Altered Brain Volume, Microstructure Metrics and Functional Connectivity Features in Multiple System Atrophy

被引:3
作者
Ge, Yunxiang [1 ]
Zheng, Weimin [2 ]
Li, Yujia [1 ]
Dou, Weibei [1 ]
Ren, Shan [3 ]
Chen, Zhigang [3 ]
Wang, Zhiqun [2 ]
机构
[1] Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol BNRist, Dept Elect Engn, Beijing, Peoples R China
[2] Aerosp Ctr Hosp, Dept Radiol, Beijing, Peoples R China
[3] Beijing Univ Chinese Med, Dongfang Hosp, Dept Neurol, Beijing, Peoples R China
来源
FRONTIERS IN AGING NEUROSCIENCE | 2022年 / 14卷
基金
中国国家自然科学基金;
关键词
multiple system atrophy; multimodal MRI; microstructure metrics; extended network-based statistics; support vector machine; VERBAL WORKING-MEMORY; CROSS BUN SIGN; CEREBELLAR CONTRIBUTION; PARKINSONS-DISEASE; MRI; ACTIVATION; DISORDERS; NETWORKS; TRACTOGRAPHY; DIAGNOSIS;
D O I
10.3389/fnagi.2022.799251
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
In order to deeply understand the specific patterns of volume, microstructure, and functional changes in Multiple System Atrophy patients with cerebellar ataxia syndrome (MSA-c), we perform the current study by simultaneously applying structural (T1-weighted imaging), Diffusion tensor imaging (DTI), functional (BOLD fMRI) and extended Network-Based Statistics (extended-NBS) analysis. Twenty-nine MSA-c type patients and twenty-seven healthy controls (HCs) were involved in this study. First, we analyzed the whole brain changes of volume, microstructure, and functional connectivity (FC) in MSA-c patients. Then, we explored the correlations between significant multimodal MRI features and the total Unified Multiple System Atrophy Rating Scale (UMSARS) scores. Finally, we searched for sensitive imaging biomarkers for the diagnosis of MSA-c using support vector machine (SVM) classifier. Results showed significant grey matter atrophy in cerebellum and white matter microstructural abnormalities in cerebellum, left fusiform gyrus, right precentral gyrus and lingual gyrus. Extended-NBS analysis found two significant different connected components, featuring altered functional connectivity related to left and right cerebellar sub-regions, respectively. Moreover, the reduced fiber bundle counts at right Cerebellum_3 (Cbe3) and decreased fractional anisotropy (FA) values at bilateral Cbe9 were negatively associated with total UMSARS scores. Finally, the significant features at left Cbe9, Cbe1, and Cbe7b were found to be useful as sensitive biomarkers to differentiate MSA-c from HCs according to the SVM analysis. These findings advanced our understanding of the neural pathophysiological mechanisms of MSA from the perspective of multimodal neuroimaging.
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页数:13
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