Giese Anne-Katrin, Schirmer Markus D, Donahue Kathleen L, Cloonan Lisa, Irie Robert, Winzeck Stefan, Bouts Mark J R J, McIntosh Elissa C, Mocking Steven J, Dalca Adrian V, Sridharan Ramesh, Xu Huichun, Frid Petrea, Giralt-Steinhauer Eva, Holmegaard Lukas, Roquer Jaume, Wasselius Johan, Cole John W, McArdle Patrick F, Broderick Joseph P, Jimenez-Conde Jordi, Jern Christina, Kissela Brett M, Kleindorfer Dawn O, Lemmens Robin, Lindgren Arne, Meschia James F, Rundek Tatjana, Sacco Ralph L, Schmidt Reinhold, Sharma Pankaj, Slowik Agnieszka, Thijs Vincent, Woo Daniel, Worrall Bradford B, Kittner Steven J, Mitchell Braxton D, Rosand Jonathan, Golland Polina, Wu Ona, Rost Natalia S
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Neurol Genet. 2017 Aug 24;3(5):e180. doi: 10.1212/NXG.0000000000000180. eCollection 2017 Oct.
To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI-GENetics Interface Exploration (MRI-GENIE) study.
MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.
The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
描述在急性缺血性卒中（AIS）患者临床MRI上检测到的急性和慢性脑血管神经影像表型的基因分析设计及基本原理，该研究属于MRI基因接口探索（MRI-GENIE）研究范畴。
MRI-GENIE利用卒中基因网络（SiGN）的现有基础设施。共有12个国际SiGN站点提供了3301例AIS患者的MRI。所有参与者均可获得基于网络的卒中病因分类（CCS）系统的详细临床表型分析以及全基因组基因分型数据。神经影像分析包括对既定MRI标记物的手动和自动评估。将针对急性和慢性病变的一部分扫描开发一种用于临床扫描中脑血管病变自动评估的高通量MRI分析流程，对照金标准进行验证，并应用于所有可用扫描。提取的神经影像表型将改善缺血性卒中急性和慢性脑血管病变的特征描述，包括CCS亚型及其对卒中后功能结局的影响。此外，基因检测将揭示与脑血管疾病急性和慢性MRI表现相关的变异。
MRI-GENIE研究旨在开发、验证和分发用于AIS患者临床护理中获取的扫描的MRI分析平台，这将带来（1）缺血性卒中的新基因发现，（2）个性化卒中风险评估策略，以及（3）个性化卒中结局评估。
