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Predictors for cortical gray matter volume in stroke patients with confluent white matter changes.

Department 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. Department of Psychological Studies and Center for Psychosocial Health and Aging, The Hong Kong Institute of Education, China. Bioinformatics and Imaging Programmatic Cores, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, TX, USA. Department of Radiology and Organ Imaging, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China. Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, 305# East Zhongshan Road, Nanjing, Jiangsu Province, People's Republic of China. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China. Electronic address: vctmok@cuhk.edu.hk.

Journal of the neurological sciences. 2014;(1-2):169-73
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Abstract

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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MeSH terms : Brain ; Leukoencephalopathies