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Updated: Jul 24, 2025

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
Published on: July 19, 2019
Central Vein Sign in Pediatric Multiple Sclerosis and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease
Kimystian L Harrison1, Cristina Gaudioso1, Victoria A Levasseur1
1Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, Missouri.
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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