中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 脑图谱与类脑智能实验室
  5. 神经计算及脑机交互
Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses

文献类型：期刊论文

作者Li, Jing7; Wen, Hongwei5,6; Wang, Shengpei3,4; Che, Yena2; Zhang, Nan1; Guo, Lingfei1
刊名FRONTIERS IN NEUROLOGY
出版日期2022-02-23
卷号13页码:12
ISSN号1664-2295
关键词cerebral small vessel disease cerebral microbleeds gray matter volume white matter volume multivariate pattern analysis
DOI10.3389/fneur.2022.819055
通讯作者Guo, Lingfei(glfsci@163.com)
英文摘要PurposeThe objective of this study was to evaluate whether altered gray matter volume (GMV) and white matter volume (WMV) are associated with the presence of cerebral microbleeds (CMBs) in cerebral small vessel disease (CSVD). Materials and MethodsIn this study, we included 26 CSVD patients with CMBs (CSVD-c), 43 CSVD patients without CMBs (CSVD-n) and 39 healthy controls. All participants underwent cognitive assessment testing. Both univariate analysis and multivariate pattern analysis (MVPA) approaches were applied to investigate differences in brain morphometry among groups. ResultsIn univariate analysis, GMV and WMV differences were compared among groups using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL). Compared to healthy controls, the CSVD-c group and CSVD-n group showed significantly lower GMV than the control group in similar brain clusters, mainly including the right superior frontal gyrus (medial orbital), left anterior cingulate gyrus, right inferior frontal gyrus (triangular part) and left superior frontal gyrus (medial), while the CSVD-n group also showed significantly lower WMV in the cluster of the left superior frontal gyrus (medial). No significant GMV or WMV differences were found between the CSVD-c group and the CSVD-n group. Specifically, we applied the multiple kernel learning (MKL) technique in MVPA to combine GMV and WMV features, yielding an average of >80% accuracy for three binary classification problems, which was a considerable improvement over the individual modality approach. Consistent with the univariate analysis, the MKL weight maps revealed default mode network and subcortical region damage associated with CSVD compared to controls. On the other hand, when classifying the CSVD-c group and CSVD-n group in the MVPA analysis, we found that some WMVs were highly weighted regions (left olfactory cortex and right middle frontal gyrus), which hinted at the presence of different white matter alterations in the CSVD-c group. ConclusionOur findings not only suggested that the localized alterations in GMV and WMV appeared to be associated with the pathophysiology of CSVD but also indicated that altered brain morphometry could be a potential discriminative pattern to detect CSVD at the individual level.
WOS关键词COGNITIVE FUNCTION ; PERFORMANCE ; BIOMARKERS ; TRAIL ; GYRUS ; FMRI ; IRON
WOS研究方向Neurosciences & Neurology
语种英语
出版者FRONTIERS MEDIA SA
WOS记录号WOS:000766885000001
源URL[http://ir.ia.ac.cn/handle/173211/48044]  
专题类脑智能研究中心_神经计算及脑机交互
通讯作者Guo, Lingfei
作者单位1.Shandong First Med Univ, Dept Radiol, Shandong Prov Hosp, Jinan, Peoples R China
2.Shandong First Med Univ, Dept Clin Lab, Shandong Prov Hosp, Jinan, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
5.Southwest Univ, Sch Psychol, Chongqing, Peoples R China
6.Minist Educ, Key Lab Cognit & Personal, Chongqing, Peoples R China
7.Capital Med Univ, Beijing Friendship Hosp, Dept Radiol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Li, Jing,Wen, Hongwei,Wang, Shengpei,et al. Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses[J]. FRONTIERS IN NEUROLOGY,2022,13:12.
APA Li, Jing,Wen, Hongwei,Wang, Shengpei,Che, Yena,Zhang, Nan,&Guo, Lingfei.(2022).Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses.FRONTIERS IN NEUROLOGY,13,12.
MLA Li, Jing,et al."Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses".FRONTIERS IN NEUROLOGY 13(2022):12.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。