ArticleFrontiers in neurology2026
The impact of OSCAR-IB quality control and manual segmentation on retinal atrophy rates in multiple sclerosis.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Inner retinal layer thinning, particularly of the peripapillary retinal nerve fiber layer (pRNFL) and the ganglion cell-inner plexiform layer (GCIPL), as measured by optical coherence tomography (OCT), is an established surrogate biomarker of neuroaxonal damage in multiple sclerosis; however, the influence of preprocessing strategies on longitudinal retinal change estimates remains unclear. We investigated the effects of OSCAR-IB quality control (QC) and manual segmentation correction on retinal layer change rates. Methods: People with MS (pwMS) with ≥ 2 OCT routine scans obtained ≥ 6 months apart were included. Annualized pRNFL and GCIPL thickness change was estimated using linear mixed-effects models across four preprocessing strategies: raw data, data after full OSCAR-IB QC, data after QC excluding the algorithm-criterion for segmentation, and data after manual segmentation correction. Longitudinal stability was evaluated using residual variance and random slope variance. Results: A total of 173 pwMS (mean age 34.6 years [8.5], 72.3% female) were included. Mean annualized pRNFL and GCIPL thickness change in raw data were -0.29%/year (0.29) and 0.14%/year (0.37), respectively. Compared with raw data, application of OSCAR-IB QC was associated with lower residual variance for both pRNFL (1.50 vs. 1.73) and GCIPL (0.65 vs. 0.78). Manual segmentation correction did not improve longitudinal stability for either retinal layer. Conclusion: OSCAR-IB QC was associated with improved longitudinal consistency of pRNFL and GCIPL change estimates in MS. In contrast, manual segmentation correction was not associated with additional benefit beyond exclusion-based QC, suggesting limited added value in routine clinical or large-scale research settings where feasibility and scalability are critical.
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