Clinical and Imaging Profile of MOG Antibody–Associated Optic Neuritis in Indian Patients
Keywords:
MOG Antibody Disease, Optic Neuritis, MOGAD, Magnetic Resonance Imaging, Visual Outcome, India.Abstract
Background: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) has emerged as a distinct inflammatory demyelinating disorder of the central nervous system. Optic neuritis (ON) is one of the most common clinical manifestations of MOGAD and is characterized by unique clinical and radiological features. Early recognition is essential because visual outcomes and treatment responses differ from other forms of optic neuritis.
Methods: A retrospective observational study was conducted involving 30 patients diagnosed with MOG antibody-associated optic neuritis (MOG-ON). Demographic characteristics, clinical presentation, magnetic resonance imaging (MRI) findings, visual acuity at presentation and follow-up, treatment response, and recurrence profiles were analyzed. Descriptive statistics were used to summarize clinical and imaging characteristics.
Results: The mean age of patients was 27.8 ± 12.4 years, with a female predominance (60.0%). Unilateral optic neuritis was observed in 53.3% of patients, while 46.7% had bilateral involvement. Ocular pain (83.3%) and optic disc edema (66.7%) were common clinical findings. MRI demonstrated optic nerve enhancement in 90.0% and long-segment optic nerve involvement in 60.0% of patients. Visual outcomes improved substantially during follow-up, with 66.7% achieving visual acuity ≥6/12 compared to 10.0% at baseline. Complete visual recovery occurred in 60.0% of patients, and 86.7% exhibited steroid-responsive disease. Relapses occurred in 23.3% of patients during follow-up.
Conclusion: MOG antibody-associated optic neuritis in Indian patients is characterized by young age at presentation, frequent bilateral involvement, optic disc edema, characteristic MRI findings, and favorable visual recovery following treatment. Recognition of these features may facilitate early diagnosis and optimal management.
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