MRI Characteristics of Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease
Abstract
Importance Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a demyelinating disease distinct from multiple sclerosis (MS) and aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD). Magnetic resonance imaging (MRI) is central to confirming attacks, defining lesion distribution, and excluding alternative diagnoses and is a key component of the 2023 MOGAD diagnostic criteria. However, its imaging spectrum and lesion evolution remain underrecognized in practice, and variability in imaging parameters can contribute to delayed diagnosis and suboptimal treatment. Observations This article summarizes the hallmark MRI features of optic nerve, brain, and spinal cord involvement in MOGAD, including key findings from the 2023 diagnostic criteria, supported by illustrative figures and detailed tables. The characteristic evolution of MRI abnormalities in MOGAD is highlighted, including radiologic lag, lesion dynamics during acute attacks, and frequent T2-lesion resolution, contrasting with the persistent lesions typical of MS. A recommended MRI protocol for acute attacks is proposed, and the timing and utility of rebaselining MRI (ie, repeating the MRI to establish a new baseline) after onset are reviewed. The clinical course of MOGAD is of attack-related neuroinflammation evident clinically and radiologically, and asymptomatic radiological activity is rare, suggesting that surveillance MRI has less clinical utility than in MS and less value as a surrogate biomarker in clinical trials. MRI features that differentiate MOGAD from MS and AQP4+NMOSD are summarized and imaging red flags suggestive of alternative diagnoses are highlighted. Finally, emerging advanced imaging, artificial intelligence in MOGAD imaging, and the link between imaging and immunopathogenesis are reviewed. Conclusions and Relevance MRI is central to MOGAD evaluation, and recognition of the characteristic imaging features and lesion dynamics outlined in this review can aid diagnosis. Application of the standardized MRI protocol summarized here can optimize use in clinical practice and promote harmonization across research studies. Future imaging and artificial intelligence applications may improve diagnosis, disease monitoring, and understanding of MOGAD pathogenesis.
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Authors: Eoin P. Flanagan, Brenda L. Banwell, Laura Cacciaguerra, Edgar Carnero Contentti, John J. Chen, Rosa Cortese, Giulia Fadda, Kazuo Fujihara, Ruth Geraldes, Yael Hacohen, Ho Jin Kim, Maciej Juryńczyk, Michael Levy, Kshitij Mankad, Romain Marignier, Silvia Messina, Friedemann Paul, Sudarshini Ramanathan, Àlex Rovira, Elia Sechi, Silvia Tenembaum, Jacqueline Palace
Institutions: Johns Hopkins University, Charité - Universitätsmedizin Berlin, Harvard University, University of Basel, University Hospital of Basel, University of Oxford, University College London, University of Sassari, Universitat Autònoma de Barcelona, National Cancer Center, Oxford University Hospitals NHS Trust, Polish Academy of Sciences, Fukushima Medical University, University of Ottawa, Mayo Clinic in Arizona, Great Ormond Street Hospital, Vall d'Hebron Hospital Universitari, Lyon 1 Université, Hospices Civils de Lyon, Massachusetts General Hospital, Mayo Clinic, National Hospital for Neurology and Neurosurgery, Ottawa Hospital Research Institute, Centre de Recherche en Neurosciences de Lyon, University of Siena, Hospital Alemán, Instituto de Neurología Cognitiva, Great Ormond Street Hospital for Children NHS Foundation Trust, Garrahan Hospital, Anzac Research Institute, Max Delbrück Center, Concord Repatriation General Hospital, UCL Queen Square Institute of Neurology, Hôpital Pierre Wertheimer, National Cancer Center Hospital, Instytut Biologii Doświadczalnej im. Marcelego Nenckiego