Microstructural MRI Correlates of Cognitive Impairment in Multiple Sclerosis: The Role of Deep Gray Matter

Abstract

Although cognitive impairment (CI) is frequently observed in people with multiple sclerosis (pwMS), its pathogenesis is still controversial. Conflicting results emerged concerning the role of microstructural gray matter (GM) damage especially when involving the deep GM structures. In this study, we aimed at evaluating whether differences in cortical and deep GM structures between apparently cognitively normal (ACN) and CI pwMS (36 subjects in total) are present, using an extensive set of diffusion MRI (dMRI) indices and conventional morphometry measures. The results revealed increased anisotropy and restriction over several deep GM structures in CI compared with ACN pwMS, while no changes in volume were present in the same areas. Conversely, reduced anisotropy/restriction values were detected in cortical regions, mostly the pericalcarine cortex and precuneus, combined with reduced thickness of the superior frontal gyrus and insula. Most of the dMRI metrics but none of the morphometric indices correlated with the Symbol Digit Modality Test. These results suggest that deep GM microstructural damage can be a strong anatomical substrate of CI in pwMS and might allow identifying pwMS at higher risk of developing CI.

Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer’s disease

“…These selections are complex and not immediately intuitive, which further prompted investigation into the basis of the network’s choices. We aimed to validate the network’s findings by examining tractography features impacting the structural connectome, utilizing diffusion and MAP metrics that relate to the white matter integrity of the tractography in the brain (Avram et al, 2016; Kochunov et al, 2012; Pitteri et al, 2021; Zucchelli et al, 2016). The tracts with FA and RTOP values are depicted in Figures 4.B and C .…”

“…Specifically, RTOP is associated with the average volume of pores, RTAP to their cross-sectional area and RTPP to their length as detailed in earlier studies, meaning higher values of these metrics reflect a more restricted diffusion in neural tissues (Bogusz et al, 2022; Mitra et al, 1995; Özarslan et al, 2013). These quantitative indices offer valuable information of tissue heterogeneity (Brusini et al, 2018), ischemic stroke (Brusini et al, 2016; Galazzo et al, 2018), multiple sclerosis (Brusini et al, 2021), cognitive impairment detection (Menon et al, 2020; Pitteri et al, 2021), and aging and dementia (Bouhrara et al, 2023).…”