磁共振成像2025，Vol.16Issue(6)：27-33,7.DOI:10.12015/issn.1674-8034.2025.06.004
基于灰质结构协变网络的阿尔茨海默病患者的图论分析
Graph theory analysis of Alzheimer's disease patients based on gray matter structural covariance network
摘要
Abstract
Objective:Alzheimer's disease(AD)can alter brain structure,but there is limited research on the topological properties of structural covariance network(SCN)based on gray matter.Therefore,this study used structural magnetic resonance imaging and graph theory analysis to evaluate changes in SCN in AD patients.Materials and Methods:This study screened 32 AD patients and 29 healthy controls(HC)from the Alzheimer's Disease Neuroimaging Initiative(ADNI)database,followed by T1 high-resolution imaging.The structural images were preprocessed using the SPM8 software package,and the gray matter SCN was constructed using the Graph Analysis Toolbox(GAT).Global and local network metrics were calculated and compared using graph theory analysis.Results:Compared to the HC group,AD patients showed a decrease in global network metrics,including characteristic path length(Lp),clustering coefficient(Cp),assortativity,small-world properties(Lambda,Sigma,Gamma),edge betweenness,node betweenness,and transitivity.Modularity and global efficiency increased,but the differences were not statistically significant according to permutation tests(P>0.05).Additionally,at the minimum density,the node degree in the AD group decreased in regions such as the right calcarine fissure,right fusiform gyrus,and right middle temporal gyrus.Node betweenness decreased in the right cerebellum and right supramarginal gyrus.Node betweenness increased in the right calcarine fissure,left orbital inferior frontal gyrus,left medial superior frontal gyrus,and right olfactory cortex.Cp decreased in the right temporal pole of the middle temporal gyrus and increased in the cerebellar vermis.The differences between the two groups were statistically significant(P<0.05),but after false discovery rate(FDR)correction,the differences were not significant(P>0.05).The area under the curve(AUC)results of standardized node metrics showed that node degree increased in the left cerebellum and left medial superior frontal gyrus in the AD group.Node betweenness increased in the left cerebellum,left orbital middle frontal gyrus,and left medial superior frontal gyrus,while it decreased in the right cerebellum.Cp increased in the right cerebellum and left orbital middle frontal gyrus,and decreased in the right temporal pole of the middle temporal gyrus and left thalamus.Local efficiency was higher in the right cerebellum and lower in the right temporal pole of the superior temporal gyrus in the AD group compared to the HC group,with statistically significant differences(P<0.05).The analysis of target-based and random network attacks showed no significant differences in the remaining network metrics(largest component)between the two groups after node attacks(P>0.05).The AUC results of target-based and random network attacks also showed no significant differences in the remaining network metrics between the two groups(P>0.05).Conclusions:The global and node metrics of SCN in the AD group showed changes,but the remaining network metrics did not significantly change after target-based and random network attacks.These changes in metrics may be related to cognitive impairment in AD patients.关键词
阿尔茨海默病/结构协变网络/图论分析/磁共振成像Key words
Alzheimer's disease/structural covariance network/graph theory analysis/magnetic resonance imaging分类
医药卫生引用本文复制引用
樊丽华,魏伟,陈媛媛,田欣,周锋,于群葳,郑运松..基于灰质结构协变网络的阿尔茨海默病患者的图论分析[J].磁共振成像,2025,16(6):27-33,7.基金项目
2024 Key Research and Development Project of Shaanxi Province(No.2024SF-YBXM-524) （No.2024SF-YBXM-524）
Qin Chuangyuan Traditional Chinese Medicine Industry Innovation Cluster Project(No.L2024-QCY-ZYYJJQ-Y07,Y12). 2024年度陕西省重点研发计划项目(编号:2024SF-YBXM-524) （No.L2024-QCY-ZYYJJQ-Y07,Y12）
秦创原中医药产业创新聚集区项目(编号:L2024-QCY-ZYYJJQ-Y07、Y12) （编号:L2024-QCY-ZYYJJQ-Y07、Y12）
