White Matter and Hippocampal Volume Predict the Risk of Dementia in Patients with Cerebral Small Vessel Disease: The RUN DMC Study
Year: 2015
Type: article
Study design: Observational Study
Abstract: BACKGROUND: The relationship between cerebral small vessel disease (SVD) and dementia has been studied without considering white matter (WM) volume, the microstructural integrity of the WM surrounding the SVD, and grey matter (GM). OBJECTIVE: We prospectively investigated the relationship between these structures and the risk of dementia, and formed a prediction model to investigate which characteristics (macro- or microstructural) explained most of the variance. METHODS: The RUN DMC study is a prospective cohort study among 503 non-demented participants with an age between 50 and 85 years at baseline, with baseline assessment in 2006 and follow-up assessment in 2012. Two were lost to follow-up (yielding a 99.6% response-rate). Cox regression analysis was used, to calculate hazard ratios for dementia, of baseline MRI characteristics. Tract-Based Spatial Statistics (TBSS) analysis was used to assess the added value of microstructural integrity of the WM. RESULTS: Mean age at baseline was 65.6 years (SD 8.8) and 56.8% was male. 43 participants developed dementia (8.6%), resulting in a 5.5-year cumulative risk of 11.1% (95% CI 7.7-14.6). Low WM and hippocampal volume are significant predictors for dementia. WM, WM hyperintensities, and hippocampal volume explained most of the variance. TBSS analyses showed no additional value of diffusion parameters. CONCLUSIONS: WM and hippocampal volume were the main predictors for the development of incident dementia at 5-year follow-up in elderly with SVD. There was no additional diagnostic value of the diffusion tensor imaging parameters on top of the macrostructural characteristics.
Source: Journal of Alzheimer s Disease
DOI: 10.3233/jad-150573
Institutions: Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Amphia Ziekenhuis, Haga Hospital, University of Cambridge, Erwin L. Hahn Institute for Magnetic Resonance Imaging, Radboud University Nijmegen, Donders Centre for Cognitive Neuroimaging, University of Duisburg-Essen
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Funder: University of Twente
OpenAlex ID: W1908266351
