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脑小血管病的磁共振成像表现:自动化定量分析及临床应用

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

机构信息

BrainNow Research Institute, Shenzhen, Guangdong 518000, China.

Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University; Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, Guangdong 510080, China.

出版信息

Chin Med J (Engl). 2020 Dec 16;134(2):151-160. doi: 10.1097/CM9.0000000000001299.

Abstract

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.

摘要

常见的脑小血管病(CSVD)神经影像学特征在常规结构磁共振成像上可见,包括近期皮质下小梗死、腔隙、脑白质高信号、血管周围间隙、微出血和脑萎缩。CSVD 神经影像学特征具有共同和独特的临床后果,这些特征的自动量化方法越来越多地用于研究和临床环境中。本文综述了 CSVD 神经影像学特征量化的最新进展,并概述了这些 CSVD 特征的临床后果,以及将这些特征用作临床试验终点的可能性。还讨论了 CSVD 神经影像学量化在 CSVD 机制研究和 CSVD 患者预后研究中的附加值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7711/7817342/fb130c6c66bb/cm9-134-151-g001.jpg

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