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

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.

Association Between Major Depressive Disorder and the Development of Cerebral Small Vessel Disease: A Mendelian Randomization Study

“…Numerous epidemiological studies have investigated the intricate reciprocal association between MDD (or depression) and cerebral WM lesions (Gu et al, 2022; Pasi et al, 2016; Zhang et al, 2021). Patients with CSVD exhibiting depressive symptoms demonstrate a notable decrease in network efficiency and WM integrity compared to their counterparts without such symptoms (Lu et al, 2022; van Uden et al, 2015).…”

A new nomogram including total cerebral small vessel disease burden for individualized prediction of early-onset depression in patients with acute ischemic stroke

“…The hemodynamic neurovascular coupling ensures a strong increase in cerebral blood flow and a fast increase in neuronal glucose uptake in the case of acute incidents of the brain (Popa-Wagner et al, 2015 ). When patients with CSVD suffer from a sudden attack of acute ischemic stroke, the compensatory ability of the brain is weaker, thus, it is more likely to damage the depression-related network such as the frontal-subcortical circuit (Brookes et al, 2014 ; Arba et al, 2017b ; van Agtmaal et al, 2017 ; Gu et al, 2022 ). In addition, local vascular inflammation contributes to the development of PSD (Spalletta et al, 2006 ).…”

Correlation between lenticulostriate arteries and white matter microstructure changes in patients with cerebral small vessel disease

“…The patient diagnoses were confirmed by trained neurologists. The inclusion criteria were: (1) age 45 to 80 years; (2) a clinical diagnosis of motor and sensory syndrome due to lacunar infarction or an imaging diagnosis of neuroanatomically corresponding RSSIs, CMB, EPVS (grade 2–4), cSS, and WMH (Fazekas score ≥2) ( Hassan et al, 2003 ); and (3) right-handedness ( Gu et al, 2022 ). The exclusion criteria were: (1) large vessel disease with >50% stenosis of intra- or extra-cranial arteries; (2) severe cerebral disease, such as massive cerebral hemorrhage and infarction, intracranial infection, cerebrovascular malformation, intracranial aneurysm, moyamoya disease, etc.…”

“…(1) age 45 to 80 years; (2) a clinical diagnosis of motor and sensory syndrome due to lacunar infarction or an imaging diagnosis of neuroanatomically corresponding RSSIs, CMB, EPVS (grade 2-4), cSS, and WMH (Fazekas score ≥2) (Hassan et al, 2003); and (3) right-handedness (Gu et al, 2022). The exclusion criteria were:…”

“…Tract-based spatial statistics (TBSS) can be applied to DTI analysis to negate the prominent contamination of data from cerebrospinal fluid (CBF) by focusing on the main fiber tracts ( Metzler-Baddeley et al, 2012 ). TBSS-based image analysis has revealed widespread disruption of the white matter microstructure in CSVD patients who have developed depressive states ( Gu et al, 2022 ) and apathy ( Saleh et al, 2021 ).…”