ArticleAnnals of clinical and translational neurology2024
The thalamic covariance network is associated with cognitive deficits in patients with cerebral small vascular disease.
Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 6 citations in OpenAlex.
- Dynamic reorganization of individual-level morphological networks in unilateral frontal lobe low-grade gliomas: a longitudinal study.Journal of neuro-oncology · 2025Article
- Review
- Long-term impact of white matter hyperintensities and amyloid beta on thalamic subregions in cerebral small vessel disease: A prospective cohort study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease.Neuroradiology · 2025Article
- Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states.Frontiers in neurology · 2025Article
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11 authors at 1 institution in 1 country.
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Abstract
objectiveAbnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico-cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI).
methodsWe performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD-CI), 85 patients without CI (CSVD-NC), and 108 healthy controls using source-based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population.
resultsThe results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD-CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD-NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier.
interpretationOur findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients.
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