Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens

Author:

Feng Mengmeng1ORCID,Hongwei Hongwei2,Haotian Xin1,Wang Shengpei3,Gao Yian4,Sui Chaofan4,Liang Changhu4,Guo Lingfei4ORCID

Affiliation:

1. Shandong University

2. Southwest University

3. CAS Institute of Automation: Chinese Academy of Sciences Institute of Automation

4. Shandong Provincial Hospital Affiliated to Shandong First Medical University: Shandong Provincial Hospital

Abstract

Abstract Objective To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens. Materials and Methods Probabilistic diffusion tractography and graph theory were used to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Results Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. Conclusions The decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Publisher

Research Square Platform LLC

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