results. While the uses of MS and MOGAD diagnostic criteria are helpful for typical cases, such utility for patients with overlapping clinical, laboratorial, and imaging features is unknown, posing diagnostic and management uncertainties. OBJECTIVES To report a multicenter cohort of patients with overlapping phenotypic features of MOGAD and MS and evaluate the application of new MOGAD diagnostic criteria. METHODS A collaborative retrospective cohort study was performed to identify patients with both positive serum anti-MOG-IgG and fulfillment of the MS revised 2017 McDonald criteria. Clinical and radiographic features of patients fulfilling inclusion criteria were reviewed longitudinally, including relapses, repeated MRI, and MOG-IgG testing in detail to allow the panel of expert opinion to assign to each case. The International MOGAD Panel proposed criteria were applied at onset and last follow-up to each case and compared to the expert author diagnosis assignment based on presentation, clinical and imaging features, and response to treatment. RESULTS Ten of 225 (4%) MOG-IgG seropositive cases met study inclusion criteria [seven of 10 were female; age at initial event: eight adults (mean age 26.8 years), two adolescents (mean age 14.5 years)]. AQP4-IgG was negative for all. Apart from serum titers of MOG-IgG, distinguishing clinical and radiographic features [i.e., clinical severity of the initial demyelinating event, radiographic features (optic nerve/spine/brain), and presence/absence of lesion normalization on serial scans] led to consensus of three separate classifications differing by degrees of shared features of MOGAD and MS. Patients were classified by expert panel into (1) Classic MOGAD even with MS-like, well-defined brain lesions, when severe events and most T2 lesions normalized (n = 5; MOG-IgG titers 1:100, 1:20, 1:160, 1:40, 1:200); (2) Classic RRMS included cases thought to have likely false positive or clinically irrelevant MOG-IgG, due to mild clinical events and no radiographic normalization of well-defined MS-like lesions (n = 3; MOG titers 1:20, 1:100, 1:40); (3) MOGAD and MS overlapping phenotype was defined by those with a combination of mild and severe clinical events, partial T2 lesion normalization, both well- and ill-defined lesions (n = 2; MOG titers 1:20, 1:100). The application of the International MOGAD Panel criteria categorized five patients (50%) in agreement with expert assignment. One additional patient was classified in agreement to assignment when MOGAD criteria were applied after serial MOG-IgG titers testing. DISCUSSION While the International MOGAD Panel diagnostic criteria have helped with accuracy for the diagnosis of this condition, in a group of patients seropositive for MOG-IgG with overlapping clinical and imaging features of RRMS criteria review may lead to increased accuracy. Serial serologies, repeated imaging, close attention to clinical course, and response to therapy are possible variables to consider for further refinement of MOGAD diagnostic criteria.
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Affiliation(s)
- Giovanna S Manzano
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
- Department of Neurology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael Levy
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
| | - Rebecca Salky
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
| | - Farrah J Mateen
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
| | - Eric C Klawiter
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
| | - Tanuja Chitnis
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA
- Department of Neurology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | - Eleni S Vasileiou
- Department of Neurology, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Elias S Sotirchos
- Department of Neurology, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | | | - Saif Huda
- Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Anu Jacob
- Section of Multiple Sclerosis and Autoimmune Neurology, Cleveland Clinic, Abu Dhabi, United Arab Emirates
| | - Marcelo Matiello
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, 15 Parkman Street, Wang 8-835, Boston, MA, 02114, USA.
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11
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Rovira À, Auger C, Sceppacuercia S, Torres C. Typical and Emerging Diagnostic MRI Features in Multiple Sclerosis. Can Assoc Radiol J 2024:8465371241261847. [PMID: 39044390 DOI: 10.1177/08465371241261847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024] Open
Abstract
Magnetic resonance imaging (MRI) stands as the most sensitive paraclinical technique for detecting the demyelinating lesions characteristic of multiple sclerosis (MS). Consequently, MRI plays a pivotal role in establishing an accurate and timely diagnosis of the disease, ultimately based on the application of the McDonald criteria. Early diagnosis is particularly important as it facilitates the prompt initiation of disease-modifying treatments, deemed most effective during the initial phases of MS. This review article examines the recommended standardized MRI protocol, as well as the classic imaging features of MS in the brain, optic nerve, and spinal cord, capable of discriminating, in most cases, MS from other disorders that can mimic this disease. Additionally, novel MR imaging findings, such as the central vein sign and paramagnetic rim lesion, which have been proposed as new imaging biomarkers to enhance diagnostic specificity for MS, are also discussed. These emerging features are likely to be incorporated in the future iterations of the McDonald criteria, and therefore, radiologists should be familiar with their appearance and with the optimal MRI protocols required for their detection.
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Affiliation(s)
- Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Autonomous University of Barcelona, Barcelona, Spain
- Vall d'Hebron Research Institute, Barcelona, Spain
| | - Cristina Auger
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Autonomous University of Barcelona, Barcelona, Spain
- Vall d'Hebron Research Institute, Barcelona, Spain
| | | | - Carlos Torres
- Department of Radiology, University of Ottawa, The Ottawa Hospital Civic and General Campus, Ottawa, ON, Canada
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12
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Tzanetakos D, Tzartos JS, Velonakis G, Giannopoulos S, Tsivgoulis G. Neuromyelitis optica spectrum disorder-associated myelitis mimicking intramedullary neoplasm as a diagnostic pitfall: a case report. Neurol Sci 2024:10.1007/s10072-024-07684-5. [PMID: 38985372 DOI: 10.1007/s10072-024-07684-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 07/04/2024] [Indexed: 07/11/2024]
Affiliation(s)
- Dimitrios Tzanetakos
- Second Department of Neurology, "Attikon" University Hospital, National and Kapodistrian University of Athens, Athens, Greece.
| | - John S Tzartos
- Second Department of Neurology, "Attikon" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Georgios Velonakis
- Research Unit of Radiology, Second Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Sotirios Giannopoulos
- Second Department of Neurology, "Attikon" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Georgios Tsivgoulis
- Second Department of Neurology, "Attikon" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
- Department of Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
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13
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Borrelli S, Martire MS, Stölting A, Vanden Bulcke C, Pedrini E, Guisset F, Bugli C, Yildiz H, Pothen L, Elands S, Martinelli V, Smith B, Jacobson S, Du Pasquier RA, Van Pesch V, Filippi M, Reich DS, Absinta M, Maggi P. Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200253. [PMID: 38788180 PMCID: PMC11129678 DOI: 10.1212/nxi.0000000000200253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/13/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND AND OBJECTIVES The diagnosis of multiple sclerosis (MS) can be challenging in clinical practice because MS presentation can be atypical and mimicked by other diseases. We evaluated the diagnostic performance, alone or in combination, of the central vein sign (CVS), paramagnetic rim lesion (PRL), and cortical lesion (CL), as well as their association with clinical outcomes. METHODS In this multicenter observational study, we first conducted a cross-sectional analysis of the CVS (proportion of CVS-positive lesions or simplified determination of CVS in 3/6 lesions-Select3*/Select6*), PRL, and CL in MS and non-MS cases on 3T-MRI brain images, including 3D T2-FLAIR, T2*-echo-planar imaging magnitude and phase, double inversion recovery, and magnetization prepared rapid gradient echo image sequences. Then, we longitudinally analyzed the progression independent of relapse and MRI activity (PIRA) in MS cases over the 2 years after study entry. Receiver operating characteristic curves were used to test diagnostic performance and regression models to predict diagnosis and clinical outcomes. RESULTS The presence of ≥41% CVS-positive lesions/≥1 CL/≥1 PRL (optimal cutoffs) had 96%/90%/93% specificity, 97%/84%/60% sensitivity, and 0.99/0.90/0.77 area under the curve (AUC), respectively, to distinguish MS (n = 185) from non-MS (n = 100) cases. The Select3*/Select6* algorithms showed 93%/95% specificity, 97%/89% sensitivity, and 0.95/0.92 AUC. The combination of CVS, CL, and PRL improved the diagnostic performance, especially when Select3*/Select6* were used (93%/94% specificity, 98%/96% sensitivity, 0.99/0.98 AUC; p = 0.002/p < 0.001). In MS cases (n = 185), both CL and PRL were associated with higher MS disability and severity. Longitudinal analysis (n = 61) showed that MS cases with >4 PRL at baseline were more likely to experience PIRA at 2-year follow-up (odds ratio 17.0, 95% confidence interval: 2.1-138.5; p = 0.008), whereas no association was observed between other baseline MRI measures and PIRA, including the number of CL. DISCUSSION The combination of CVS, CL, and PRL can improve MS differential diagnosis. CL and PRL also correlated with clinical measures of poor prognosis, with PRL being a predictor of disability accrual independent of clinical/MRI activity.
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Affiliation(s)
- Serena Borrelli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Maria Sofia Martire
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Anna Stölting
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Colin Vanden Bulcke
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Edoardo Pedrini
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - François Guisset
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Céline Bugli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Halil Yildiz
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lucie Pothen
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Sophie Elands
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Vittorio Martinelli
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Bryan Smith
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Steven Jacobson
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Renaud A Du Pasquier
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Vincent Van Pesch
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Massimo Filippi
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Daniel S Reich
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Martina Absinta
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Pietro Maggi
- From the Neuroinflammation Imaging Lab (NIL) (S.B., A.S., C.V.B., F.G., P.M.), Institute of NeuroScience, Université catholique de Louvain; Department of Neurology (S.B., S.E.), Hôpital Erasme, Hôpital Universitaire de Bruxelles; Department of Neurology (S.B.), Centre Hospitalier Universitaire Brugmann, Université Libre de Brussels, Belgium; Neurology Unit (M.S.M., V.M., M.F.), IRCCS San Raffaele Hospital, Milan, Italy; ICTEAM Institute (C.V.B.), Université catholique de Louvain, Louvain-la-Neuve, Belgium; Vita-Salute San Raffaele University (E.P., M.F., M.A.); Translational Neuropathology Unit (E.P., M.A.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Plateforme technologique de Support en Méthodologie et Calcul Statistique (C.B.); Department of Internal Medicine and Infectious Diseases (H.Y., L.P.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Section of Infections of the Nervous System (B.S.); Viral Immunology Section (S.J.), National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD; Neurology Service (R.A.D.P., P.M.), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Switzerland; Department of Neurology (V.V.P., P.M.), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Neuroimaging Research Unit (M.F.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Translational Neuroradiology Section (D.S.R.), National Institute of Neurological Disorders and Stroke (NINDS), National In-stitutes of Health (NIH); and Department of Neurology (M.A.), Johns Hopkins University School of Medicine, Baltimore, MD
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Luo X, Li H, Xia W, Quan C, ZhangBao J, Tan H, Wang N, Bao Y, Geng D, Li Y, Yang L. Joint radiomics and spatial distribution model for MRI-based discrimination of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder. Eur Radiol 2024; 34:4364-4375. [PMID: 38127076 DOI: 10.1007/s00330-023-10529-y] [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: 03/01/2023] [Revised: 10/26/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023]
Abstract
OBJECTIVE To develop a discrimination pipeline concerning both radiomics and spatial distribution features of brain lesions for discrimination of multiple sclerosis (MS), aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder (NMOSD), and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder (MOGAD). METHODS Hyperintensity T2 lesions were delineated in 212 brain MRI scans of MS (n = 63), NMOSD (n = 87), and MOGAD (n = 45) patients. To avoid the effect of fixed training/test dataset sampling when developing machine learning models, patients were allocated into 4 sub-groups for cross-validation. For each scan, 351 radiomics and 27 spatial distribution features were extracted. Three models, i.e., multi-lesion radiomics, spatial distribution, and joint models, were constructed using random forest and logistic regression algorithms for differentiating: MS from the others (MS models) and MOGAD from NMOSD (MOG-NMO models), respectively. Then, the joint models were combined with demographic characteristics (i.e., age and sex) to create MS and MOG-NMO discriminators, respectively, based on which a three-disease discrimination pipeline was generated and compared with radiologists. RESULTS For classification of both MS-others and MOG-NMO, the joint models performed better than radiomics or spatial distribution model solely. The MS discriminator achieved AUC = 0.909 ± 0.027 and bias-corrected C-index = 0.909 ± 0.027, and the MOG-NMO discriminator achieved AUC = 0.880 ± 0.064 and bias-corrected C-index = 0.883 ± 0.068. The three-disease discrimination pipeline differentiated MS, NMOSD, and MOGAD patients with 75.0% accuracy, prominently outperforming the three radiologists (47.6%, 56.6%, and 66.0%). CONCLUSIONS The proposed pipeline integrating multi-lesion radiomics and spatial distribution features could effectively differentiate MS, NMOSD, and MOGAD. CLINICAL RELEVANCE STATEMENT The discrimination pipeline merging both radiomics and spatial distribution features of brain lesions may facilitate the differential diagnoses of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder. KEY POINTS • Our study introduces an approach by combining radiomics and spatial distribution models. • The joint model exhibited superior performance in distinguishing multiple sclerosis from aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorder and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder as well as discriminating the latter two diseases. • The three-disease discrimination pipeline showcased remarkable accuracy, surpassing the performance of experienced radiologists, highlighting its potential as a valuable diagnostic tool.
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Affiliation(s)
- Xiao Luo
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Haiqing Li
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China
| | - Wei Xia
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Chao Quan
- Department of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jingzi ZhangBao
- Department of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hongmei Tan
- Department of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Na Wang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China
| | - Yifang Bao
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China
| | - Daoying Geng
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China.
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China.
| | - Liqin Yang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China.
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China.
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15
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Etemadifar M, Norouzi M, Alaei SA, Karimi R, Salari M. The diagnostic performance of AI-based algorithms to discriminate between NMOSD and MS using MRI features: A systematic review and meta-analysis. Mult Scler Relat Disord 2024; 87:105682. [PMID: 38781885 DOI: 10.1016/j.msard.2024.105682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 04/28/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Magnetic resonance imaging [MRI] findings in Neuromyelitis optica spectrum disorder [NMOSD] and Multiple Sclerosis [MS] patients could lead us to discriminate toward them. For instance, U-fiber and Dawson's finger-type lesions are suggestive of MS, however linear ependymal lesions raise the possibility of NMOSD. Recently, artificial intelligence [AI] models have been used to discriminate between NMOSD and MS based on MRI features. In this study, we aim to systematically review the capability of AI algorithms in NMOSD and MS discrimination based on MRI features. METHOD We searched PubMed, Scopus, Web of Sciences, Embase, and IEEE databases up to August 2023. All studies that used AI-based algorithms to discriminate between NMOSD and MS using MRI features were included, without any restriction in time, region, race, and age. Data on NMOSD and MS patients, Aquaporin-4 antibodies [AQP4-Ab] status, diagnosis criteria, performance metrics (accuracy, sensitivity, specificity, and AUC), artificial intelligence paradigm, MR imaging, and used features were extracted. This study is registered with PROSPERO, CRD42023465265. RESULTS Fifteen studies were included in this systematic review, with sample sizes ranging between 53 and 351. 1,362 MS patients and 1,118 NMOSD patients were included in our systematic review. AQP4-Ab was positive in 94.9% of NMOSD patients in 9 studies. Eight studies used machine learning [ML] as a classifier, while 7 used deep learning [DL]. AI models based on only MRI or MRI and clinical features yielded a pooled accuracy of 82% (95% CI: 78-86%), sensitivity of 83% (95% CI: 79-88%), and specificity of 80% (95% CI: 75-86%). In subgroup analysis, using only MRI features yielded an accuracy, sensitivity, and specificity of 83% (95% CI: 78-88%), 81% (95% CI: 76-87%), and 84% (95% CI: 79-89%), respectively. CONCLUSION AI models based on MRI features showed a high potential to discriminate between NMOSD and MS. However, heterogeneity in MR imaging, model evaluation, and reporting performance metrics, among other confounders, affected the reliability of our results. Well-designed studies on multicentric datasets, standardized imaging and evaluation protocols, and detailed transparent reporting of results are needed to reach optimal performance.
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Affiliation(s)
- Masoud Etemadifar
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahdi Norouzi
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Seyyed-Ali Alaei
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Raheleh Karimi
- Department of Epidemiology and Biostatistics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Salari
- Functional Neurosurgery Research Center, Shohada Tajrish Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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16
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Lorefice L, Cortese R. Brain and spinal cord atrophy in NMOSD and MOGAD: Current evidence and future perspectives. Mult Scler Relat Disord 2024; 85:105559. [PMID: 38554671 DOI: 10.1016/j.msard.2024.105559] [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: 01/22/2024] [Revised: 02/26/2024] [Accepted: 03/18/2024] [Indexed: 04/02/2024]
Abstract
Neuromyelitis optica spectrum disorder (NMOSD) is a severe form of inflammation of the central nervous system (CNS) including acute myelitis, optic neuritis and brain syndrome. Currently, the classification of NMOSD relies on serologic testing, distinguishing between seropositive or seronegative anti-aquaporin-4 antibody (AQP4) status. However, the situation has recently grown more intricate with the identification of patients exhibiting the NMOSD phenotype and myelin oligodendrocyte glycoprotein antibodies (MOGAD). NMOSD is primarily recognized as a relapsing disorder; MOGAD can manifest with either a monophasic or relapsing course. Significant symptomatic inflammatory CNS injuries with stability in clinical findings outside the acute phase are reported in both diseases. Nevertheless, recent studies have proposed the existence of a subclinical pathological process, revealing longitudinal changes in brain and spinal cord atrophy. Within this context, we summarise key studies investigating brain and spinal cord measurements in adult NMOSD and MOGAD. We also explore their relationship with clinical aspects, highlight differences from multiple sclerosis (MS), and address future challenges. This exploration is crucial for determining the presence of chronic damage processes, enabling the customization of therapeutic interventions irrespective of the acute phase of the disease.
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Affiliation(s)
- L Lorefice
- Department of Medical Sciences and Public Health, Multiple Sclerosis Center, Binaghi Hospital, ASL Cagliari, University of Cagliari, Via Is Guadazzonis 2, Cagliari 09126, Italy.
| | - R Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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17
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Nguyen P, Rempe T, Forghani R. Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting. Magn Reson Imaging Clin N Am 2024; 32:363-374. [PMID: 38555146 DOI: 10.1016/j.mric.2024.01.001] [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: 04/02/2024]
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.
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Affiliation(s)
- Phuong Nguyen
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA
| | - Torge Rempe
- Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA
| | - Reza Forghani
- Department of Radiology, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Division of Movement Disorders, Department of Neurology, University of Florida College of Medicine, Norman Fixel Institute for Neurological Diseases, 3009 SW Williston Road, Gainesville, FL 32608, USA; Division of Medical Physics, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL 32610-0374, USA; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Room 221.1, 3011 SW Williston Road, Gainesville, FL 32608, USA.
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18
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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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19
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Yao M, Wang W, Sun J, Guo T, Bian J, Xiao F, Li Y, Cong H, Wei Y, Zhang X, Liu J, Yin L. The landscape of PBMCs in AQP4-IgG seropositive NMOSD and MOGAD, assessed by high dimensional mass cytometry. CNS Neurosci Ther 2024; 30:e14608. [PMID: 38334017 PMCID: PMC10853888 DOI: 10.1111/cns.14608] [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: 10/08/2023] [Revised: 01/02/2024] [Accepted: 01/05/2024] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVES Data on peripheral blood mononuclear cells (PBMCs) characteristics of aquaporin-4 (AQP4)-IgG seropositive neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) are lacking. In this study, we describe the whole PBMCs landscape of the above diseases using cytometry by time-of-flight mass spectrometry (CyTOF). METHODS The immune cell populations were phenotyped and clustered using CyTOF isolated from 27 AQP4-IgG seropositive NMOSD, 11 MOGAD patients, and 15 healthy individuals. RNA sequencing was employed to identify critical genes. Fluorescence cytometry and qPCR analysis were applied to further validate the algorithm-based results that were obtained. RESULTS We identified an increased population of CD11b+ mononuclear phagocytes (MNPs) in patients with high expression of CCR2, whose abundance may correlate with brain inflammatory infiltration. Using fluorescence cytometry, we confirmed the CCR2+ monocyte subsets in a second cohort of patients. Moreover, there was a wavering of B, CD4+ T, and NKT cells between AQP4-IgG seropositive NMOSD and MOGAD. CONCLUSIONS Our findings describe the whole landscape of PBMCs in two similar demyelinated diseases and suggest that, besides MNPs, T, NK and B, cells were all involved in the pathogenesis. The identified cell population may be used as a predictor for monitoring disease development or treatment responses.
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Affiliation(s)
- Mengyuan Yao
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Wenjing Wang
- Beijing Institute of Hepatology, Beijing Youan HospitalCapital Medical UniversityBeijingChina
| | - Jiali Sun
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Tianshu Guo
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Jiangping Bian
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Fuyao Xiao
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yuanyuan Li
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Hengri Cong
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yuzhen Wei
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xinghu Zhang
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Jianghong Liu
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain DisordersCapital Medical UniversityBeijingChina
| | - Linlin Yin
- Department of Neuroinfection and Neuroimmunology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain DisordersCapital Medical UniversityBeijingChina
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20
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Chen X, Zhang J, Shen LS, Chen YP, Yang JQ, Tang WJ, Guo RM. Bibliometric analysis of myelin imaging studies of patients with multiple sclerosis (2000-2022). Quant Imaging Med Surg 2024; 14:837-851. [PMID: 38223029 PMCID: PMC10784065 DOI: 10.21037/qims-23-1157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/10/2023] [Indexed: 01/16/2024]
Abstract
Background Multiple sclerosis (MS) is a condition that can impact the central nervous system (CNS) and cause damage to the myelin, which is responsible for facilitating the normal transmission of electrical impulses along the nerves. We performed a bibliometric analysis of the scientific publications on myelin imaging in MS to reveal the development trends in this field and to evaluate research trends in myelin imaging in MS. Methods The Web of Science Core Collection was searched for articles related to myelin imaging in MS published between January 2000 and December 2022. CiteSpace, VOSviewer, and R language were used to evaluate and visualize contributions by and co-occurrence relationships among countries and institutions, authors, journals, citations, keywords, and so on. Results A total of 1,639 articles addressed the topic of myelin imaging in MS. The United States had the largest number of annual publications. The University of London was the institution with the highest number of publications (n=118) and citations (n=9,885). The top 3 productive authors were all from the University of British Columbia in Canada. An article published by Mackay et al. in 1994 had the most citations (n=272). Neuroimage [impact factor (IF) =7.40, Journal Citation Reports quartile 1 (Q1)] was the most productive journal in terms of the number of articles relating to myelin imaging in MS (n=149). In recent years, myelin water imaging, synthetic magnetic resonance imaging (SyMRI), inhomogeneous magnetization, positron emission tomography (PET) imaging, and aquaporin-4 (AQP4) have been researched hotspots of myelin imaging in MS. Conclusions With advancements in the pathophysiological research on myelin changes in MS, myelin imaging is playing an important role in the diagnosis and treatment of MS. In addition, the use of new sequences of myelin imaging to distinguish MS from other inflammatory demyelinating diseases is a future development trend in this field.
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Affiliation(s)
| | | | - Li-Shan Shen
- Department of Radiology, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yao-Ping Chen
- Department of Radiology, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jin-Quan Yang
- Department of Radiology, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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21
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Siriratnam P, Huda S, Butzkueven H, van der Walt A, Jokubaitis V, Monif M. A comprehensive review of the advances in neuromyelitis optica spectrum disorder. Autoimmun Rev 2023; 22:103465. [PMID: 37852514 DOI: 10.1016/j.autrev.2023.103465] [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: 09/25/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Abstract
Neuromyelitis optica spectrum disorder (NMOSD) is a rare relapsing neuroinflammatory autoimmune astrocytopathy, with a predilection for the optic nerves and spinal cord. Most cases are characterised by aquaporin-4-antibody positivity and have a relapsing disease course, which is associated with accrual of disability. Although the prognosis in NMOSD has improved markedly over the past few years owing to advances in diagnosis and therapeutics, it remains a severe disease. In this article, we review the evolution of our understanding of NMOSD, its pathogenesis, clinical features, disease course, treatment options and associated symptoms. We also address the gaps in knowledge and areas for future research focus.
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Affiliation(s)
- Pakeeran Siriratnam
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
| | - Saif Huda
- Department of Neurology, Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
| | - Anneke van der Walt
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
| | - Vilija Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
| | - Mastura Monif
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria, Australia; Department of Neurology, The Royal Melbourne Hospital, Parkville, VIC, Australia.
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22
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Sacco S, Virupakshaiah A, Papinutto N, Schoeps VA, Akula A, Zhao H, Arona J, Stern WA, Chong J, Hart J, Zamvil SS, Sati P, Henry RG, Waubant E. Susceptibility-based imaging aids accurate distinction of pediatric-onset MS from myelin oligodendrocyte glycoprotein antibody-associated disease. Mult Scler 2023; 29:1736-1747. [PMID: 37897254 PMCID: PMC10687802 DOI: 10.1177/13524585231204414] [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: 06/30/2023] [Revised: 09/07/2023] [Accepted: 09/13/2023] [Indexed: 10/30/2023]
Abstract
BACKGROUND Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) and pediatric-onset multiple sclerosis (POMS) share clinical and magnetic resonance imaging (MRI) features but differ in prognosis and management. Early POMS diagnosis is essential to avoid disability accumulation. Central vein sign (CVS), paramagnetic rim lesions (PRLs), and central core lesions (CCLs) are susceptibility-based imaging (SbI)-related signs understudied in pediatric populations that may help discerning POMS from MOGAD. METHODS T2-FLAIR and SbI (three-dimensional echoplanar imaging (3D-EPI)/susceptibility-weighted imaging (SWI) or similar) were acquired on 1.5T/3T scanners. Two readers assessed CVS-positive rate (%CVS+), and their average score was used to build a receiver operator curve (ROC) assessing the ability to discriminate disease type. PRLs and CCLs were identified using a consensual approach. RESULTS The %CVS+ distinguished 26 POMS cases (mean age 13.7 years, 63% females, median EDSS 1.5) from 14 MOGAD cases (10.8 years, 35% females, EDSS 1.0) with ROC = 1, p < 0.0001, (cutoff 41%). PRLs were only detectable in POMS participants (mean 2.1±2.3, range 1-10), discriminating the two conditions with a sensitivity of 69% and a specificity of 100%. CCLs were more sensitive (81%) but less specific (71.43%). CONCLUSION The %CVS+ and PRLs are highly specific markers of POMS. After proper validation on larger multicenter cohorts, consideration should be given to including such imaging markers for diagnosing POMS at disease onset.
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Affiliation(s)
- Simone Sacco
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Akash Virupakshaiah
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Nico Papinutto
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Vinicius A Schoeps
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Amit Akula
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Haojun Zhao
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Jennifer Arona
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - William A Stern
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Janet Chong
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Janace Hart
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Scott S Zamvil
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Pascal Sati
- Neuroimaging Program, Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Roland G Henry
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Emmanuelle Waubant
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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Özütemiz C, White M, Elvendahl W, Eryaman Y, Marjańska M, Metzger GJ, Patriat R, Kulesa J, Harel N, Watanabe Y, Grant A, Genovese G, Cayci Z. Use of a Commercial 7-T MRI Scanner for Clinical Brain Imaging: Indications, Protocols, Challenges, and Solutions-A Single-Center Experience. AJR Am J Roentgenol 2023; 221:788-804. [PMID: 37377363 PMCID: PMC10825876 DOI: 10.2214/ajr.23.29342] [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: 06/29/2023]
Abstract
The first commercially available 7-T MRI scanner (Magnetom Terra) was approved by the FDA in 2017 for clinical imaging of the brain and knee. After initial protocol development and sequence optimization efforts in volunteers, the 7-T system, in combination with an FDA-approved 1-channel transmit/32-channel receive array head coil, can now be routinely used for clinical brain MRI examinations. The ultrahigh field strength of 7-T MRI has the advantages of improved spatial resolution, increased SNR, and increased CNR but also introduces an array of new technical challenges. The purpose of this article is to describe an institutional experience with the use of the commercially available 7-T MRI scanner for routine clinical brain imaging. Specific clinical indications for which 7-T MRI may be useful for brain imaging include brain tumor evaluation with possible perfusion imaging and/or spectroscopy, radiotherapy planning; evaluation of multiple sclerosis and other demyelinating diseases, evaluation of Parkinson disease and guidance of deep brain stimulator placement, high-detail intracranial MRA and vessel wall imaging, evaluation of pituitary pathology, and evaluation of epilepsy. Detailed protocols, including sequence parameters, for these various indications are presented, and implementation challenges (including artifacts, safety, and side effects) and potential solutions are explored.
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Affiliation(s)
- Can Özütemiz
- Department of Radiology, University of Minnesota, 420 Delaware St SE, MMC 292, Minneapolis, MN 55455
| | - Matthew White
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
- Center for Clinical Imaging Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Wendy Elvendahl
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
- Center for Clinical Imaging Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Yigitcan Eryaman
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Gregory J Metzger
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Rémi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Jeramy Kulesa
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Yoichi Watanabe
- Department of Radiation Oncology, University of Minnesota, Minneapolis, MN
| | - Andrea Grant
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Guglielmo Genovese
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Zuzan Cayci
- Department of Radiology, University of Minnesota, 420 Delaware St SE, MMC 292, Minneapolis, MN 55455
- Center for Clinical Imaging Research, Department of Radiology, University of Minnesota, Minneapolis, MN
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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 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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25
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Donica VC, Alexa AI, Pavel IA, Danielescu C, Ciapă MA, Donica AL, Bogdănici CM. The Evolvement of OCT and OCT-A in Identifying Multiple Sclerosis Biomarkers. Biomedicines 2023; 11:3031. [PMID: 38002031 PMCID: PMC10669604 DOI: 10.3390/biomedicines11113031] [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: 10/12/2023] [Revised: 11/09/2023] [Accepted: 11/10/2023] [Indexed: 11/26/2023] Open
Abstract
The prevalence of multiple sclerosis (MS) has been increasing among young people in developing countries over the last years. With the continuous development of new technology, the diagnosis and follow-up of these patients has received new parameters that physicians may use in their practice. This paper reviews the main biomarkers identified through Optical Coherence Tomography Angiography (OCT-A) involved in the development and progression of MS and investigates the role it may have in detecting changes to the central nervous system (CNS).
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Affiliation(s)
- Vlad Constantin Donica
- Department of Ophthalmology, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, No. 16, 700115 Iasi, Romania; (V.C.D.); (C.D.); (C.M.B.)
| | - Anisia Iuliana Alexa
- Department of Ophthalmology, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, No. 16, 700115 Iasi, Romania; (V.C.D.); (C.D.); (C.M.B.)
| | - Irina Andreea Pavel
- Department of Ophthalmology, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, No. 16, 700115 Iasi, Romania; (V.C.D.); (C.D.); (C.M.B.)
| | - Ciprian Danielescu
- Department of Ophthalmology, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, No. 16, 700115 Iasi, Romania; (V.C.D.); (C.D.); (C.M.B.)
| | | | | | - Camelia Margareta Bogdănici
- Department of Ophthalmology, Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, No. 16, 700115 Iasi, Romania; (V.C.D.); (C.D.); (C.M.B.)
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26
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Villacieros-Álvarez J, Espejo C, Arrambide G, Castillo M, Carbonell-Mirabent P, Rodriguez M, Bollo L, Castilló J, Comabella M, Galán I, Midaglia L, Mongay-Ochoa N, Nos C, Rio J, Rodríguez-Acevedo B, Sastre-Garriga J, Tur C, Vidal-Jordana A, Vilaseca A, Zabalza A, Auger C, Rovira A, Montalban X, Tintoré M, Cobo-Calvo Á. Myelin Oligodendrocyte Glycoprotein Antibodies in Adults with a First Demyelinating Event Suggestive of Multiple Sclerosis. Ann Neurol 2023. [PMID: 37705507 DOI: 10.1002/ana.26793] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/21/2023] [Accepted: 09/07/2023] [Indexed: 09/15/2023]
Abstract
OBJECTIVE Myelin oligodendrocyte glycoprotein antibodies (MOG-Ab) distinguish multiple sclerosis (MS) from MOG-associated disease in most cases. However, studies analyzing MOG-Ab at the time of a first demyelinating event suggestive of MS in adults are lacking. We aimed to (1) evaluate the prevalence of MOG-Ab in a first demyelinating event suggestive of MS and (2) compare clinical and paraclinical features between seropositive (MOG-Ab+) and seronegative (MOG-Ab-) patients. METHODS Six hundred thirty adult patients with available serum samples obtained within 6 months from the first event were included. MOG-Ab were analyzed using a live cell-based assay. Statistical analyses included parametric and nonparametric tests, logistic regression, and survival models. RESULTS MOG-Ab were positive in 17 of 630 (2.7%). Fourteen out of 17 (82.4%) MOG-Ab+ patients presented with optic neuritis (ON) compared to 227of 613 (37.0%) MOG-Ab- patients (p = 0.009). Cerebrospinal fluid-restricted oligoclonal bands (CSF-OBs) were found in 2 of 16 (12.5%) MOG-Ab+ versus 371 of 601 (61.7%) MOG-Ab- subjects (p < 0.001). Baseline brain magnetic resonance imaging (MRI) was normal in 9 of 17 (52.9%) MOG-Ab+ versus 153 of 585 (26.2%) MOG-Ab- patients (p = 0.029). Absence of CSF-OBs and ON at onset were independently associated with MOG-Ab positivity (odds ratio [OR] = 9.03, 95% confidence interval [CI] = 2.04-53.6, p = 0.009; and OR = 4.17, 95% CI = 1.15-19.8, p = 0.042, respectively). Of MOG-Ab+ patients, 22.9% (95% CI = 0.0-42.7) compared to 67.6% (95% CI = 63.3-71.3) of MOG-Ab- patients fulfilled McDonald 2017 criteria at 5 years (log-rank p = 0.003). INTERPRETATION MOG-Ab are infrequent in adults with a first demyelinating event suggestive of MS. However, based on our results, we suggest to determine these antibodies in those patients with ON and absence of CSF-OBs, as long as the brain MRI is not suggestive of MS. ANN NEUROL 2023.
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Affiliation(s)
- Javier Villacieros-Álvarez
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Carmen Espejo
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Georgina Arrambide
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Mireia Castillo
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Pere Carbonell-Mirabent
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Marta Rodriguez
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Luca Bollo
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Joaquín Castilló
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Manuel Comabella
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Ingrid Galán
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Luciana Midaglia
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Neus Mongay-Ochoa
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Carlos Nos
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Jordi Rio
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Breogan Rodríguez-Acevedo
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Carmen Tur
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Angela Vidal-Jordana
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Andreu Vilaseca
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Ana Zabalza
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Cristina Auger
- Autonomous University of Barcelona, Barcelona, Spain
- Section of Neuroradiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Alex Rovira
- Autonomous University of Barcelona, Barcelona, Spain
- Section of Neuroradiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Xavier Montalban
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
| | - Álvaro Cobo-Calvo
- Neurology-Neuroimmunology Department, Multiple Sclerosis Center of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Vall d'Hebron Research Institute, Barcelona, Spain
- Autonomous University of Barcelona, Barcelona, Spain
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Wang Y, Danzeng Q, Jiang W, Han B, Zhu X, Liu Z, Sun J, Chen K, Zhang G. A retrospective study of myelin oligodendrocyte glycoprotein antibody-associated disease from a clinical laboratory perspective. Front Neurol 2023; 14:1187824. [PMID: 37771453 PMCID: PMC10523388 DOI: 10.3389/fneur.2023.1187824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
Objectives To analyze the differences in laboratory data between patients with myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Methods The study included 26 MOGAD patients who visited Beijing Tiantan Hospital from 2018 to 2021. MS and NMOSD patients who visited the clinic during the same period were selected as controls. Relevant indicators were compared between the MOGAD group and the MS/NMOSD groups, and the diagnostic performance of meaningful markers was assessed. Results The MOGAD group showed a slight female preponderance of 57.7%, with an average onset age of 29.8 years. The absolute and relative counts of neutrophils were higher in the MOGAD group than in the MS group, while the proportion of lymphocytes was lower. The cerebrospinal fluid (CSF) IgG level, IgG index, 24-h IgG synthesis rate, and positive rate of oligoclonal bands (OCB) were lower in MOGAD patients than in the MS group. The area under ROC curve (AUC) was 0.939 when combining the relative lymphocyte count and IgG index. Compared to the NMOSD group, the MOGAD group had higher levels of serum complement C4 and lower levels of serum IgG. The AUC of serum C4 combined with FT4 was 0.783. Conclusion Statistically significant markers were observed in the laboratory data of MOGAD patients compared to MS/NMOSD patients. The relative lymphocyte count combined with IgG index had excellent diagnostic efficacy for MOGAD and MS, while serum C4 combined with FT4 had better diagnostic efficacy for MOGAD and NMOSD.
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Affiliation(s)
- Yufei Wang
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Qusang Danzeng
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Wencan Jiang
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Bingqing Han
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Xiaowen Zhu
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Ziwei Liu
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Jialu Sun
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Kelin Chen
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
| | - Guojun Zhang
- Laboratory Diagnosis Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- NMPA Key Laboratory for Quality Control of In Vitro Diagnostics, Beijing, China
- Beijing Engineering Research Center of Immunological Reagents Clinical Research, Beijing, China
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28
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Carnero Contentti E, Okuda DT, Rojas JI, Chien C, Paul F, Alonso R. MRI to differentiate multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. J Neuroimaging 2023; 33:688-702. [PMID: 37322542 DOI: 10.1111/jon.13137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/17/2023] Open
Abstract
Differentiating multiple sclerosis (MS) from other relapsing inflammatory autoimmune diseases of the central nervous system such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is crucial in clinical practice. The differential diagnosis may be challenging but making the correct ultimate diagnosis is critical, since prognosis and treatments differ, and inappropriate therapy may promote disability. In the last two decades, significant advances have been made in MS, NMOSD, and MOGAD including new diagnostic criteria with better characterization of typical clinical symptoms and suggestive imaging (magnetic resonance imaging [MRI]) lesions. MRI is invaluable in making the ultimate diagnosis. An increasing amount of new evidence with respect to the specificity of observed lesions as well as the associated dynamic changes in the acute and follow-up phase in each condition has been reported in distinct studies recently published. Additionally, differences in brain (including the optic nerve) and spinal cord lesion patterns between MS, aquaporin4-antibody-positive NMOSD, and MOGAD have been described. We therefore present a narrative review on the most relevant findings in brain, spinal cord, and optic nerve lesions on conventional MRI for distinguishing adult patients with MS from NMOSD and MOGAD in clinical practice. In this context, cortical and central vein sign lesions, brain and spinal cord lesions characteristic of MS, NMOSD, and MOGAD, optic nerve involvement, role of MRI at follow-up, and new proposed diagnostic criteria to differentiate MS from NMOSD and MOGAD were discussed.
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Affiliation(s)
| | - Darin T Okuda
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Juan I Rojas
- Centro de esclerosis múltiple de Buenos Aires, Buenos Aires, Argentina
| | - Claudia Chien
- 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, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemman 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, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ricardo Alonso
- Centro Universitario de Esclerosis Múltiple (CUEM), Hospital Ramos Mejía, Buenos Aires, Argentina
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29
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Seok JM, Cho W, Chung YH, Ju H, Kim ST, Seong JK, Min JH. Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model. Sci Rep 2023; 13:11625. [PMID: 37468553 DOI: 10.1038/s41598-023-38271-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 07/06/2023] [Indexed: 07/21/2023] Open
Abstract
Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are autoimmune inflammatory disorders of the central nervous system (CNS) with similar characteristics. The differential diagnosis between MS and NMOSD is critical for initiating early effective therapy. In this study, we developed a deep learning model to differentiate between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) using brain magnetic resonance imaging (MRI) data. The model was based on a modified ResNet18 convolution neural network trained with 5-channel images created by selecting five 2D slices of 3D FLAIR images. The accuracy of the model was 76.1%, with a sensitivity of 77.3% and a specificity of 74.8%. Positive and negative predictive values were 76.9% and 78.6%, respectively, with an area under the curve of 0.85. Application of Grad-CAM to the model revealed that white matter lesions were the major classifier. This compact model may aid in the differential diagnosis of MS and NMOSD in clinical practice.
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Affiliation(s)
- Jin Myoung Seok
- Department of Neurology, Soonchunhyang University Hospital Cheonan, Soonchunhyang University College of Medicine, Cheonan, South Korea
| | - Wanzee Cho
- Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Yeon Hak Chung
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hyunjin Ju
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Sung Tae Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Joon-Kyung Seong
- Department of Artificial Intelligence, Korea University, Seoul, South Korea.
- School of Biomedical Engineering, Korea University, Seoul, South Korea.
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, South Korea.
| | - Ju-Hong Min
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Seoul, South Korea.
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 50 Irwon-dong, Gangnam-gu, Seoul, 135-710, South Korea.
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Tomizawa Y, Hoshino Y, Kamo R, Cossu D, Yokoyama K, Hattori N. Comparing clinical and imaging features of patients with MOG antibody-positivity and with and without oligoclonal bands. Front Immunol 2023; 14:1211776. [PMID: 37520579 PMCID: PMC10374016 DOI: 10.3389/fimmu.2023.1211776] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 06/22/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction Myelin-oligodendrocyte glycoprotein antibody (MOG)-associated disorder (MOGAD) is a recently identified immune-mediated inflammatory disorder of the central nervous system (CNS). The significance of oligoclonal bands (OCBs) is not fully elucidated. This study investigated the clinical differences between patients with MOGAD who tested positive or negative for OCBs. Methods The study was conducted on 23 patients with MOG-IgG-seropositivity who presented with central nervous system (CNS) symptoms. The patients were screened and divided into OCB-positive (n=10) and OCB-negative (n=13) groups, and their demographic, clinical, and magnetic resonance imaging (MRI) features were compared. Results The results revealed that patients with OCB-positivity had a significantly higher frequency of relapse, and their IgG index was significantly higher. Discussion OCBs were common in MOGAD met the consensus criteria. The study concluded that careful treatment decision-making is necessary in MOG antibody-positive cases with OCB-positivity.
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Affiliation(s)
- Yuji Tomizawa
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
| | - Yasunobu Hoshino
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
| | - Ryota Kamo
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
| | - Davide Cossu
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
- Department of Biomedical Sciences, Sassari University, Sassari, Italy
| | - Kazumasa Yokoyama
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
- Tousei Center for Neurological Diseases, Shizuoka, Japan
| | - Nobutaka Hattori
- Department of Neurology, School of Medicine, Juntendo University, Tokyo, Japan
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Mainero C, Treaba CA, Barbuti E. Imaging cortical lesions in multiple sclerosis. Curr Opin Neurol 2023; 36:222-228. [PMID: 37078649 DOI: 10.1097/wco.0000000000001152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
PURPOSE OF REVIEW Cortical lesions are an established pathological feature of multiple sclerosis, develop from the earliest disease stages and contribute to disease progression. Here, we discuss current imaging approaches for detecting cortical lesions in vivo and their contribution for improving our understanding of cortical lesion pathogenesis as well as their clinical significance. RECENT FINDINGS Although a variable portion of cortical lesions goes undetected at clinical field strength and even at ultra-high field MRI, their evaluation is still clinically relevant. Cortical lesions are important for differential multiple sclerosis (MS) diagnosis, have relevant prognostic value and independently predict disease progression. Some studies also show that cortical lesion assessment could be used as a therapeutic outcome target in clinical trials. Advances in ultra-high field MRI not only allow increased cortical lesion detection in vivo but also the disclosing of some interesting features of cortical lesions related to their pattern of development and evolution as well to the nature of associated pathological changes, which might prove relevant for better understanding the pathogenesis of these lesions. SUMMARY Despite some limitations, imaging of cortical lesions is of paramount importance in MS for elucidating disease mechanisms as well as for improving patient management in clinic.
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Affiliation(s)
- Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elena Barbuti
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Ospedale Sant'Andrea, University "La Sapienza", Rome, Italy
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Harrison KL, Gaudioso C, Levasseur VA, Dunham SR, Schanzer N, Keuchel C, Salter A, Goyal MS, Mar S. Central Vein Sign in Pediatric Multiple Sclerosis and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease. Pediatr Neurol 2023; 146:21-25. [PMID: 37406422 DOI: 10.1016/j.pediatrneurol.2023.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 05/17/2023] [Accepted: 05/18/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND The central vein sign (CVS) on brain magnetic resonance imaging (MRI) is a promising diagnostic marker for distinguishing adult multiple sclerosis (MS) from other demyelinating conditions, but its prevalence is not well-established in pediatric-onset multiple sclerosis (POMS) versus myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). MOGAD can mimic MS radiologically. This study seeks to determine the utility of CVS, together with other radiological findings, in distinguishing POMS from MOGAD in children. METHODS Children with POMS or MOGAD were identified in a pediatric demyelinating database. Two reviewers, blinded to diagnosis, fused fluid-attenuated inversion recovery sequences and susceptibility-weighted imaging from clinical imaging to identify CVS. Agreement in CVS number was reported using intraclass correlation coefficients (ICC). We performed topographic analyses as well as characterization of the clinical information and lesions on brain, spinal cord, and orbital MRI when available. RESULTS Twenty children, 10 with POMS and 10 with MOGAD, were assessed. The median lesion percentage of CVS was higher in POMS versus MOGAD for both raters (rater 1: 80% vs 9.8%; rater 2: 22.7% vs 7.5%). Inter-rater reliability for identifying total white matter lesions was strong (ICC 0.94 [95% confidence interval [CI] 0.84, 0.97]); however, it was poor for detecting CVS lesions (ICC -0.17 [95% CI: -0.37, 0.58]). CONCLUSION The CVS can be a useful diagnostic tool for differentiating POMS from MOGAD. However, advanced clinical imaging tools that can better detect CVS are needed to increase inter-rater reliability before clinical application.
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Affiliation(s)
- Kimystian L Harrison
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri.
| | - Cristina Gaudioso
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Victoria A Levasseur
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - S Richard Dunham
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Natalie Schanzer
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Connor Keuchel
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Amber Salter
- Department of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Manu S Goyal
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri; Department of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Soe Mar
- Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri
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Abdel-Mannan O, Ciccarelli O. Is the central vein sign a useful diagnostic marker for paediatric-onset multiple sclerosis? Mult Scler 2023; 29:479-480. [PMID: 36514269 PMCID: PMC9972230 DOI: 10.1177/13524585221142318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Omar Abdel-Mannan
- Queen Square MS Centre, UCL Queen Square
Institute of Neurology, Faculty of Brain Sciences, University College
London, London, UK/Department of Neurology, Great Ormond Street Hospital NHS
Trust, London, UK
| | - Olga Ciccarelli
- O Ciccarelli Queen Square MS Centre, UCL
Queen Square Institute of Neurology, Faculty of Brain Sciences, University
College London, London, WC1N 3BG, UK.
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