CASIA OpenIR  > 脑图谱与类脑智能实验室  > 神经计算与脑机交互
Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses
Li, Jing1; Wen, Hongwei2,3; Wang, Shengpei4,5; Che, Yena6; Zhang, Nan7; Guo, Lingfei7
Source PublicationFRONTIERS IN NEUROLOGY
ISSN1664-2295
2022-02-23
Volume13Pages:12
Corresponding AuthorGuo, Lingfei(glfsci@163.com)
AbstractPurposeThe 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.
Keywordcerebral small vessel disease cerebral microbleeds gray matter volume white matter volume multivariate pattern analysis
DOI10.3389/fneur.2022.819055
WOS KeywordCOGNITIVE FUNCTION ; PERFORMANCE ; BIOMARKERS ; TRAIL ; GYRUS ; FMRI ; IRON
Indexed BySCI
Language英语
WOS Research AreaNeurosciences & Neurology
WOS SubjectClinical Neurology ; Neurosciences
WOS IDWOS:000766885000001
PublisherFRONTIERS MEDIA SA
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/48045
Collection脑图谱与类脑智能实验室_神经计算与脑机交互
Corresponding AuthorGuo, Lingfei
Affiliation1.Capital Med Univ, Beijing Friendship Hosp, Dept Radiol, Beijing, Peoples R China
2.Minist Educ, Key Lab Cognit & Personal, Chongqing, Peoples R China
3.Southwest Univ, Sch Psychol, Chongqing, Peoples R China
4.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Beijing, Peoples R China
6.Shandong First Med Univ, Dept Clin Lab, Shandong Prov Hosp, Jinan, Peoples R China
7.Shandong First Med Univ, Dept Radiol, Shandong Prov Hosp, Jinan, Peoples R China
Recommended Citation
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.
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