Magnetic resonance imaging manifestations of cerebral small vessel disease:automated quantification and clinical application

作     者：Lei Zhao Allan Lee Yu-Hua Fan Vincent C.T.Mok Lin Shi Zhao Lei;Lee Allan;Fan Yu-Hua;Mok Vincent C.T.;Shi Lin

作者机构：BrainNow Research InstituteShenzhenGuangdong 518000China Department of NeurologyThe First Affiliated HospitalSun Yat-sen UniversityGuangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological DiseasesNational Key Clinical Department and Key Discipline of NeurologyGuangzhouGuangdong 510080China Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong Kong 999077China Gerald Choa Neuroscience CentreMargaret KL Cheung Research Centre for Management of ParkinsonismTherese Pei Fong Chow Research Centre for Prevention of DementiaLui Che Woo Institute of Innovative MedicineThe Chinese University of Hong KongHong Kong 999077China Department of Imaging and Interventional RadiologyThe Chinese University of Hong KongHong Kong 999077China 

出 版 物：《Chinese Medical Journal》 (中华医学杂志（英文版）)

年 卷 期：2021年第134卷第2期

页      面：151-160页

核心收录：

学科分类：1002[医学-临床医学] 100204[医学-神经病学] 10[医学] 

基　　金：supported partially by grants from the National Key Research and Development Program of China(No.2016YFC1300600) Research Grants Council of the Hong Kong Special Administrative Region,China(No.CUHK 14204117)。 

主　　题：Cerebral small vessel disease Neuroimaging manifestations Automated quantification Clinical relevance 

摘      要：The common cerebral small vessel disease(CSVD)neuroimaging features visible on conventional structural magnetic resonance imaging include recent small subcortical infarcts,lacunes,white matter hyperintensities,perivascular spaces,microbleeds,and brain atrophy.The CSVD neuroimaging features have shared and distinct clinical consequences,and the automatic quantification methods for these features are increasingly used in research and clinical settings.This review article explores the recent progress in CSVD neuroimaging feature quantification and provides an overview of the clinical consequences of these CSVD features as well as the possibilities of using these features as endpoints in clinical trials.The added value of CSVD neuroimaging quantification is also discussed for researches focused on the mechanism of CSVD and the prognosis in subjects with CSVD.