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Updated: May 3, 2026

A Versatile Murine Model of Subcortical White Matter Stroke for the Study of Axonal Degeneration and White Matter Neurobiology
Published on: March 17, 2016
Predictors for cortical gray matter volume in stroke patients with confluent white matter changes
Yunyun Xiong1, Adrian Wong2, Kelvin Wong3
1Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, 305# East Zhongshan Road, Nanjing, Jiangsu Province, People's Republic of China; Department of Psychological Studies and Center for Psychosocial Health and Aging, The Hong Kong Institute of Education, China.
Background And Purpose:
Our previous study found that cortical gray matter (cGM) volume predicted vascular cognitive impairment independent of age-related white matter changes (WMC). We aimed to investigate predictors for cGM volume in ischemic stroke patients with confluent WMC.
Methods:
One-hundred post-stroke patients with confluent WMC were recruited into the study. All volumetric measures were standardized by intracranial volume as volume ratio. Univariate analyses and multivariate linear regression models were used to test relationship of cGM volume with basic demography, vascular risk factors, APOE status, WMC volume (periventricular and deep WMC), infarct measures (volume, number and location) and microbleed (number, presence and location).
Results:
After controlling for significant variables in the univariate analyses, multivariate linear regression models found that old age (β=-0.288, p=0.001), low triglyceride (β=0.194, p=0.027), periventricular WMC (PVWMC) (β=-0.392, p<0.001) and presence of thalamic microbleed (β=-0.197, p=0.041) were independently predictive of less cGM volume ratio.
Conclusions:
Age, PVWMC and left thalamic microbleed predict less cGM volume.
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