Structural Brain Network Measures in Elderly Patients with Cerebral Small Vessel Disease and Depressive Symptoms

Abstract Objectives: To investigate whether there is a difference in the incidence of depression between patients with small cerebral vascular disease (CSVD) and normal controls (NC), and the relationship between depression and white matter fiber damage and structural brain network in elderly patients with CSVD. Method: A total of 115 elderly subjects were consecutively recruited from the neurology clinic, including 36 patients with CSVD with depressive state, 34 patients with CSVD without depressive state, and 45 NCs. A detailed neuropsychological assessment and multimodal MRI were performed. Based on TBSS analysis and structural network analysis, differences between groups were compared, and logistic regression was used to determine the predictive value of TBSS indicators and structural brain network measures for depression in CSVD patients. Results: Group differences were found in global TBSS analysis and brain network measures. After adjusting for age, gender, education level, and vascular risk factors (VRF), there were significant correlations between TBSS indicators and structural network indicators and depression, including: FA (r= -0.291, p <0.05), ELocal (r = -0.278, p < 0.01) and in network strength (r = - 0.403, p < 0.001). At the same time, ELocal was an independent risk factor for depression in patients with CSVD.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 depression. In addition, we believe that abnormal white matter alterations in subcortical neural circuits affect the microstructural function of brain connections, which may be a mechanism for the concomitant depressive symptoms in CSVD patients.