脑小血管病白质高信号肾虚证的脑网络特征研究
Study on brain network characteristics of kidney deficiency patients with high white matter hyperintensities in cerebral small vessel disease
高金阳 1林丹 2路一坤 1张硕 1周莹 1马丽芳 1韩笑 1崔方圆1
作者信息
- 1. 北京中医药大学东直门医院 北京 100700
- 2. 北京中医药大学针灸推拿学院
- 折叠
摘要
目的 探究脑白质高信号(white matter hyperintensities,WMH)肾虚型患者的静息态脑网络特征.方法 本研究纳入WMH患者及健康受试者,采集临床及功能磁共振数据.采用局部一致性(ReHo)分析比较2组脑功能活动差异;WMH患者分为肾虚组和非肾虚组,运用独立成分分析(ICA)探究2组脑网络特征.结果 WMH组较健康组的ReHo值在右楔前叶和辅助运动区显著下降、右颞叶显著升高;颞叶的ReHo值与HAMD评分呈正相关趋势.ICA分析显示肾虚组较非肾虚组默认模式网络与额顶网络连接增强,与听觉网络、视觉网络连接减弱.结论 WMH肾虚证患者情绪、认知相关脑区功能连接发生异常,可为此类疾病的防治提供较为客观的参考依据.
Abstract
Objective To explore the characteristics of resting brain network in kidney deficiency pa-tients with high white matter hyperintensities (WMH). Methods Clinical and functional magnetic reso-nance imaging (fMRI) data were collected from patients with WMH and healthy subjects. We analyzed and compared the differences of brain function between the two groups by using regional homogeneity (ReHo). Patients with WMH were divided into kidney deficiency group and non-kidney deficiency group,and independent component analysis (ICA) was used to explore the characteristics of brain net-work. Results Compared with the healthy group,the ReHo value of the WMH groups decreased signifi-cantly in the right precuneus and right supplementary motor area,and increased significantly in the right temporal lobe. The ReHo value of the temporal lobe was positively correlated with HAMD score. ICA a-nalysis showed that the connection between the default mode network and the frontoparietal network in the kidney deficiency group was stronger,while the connection to the auditory network and visual network was weaker in the kidney deficiency group. Conclusion The abnormal functional connections of emo-tional and cognitive brain regions in patients with WMH kidney deficiency syndrome can provide objective reference for the prevention and treatment of these diseases.
关键词
白质高信号/局部一致性/独立成分分析/脑网络/中医证候Key words
white matter hyperintensities/regional homogeneity/independent component analysis/brain network/TCM syndrom引用本文复制引用
基金项目
国家自然科学基金青年基金项目(8200151376)
出版年
2024
国家科技期刊平台
NSTL
万方数据