Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses

doi:10.3389/fneur.2022.819055

	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, Yena 6; Zhang, Nan 7; Guo, Lingfei 7
发表期刊	FRONTIERS IN NEUROLOGY
ISSN	1664-2295
	2022-02-23
卷号	13 页码:12
通讯作者	Guo, Lingfei(glfsci@163.com)
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.
关键词	cerebral small vessel disease cerebral microbleeds gray matter volume white matter volume multivariate pattern analysis
DOI	10.3389/fneur.2022.819055
关键词[WOS]	COGNITIVE FUNCTION ; PERFORMANCE ; BIOMARKERS ; TRAIL ; GYRUS ; FMRI ; IRON
收录类别	SCI
语种	英语
WOS研究方向	Neurosciences & Neurology
WOS类目	Clinical Neurology ; Neurosciences
WOS记录号	WOS:000766885000001
出版者	FRONTIERS MEDIA SA
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48045
专题	脑图谱与类脑智能实验室_神经计算与脑机交互
通讯作者	Guo, Lingfei
作者单位	1.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
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.