Department of Neurology, Second Hospital of Tianjin Medical University, No.23, Pingjiang Road, Hexi District, Tianjin, 300211, China.
Department of Rehabilitation, Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
BMC Geriatr. 2022 Jul 9;22(1):568. doi: 10.1186/s12877-022-03245-7.
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.
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.
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) (r = - 0.278, p < 0.01) and network strength (r = - 0.403, p < 0.001).
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.
探讨弥散张量成像（DTI）指标与伴有抑郁状态的脑小血管病（CSVD）之间的关系，并探讨 CSVD 伴抑郁时白质损伤的潜在机制。
连续纳入神经内科门诊的 115 名老年患者，包括 36 例伴有抑郁状态的 CSVD 患者（CSVD+D）、34 例无抑郁状态的 CSVD 患者（CSVD-D）和 45 名对照者。所有患者均行详细的神经心理学评估和多模态磁共振成像（MRI）检查。基于基于纤维束空间统计学（TBSS）分析和结构网络分析，比较组间差异，包括白质纤维指标（各向异性分数和平均弥散度）和结构脑网络指标（全局效率、局部效率和网络强度），以探讨三组间 DTI 参数的差异和相关性。
CSVD-D 组和 CSVD+D 组的 CSVD 负荷评分和常规影像学结果无显著差异。DTI 指标存在组间差异（p<0.05），在校正年龄、性别、教育程度和血管危险因素（VRF）后，TBSS 分析指标与抑郁存在显著相关性，包括：各向异性分数（FA）（r=-0.291，p<0.05）、平均弥散度（MD）（r=0.297，p<0.05）；同时，结构网络指标与抑郁也存在显著相关性，包括：局部效率（E）（r=-0.278，p<0.01）和网络强度（r=-0.403，p<0.001）。
DTI 参数中 FA、MD 值和结构网络指标的变化在一定程度上可以预测 CSVD 的抑郁状态，为血管相关性抑郁发病机制中异常神经回路假说提供了更直接的结构基础。此外，皮质下神经回路的异常白质改变可能影响脑连接的微观结构功能，这可能是 CSVD 患者伴发抑郁症状的机制之一。
