: MRI and clinical features of myelin oligodendrocyte glycoprotein (MOG)-antibody disease may overlap with those of other inflammatory demyelinating conditions posing diagnostic challenges, especially in non-acute phases and when serologic testing for MOG-antibodies is unavailable or shows uncertain results. We aimed to identify MRI and clinical markers that differentiate non-acute MOG-antibody disease from aquaporin4 (AQP4)-antibody neuromyelitis optica spectrum disorder and relapsing remitting multiple sclerosis, guiding in the identification of MOG-antibody disease patients in clinical practice. In this cross-sectional retrospective study, data from 16 MAGNIMS centres were included. Data collection and analyses were conducted from 2019 to 2021. Inclusion criteria were: diagnosis of MOG-antibody disease, AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis, brain and cord MRI at least 6 months from relapse, EDSS on the day of MRI. Brain white matter T2 lesions, T1-hypointense lesions, cortical and cord lesions were identified. Random-forest models were constructed to classify patients as MOG-antibody disease/AQP4-neuromyelitis optica spectrum disorder/multiple sclerosis; a leave one out cross-validation procedure assessed the performance of the models. Based on the best discriminators between diseases, we proposed a guide to target investigations for MOG-antibody disease. One hundred sixty-two patients with MOG-antibody disease (99F, mean age: 41 [±14] years, median EDSS: 2 [0-7.5]), 162 with AQP4-neuromyelitis optica spectrum disorder (132F, mean age: 51 [±14] years, median EDSS: 3.5 [0-8]), 189 with multiple sclerosis (132F, mean age: 40 [±10] years, median EDSS: 2 [0-8]) and 152 healthy controls (91F) were studied. In young patients (<34 years), with low disability (EDSS < 3), the absence of Dawson's fingers, temporal lobe lesions and longitudinally extensive lesions in the cervical cord pointed towards a diagnosis of MOG-antibody disease instead of the other two diseases (accuracy: 76%, sensitivity: 81%, specificity: 84%, p < 0.001). In these non-acute patients, a number of brain lesions < 6 predicted MOG-antibody disease versus multiple sclerosis (accuracy: 83%, sensitivity: 82%, specificity: 83%, p < 0.001). An EDSS < 3 and the absence of longitudinally extensive lesions in the cervical cord predicted MOG-antibody disease versus AQP4-neuromyelitis optica spectrum disorder (accuracy: 76%, sensitivity: 89%, specificity: 62%, p < 0.001). A workflow with sequential tests and supporting features has been proposed to guide a better identification of MOG-antibody disease patients. Adult non-acute MOG-antibody disease patients showed distinctive clinical and MRI features when compared to AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis. A careful inspection of the morphology of brain and cord lesions together with clinical information, can guide for further analyses towards diagnosis of MOG-antibody disease in clinical practice.

Clinical and MRI measures to identify non-acute MOG-antibody disease in adults

Carmisciano, Luca;Sormani, Maria Pia;
2022-01-01

Abstract

: MRI and clinical features of myelin oligodendrocyte glycoprotein (MOG)-antibody disease may overlap with those of other inflammatory demyelinating conditions posing diagnostic challenges, especially in non-acute phases and when serologic testing for MOG-antibodies is unavailable or shows uncertain results. We aimed to identify MRI and clinical markers that differentiate non-acute MOG-antibody disease from aquaporin4 (AQP4)-antibody neuromyelitis optica spectrum disorder and relapsing remitting multiple sclerosis, guiding in the identification of MOG-antibody disease patients in clinical practice. In this cross-sectional retrospective study, data from 16 MAGNIMS centres were included. Data collection and analyses were conducted from 2019 to 2021. Inclusion criteria were: diagnosis of MOG-antibody disease, AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis, brain and cord MRI at least 6 months from relapse, EDSS on the day of MRI. Brain white matter T2 lesions, T1-hypointense lesions, cortical and cord lesions were identified. Random-forest models were constructed to classify patients as MOG-antibody disease/AQP4-neuromyelitis optica spectrum disorder/multiple sclerosis; a leave one out cross-validation procedure assessed the performance of the models. Based on the best discriminators between diseases, we proposed a guide to target investigations for MOG-antibody disease. One hundred sixty-two patients with MOG-antibody disease (99F, mean age: 41 [±14] years, median EDSS: 2 [0-7.5]), 162 with AQP4-neuromyelitis optica spectrum disorder (132F, mean age: 51 [±14] years, median EDSS: 3.5 [0-8]), 189 with multiple sclerosis (132F, mean age: 40 [±10] years, median EDSS: 2 [0-8]) and 152 healthy controls (91F) were studied. In young patients (<34 years), with low disability (EDSS < 3), the absence of Dawson's fingers, temporal lobe lesions and longitudinally extensive lesions in the cervical cord pointed towards a diagnosis of MOG-antibody disease instead of the other two diseases (accuracy: 76%, sensitivity: 81%, specificity: 84%, p < 0.001). In these non-acute patients, a number of brain lesions < 6 predicted MOG-antibody disease versus multiple sclerosis (accuracy: 83%, sensitivity: 82%, specificity: 83%, p < 0.001). An EDSS < 3 and the absence of longitudinally extensive lesions in the cervical cord predicted MOG-antibody disease versus AQP4-neuromyelitis optica spectrum disorder (accuracy: 76%, sensitivity: 89%, specificity: 62%, p < 0.001). A workflow with sequential tests and supporting features has been proposed to guide a better identification of MOG-antibody disease patients. Adult non-acute MOG-antibody disease patients showed distinctive clinical and MRI features when compared to AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis. A careful inspection of the morphology of brain and cord lesions together with clinical information, can guide for further analyses towards diagnosis of MOG-antibody disease in clinical practice.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1105873
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