Predicting dementia in cerebral small vessel disease using an automatic diffusion tensor image segmentation technique
Stroke Sep 19, 2019
Williams OA, Zeestraten EA, Benjamin P, et al. - Because cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment, with a significant proportion of cases going on to develop dementia, researchers investigated the extent to which diffusion tensor image segmentation technique (DSEG) anticipates both degree of cognitive decline and conversion to dementia, thus providing a useful prognostic procedure. For this investigation, 99 SVD patients (aged 43 to 89 years) had annual MRI scanning (for 3 years) and cognitive assessment (for 5 years). DSEG-θ was employed as a whole-cerebrum measure of SVD severity. According to results, DSEG-θ was significantly associated with decline in executive function and global cognition. Findings suggested that DSEG is a fully automatic technique that offers a precise method for evaluating brain microstructural damage in SVD from a single imaging modality (diffusion tensor imaging). DSEG-θ is an important tool for identifying patients with increased risk of developing dementia with SVD and has potential as a clinical marker of severity of SVD.
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