Relapses and progression contribute to multiple sclerosis (MS) disease course, but neither the relationship between them nor the spectrum of clinical heterogeneity has been fully characterized. A hypothesis-driven, biologically informed model could build on the clinical phenotypes to encompass the dynamic admixture of factors underlying MS disease course. In this medical hypothesis, we put forth a dynamic model of MS disease course that incorporates localization and other drivers of disability to propose a clinical manifestation framework that visualizes MS in a clinically individualized way. The topographical model encapsulates 5 factors (localization of relapses and causative lesions; relapse frequency, severity, and recovery; and progression rate), visualized utilizing dynamic 3-dimensional renderings. The central hypothesis is that, like symptom recrudescence in Uhthoff phenomenon and pseudoexacerbations, progression clinically recapitulates prior relapse symptoms and unmasks previously silent lesions, incrementally revealing underlying lesion topography. The model uses real-time simulation software to depict disease course archetypes and illuminate several well-described but poorly reconciled phenomena including the clinical/MRI paradox and prognostic significance of lesion location and burden on disease outcomes. Utilization of this model could allow for earlier and more clinically precise identification of progressive MS and predictive implications can be empirically tested.

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ObjectiveUsing the topographical model of multiple sclerosis (MS) to evaluate a longitudinal cohort we (1) test the recapitulation hypothesis, positing that patients’ “disease topography” predicts the clinical pattern of disability accumulation; and (2) identify leading indicators of progression.Methods10 patients who transitioned from relapsing–remitting MS to secondary progressive MS (SPMS) were evaluated. Neurologic exams were analyzed from relapses, at time of SPMS diagnosis, and most recent visit. Functional systems (FS), location/laterality, and recovery were recorded. The pyramidal/motor system was the target FS assessing symptom laterality and severity at relapse and SPMS time-points. Each patient's clinical course was mapped using the topographical model software.ResultsCohort was 80% female, age 31.6 ± 8.6 years at diagnosis, followed average 23.8 ± 8.8 years, mean 3.1 relapses before SPMS. 83.3 ± 0.2% of relapse symptoms were present at transition to SPMS, increasing to 91.0 ± 0.2% at most recent visit. This demonstrates concordance between the topographical distribution of relapse symptoms and deficits from subsequent progression. In the topographical model, progression became apparent 7.75 years earlier than SPMS was diagnosed in practice.ConclusionsWe demonstrate the model's utility in depicting patients' disease topography as the loci of clinical progression. This could allow for earlier recognition of progressive disease by identifying leading indicators of progression.