Background and purpose: Corpus callosum (CC) is frequently involved in relapsing-remitting multiple sclerosis (RRMS). Magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) allow to study CC macrostructural and microstructural tissue integrity. Here, we applied a data-driven approach to MRI and DTI data of normal-appearing CC in RRMS subjects, and subsequently evaluated if differences in tissue integrity corresponded to different levels of physical disability and cognitive impairment.
Methods: 74 RRMS patients and 20 healthy controls (HC) underwent 3 T MRI and DTI. Thickness and fractional anisotropy (FA) along midsagittal CC were extracted, and values from RRMS patients were fed to a hierarchical clustering algorithm. We then used ANOVA to test for differences in clinical and cognitive variables across the imaging-based clusters and HC.
Results: We found three distinct MRI-based subgroups of RRMS patients with increasing severity of CC damage. The first subgroup showed callosal integrity similar to HC (Cluster 1); Cluster 2 had milder callosal damage; a third subgroup showed the most severe callosal damage (Cluster 3). Cluster 3 included patients with longer disease duration and worst scores in Expanded Disability Status Scale. Cognitive domains of verbal memory, executive functions and processing speed were impaired in Cluster 3 and Cluster 2 compared to Cluster 1 and HC.
Conclusions: Within the same homogeneous cohort of patients, we could identify three neuroimaging RRMS clusters characterized by different involvement of normal-appearing CC. Interestingly, these corresponded to three distinct levels of clinical and cognitive disability.
Keywords: Cognitive impairment; Corpus callosum; DTI; Hierarchical clustering; MRI; Multiple sclerosis.