Dynamic functional network connectivity in patients with a mismatch between white matter hyperintensity and cognitive function - Zeng, Siyuan; Ma, Lin; Mao, Haixia; Shi, Yachen; Xu, Min; Gao, Qianqian; Kaidong, Chen; Li, Mingyu; Ding, Yuxiao; Ji, Yi; Hu, Xiaoyun; Feng, Wang; et al. (Frontiers in Aging Neuroscience, 2024)
Objective White matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective. Methods The resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system. Results The 149 CSVD patients included 20 cases of “Type I mismatch,” 51 cases of Type I match, 38 cases of “Type II mismatch,” and 40 cases of “Type II match.” Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between “Type I match” and “Type I mismatch”; the FT of States 1 and 4 differed significantly between “Type II match” and “Type II mismatch.” Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between “Type I match” and “Type I mismatch,” while the left MTA score differed between “Type II match” and “Type II mismatch.” Conclusion Different mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.