ArticleIrish journal of medical science2025
Subcortical volume alterations indicate structural atrophy patterns over time in relapsing-remitting multiple sclerosis: a volBrain-based analysis.
Article in Irish journal of medical science, 2025. 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
backgroundMultiple Sclerosis (MS), a neurodegenerative disorder affecting central nervous system, predominantly manifests as Relapsing-Remitting MS (RRMS), with subcortical volume loss serving as a prognostic indicator.
aimsThis study aimed to assess time-dependent volumetric changes in thalamus and basal nuclei using a validated automated tool, volBrain software, on MR images (MRI) across three years and relationship between structural changes and disease progression.
methodsThe study included 50 RRMS patients (33.5 ± 6.3 years; 68% female, 32% male) and 50 healthy controls (38.0 ± 5.8 years; 64% female, 36% male). T1-weighted brain MRI scans (from 2017, 2019, 2022) were analyzed via volBrain. Statistical analyses included Shapiro-Wilk, Mann-Whitney U, Friedman, and Dunn tests.
resultsThalamus, nucleus caudatus (nuc. caudatus), and nucleus lentiformis (nuc. lentiformis) volumes were significantly lower in RRMS (p < 0.05). Significant volume loss was observed between 1st-3rd MRI and 2nd-3rd MRI (p < 0.05), but difference between 1st-2nd MRI was not statistically significant (p > 0.05). The most pronounced volume loss occurred between 1st-3rd MRI, with the greatest reduction observed in left nuc. caudatus (7.92%). This loss was followed by right thalamus (5.68%) and nuc. lentiformis (4.35%). Although atrophy was observed across disease duration groups, this difference was not statistically significant (p > 0.05). Volume loss in thalamus and basal nuclei indicated significant atrophy in RRMS patients.
conclusionsFindings highlighted MS-induced subcortical atrophy that significantly impacts brain structure. This study was distinguished through volBrain, highlighting its effectiveness in providing data with clinical relevance. Subcortical volume changes show potential as biomarkers for disease progression and guiding targeted therapies.
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