White Matter and Hippocampal Volume Predict the Risk of Dementia in Patients with Cerebral Small Vessel Disease: The RUN DMC Study

痴呆 白质 磁共振弥散成像 高强度 危险系数 心脏病学 前瞻性队列研究 比例危险模型 医学 内科学 部分各向异性 心理学 磁共振成像 疾病 置信区间 放射科
作者
Ingeborg W.M. van Uden,Helena M. van der Holst,Anil M. Tuladhar,Anouk G.W. van Norden,Karlijn F. de Laat,Loes C.A. Rutten‐Jacobs,David G. Norris,Jurgen A.H.R. Claassen,Ewoud J. van Dijk,Roy P. C. Kessels,Frank‐Erik de Leeuw
出处
期刊:Journal of Alzheimer's Disease [IOS Press]
卷期号:49 (3): 863-873 被引量:49
标识
DOI:10.3233/jad-150573
摘要

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).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.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.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.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.
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