ArticleBMC geriatrics2022
Structural brain network measures in elderly patients with cerebral small vessel disease and depressive symptoms.
Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 26 citations in OpenAlex.
- Tai Chi modulating multimodal connectivity patterns and cognitive function in cerebral small vessel disease.GeroScience · 2026Trial
- Hemispheric imbalance in mild cognitive impairment: a graph-theoretical analysis of multimodal brain networks.Annals of medicine · 2026Article
- Magnetic Resonance Imaging in Cerebral Small Vessel Disease-Related Depression: From Visual Scoring to Artificial Intelligence.CNS neuroscience & therapeutics · 2026Review
- Multimodal MRI and machine learning for identifying depression in cerebral small vessel disease: a multicenter study.BMC medical imaging · 2026Article
- From fragmented neurotechnologies to closed-loop brain health systems: integrating artificial intelligence, digital health, digital twins, and advanced materials for brain disorders.Frontiers in bioengineering and biotechnology · 2026Article
- Multi-marker cerebral small vessel disease score and risk of incident depression: The Framingham Heart Study.Journal of affective disorders · 2026Article
- Association of MRI-Visible Perivascular Spaces with Early White Matter Injury.AJNR. American journal of neuroradiology · 2025Article
- fNIRS evidence of abnormal frontotemporal cortex activation and functional connectivity in depressed patients after stroke: neuromodulatory mechanisms from mild to moderate depression.Frontiers in neurology · 2025Article
- Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states.Frontiers in neurology · 2025Article
- Association of white matter hyperintensity with systemic inflammation markers and cognitive assessments: a cross-sectional study via SHAP analysis.Frontiers in aging neuroscience · 2025Article
- Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease.BMC neuroscience · 2024Article
- Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens.Molecular neurobiology · 2024Article
- Correlation between lenticulostriate arteries and white matter microstructure changes in patients with cerebral small vessel disease.Frontiers in neuroscience · 2023Article
- A new nomogram including total cerebral small vessel disease burden for individualized prediction of early-onset depression in patients with acute ischemic stroke.Frontiers in aging neuroscience · 2022Article
- Association of systemic inflammatory markers with white matter hyperintensities and microstructural injury: an analysis of UK Biobank data.Journal of psychiatry & neuroscience : JPNArticle
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo 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.
methodA 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.
resultsThere 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
conclusionsChanges 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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