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

部分各向异性 磁共振弥散成像 白质 医学 内科学 萧条(经济学) 神经心理学 磁共振成像 物理疗法 精神科 放射科 认知 宏观经济学 经济
作者
Yumeng Gu,Ping Zhao,Wenjun Feng,Xiaoshuang Xia,Xiaolin Tian,Yu Yan,Xiaowen Wang,Decheng Gao,Yanfen Du,Xin Li
出处
期刊:BMC Geriatrics [BioMed Central]
卷期号:22 (1) 被引量:21
标识
DOI:10.1186/s12877-022-03245-7
摘要

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 (E Local ) ( 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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