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Published in: BMC Geriatrics 1/2022

Open Access 01-12-2022 | Cerebral Small Vessel Disease | Research

Structural brain network measures in elderly patients with cerebral small vessel disease and depressive symptoms

Authors: Yumeng Gu, Ping Zhao, Wenjun Feng, Xiaoshuang Xia, Xiaolin Tian, Yu Yan, Xiaowen Wang, Decheng Gao, Yanfen Du, Xin Li

Published in: BMC Geriatrics | Issue 1/2022

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Abstract

Objectives

To investigate the relationship between diffusion tensor imaging (DTI) indicators and cerebral small vessel disease (CSVD) with depressive states, and to explore the underlying mechanisms of white matter damage in CSVD with depression.

Method

A total of 115 elderly subjects were consecutively recruited from the neurology clinic, including 36 CSVD patients with depressive state (CSVD+D), 34 CSVD patients without depressive state (CSVD-D), and 45 controls. A detailed neuropsychological assessment and multimodal magnetic resonance imaging (MRI) were performed. Based on tract-based spatial statistics (TBSS) analysis and structural network analysis, differences between groups were compared, including white matter fiber indicators (fractional anisotropy and mean diffusivity) and structural brain network indicators (global efficiency, local efficiency and network strength), in order to explore the differences and correlations of DTI parameters among the three groups.

Results

There were no significant differences in terms of CSVD burden scores and conventional imaging findings between the CSVD-D and CSVD+D groups. Group differences were found in DTI indicators (p <  0.05), after adjusting for age, gender, education level, and vascular risk factors (VRF), there were significant correlations between TBSS analysis indicators and depression, including: fractional anisotropy (FA) (r = − 0.291, p <  0.05), mean diffusivity (MD) (r = 0.297, p < 0.05), at the same time, between structural network indicators and depression also show significant correlations, including: local efficiency (ELocal) (r = − 0.278, p < 0.01) and network strength (r = − 0.403, p < 0.001).

Conclusions

Changes in FA, MD values and structural network indicators in DTI parameters can predict the depressive state of CSVD to a certain extent, providing a more direct structural basis for the hypothesis of abnormal neural circuits in the pathogenesis of vascular-related depression. In addition, abnormal white matter alterations in subcortical neural circuits probably affect the microstructural function of brain connections, which may be a mechanism for the concomitant depressive symptoms in CSVD patients.
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Metadata
Title
Structural brain network measures in elderly patients with cerebral small vessel disease and depressive symptoms
Authors
Yumeng Gu
Ping Zhao
Wenjun Feng
Xiaoshuang Xia
Xiaolin Tian
Yu Yan
Xiaowen Wang
Decheng Gao
Yanfen Du
Xin Li
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Geriatrics / Issue 1/2022
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/s12877-022-03245-7

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