阿尔茨海默病患者大脑形态学及结构协变网络的改变OA北大核心CSTPCD

Objective:To investigate the alteration of cerebral grey matter volume and cortical thickness and structural covariance network (SCN) based on cortical thickness in patients with Alzheimer's disease (AD). Materials and Methods:In this study,a total of 100 patients with AD and 150 healthy controls (HCs) were included. Firstly,we conducted voxel-based morphometry (VBM) and surface-based morphometry (SBM) analysis in Computational Anatomy Toolbox 12 (CAT12) to acquire grey matter volume and cortical thickness. Subsequently,partial correlation analysis was applied to explore the correlation between brain regions with statistical differences and cognitive scales. Lastly,we constructed the SCN based on cortical thickness and analyzed its alternation of topology properties by graph theory analysis. Results:Firstly,we observed the decreased grey matter volume and cortical thickness in patients with AD[P-values after family-wise error (FEW) correction,PFWE-corr<0.001]. The volumetrically decreased brain regions included bilateral hippocampus,bilateral orbitofrontal cortex,left insula,right inferior occipital gyrus,left precuneus,left precentral gyrus,left middle cingulate gyrus. The cerebral regions with thinner cortical thickness in AD group included bilateral temporal lobe,frontal lobe,parietal lobe,cingulate gyrus,fusiform gyrus,insula,precuneus,et al. Secondly,partial correlation analysis in AD group showed that Mini-Mental State Examination (MMSE) scores were respectively positively correlated to the volumes of right hippocampus[rs=0.35,P-values after false discovery rate (FDR) correction,PFDR-corr<0.001],left hippocampus (rs=0.38,PFDR-corr<0.001),the thickness of right fusiform gyrus (rs=0.38,PFDR-corr<0.001),and the clinical dementia rating sum of boxes (CDR-SB) scores was negatively correlated to the thickness of left fusiform gyrus (rs=−0.39,PFDR-corr<0.001). Lastly,in SCN analysis,we found the global efficiency (P<0.001),local efficiency (P=0.03),sigma (P<0.001) were higher in AD patients compared to HCs,while the shortest path length (P<0.001) was lower in AD patients. Conclusions:The combination of morphological analysis by VBM and SBM and SCN analysis by graph theory was helpful to comprehensively understand the reconfiguration of brain networks and its significance,and thus provided new insights and evidence for neuroimaging changes in AD patients.