Quantitative model-based ESUS reclassification using cardiac and cerebral vessel wall MRI

使用心脑血管壁 MRI 进行基于定量模型的 ESUS 重新分类

• 批准号: 10708032
• 负责人: Nazem Akoum
• 金额: $ 75.73万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-21 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708032
• 关键词: Acute; Algorithmic Analysis; Algorithms; Arrhythmia; Arteries; Artificial Intelligence; Atherosclerosis; Atrial Fibrillation; Cardiac; Categories; Cause of Death; Cephalic; Cerebral Infarction; Cerebrum; Classification; Clinical; Coagulation Process; Development; Diagnosis; Diagnostic; Diagnostic Procedure; Diagnostic tests; Etiology; Event; Functional disorder; Future; Goals; Healthcare Systems; Heart; Heart Atrium; Hospitals; Image; Image Analysis; Imaging Techniques; Intervention Trial; Ischemic Stroke; Left; Lesion; Literature; Machine Learning; Magnetic Resonance Imaging; Medicine; Modeling; Pathology; Patients; Pattern; Prevention Measures; Prospective Studies; Protocols documentation; Public Health; Randomized; Recurrence; Risk; Scheme; Secondary Prevention; Source; Statistical Models; Stenosis; Stroke; Subgroup; Techniques; Testing; Training; United States; Universities; Validation; Washington; cardiac magnetic resonance imaging; clinical imaging; clinical practice; deep learning; disability; embolic stroke; follow-up; heart rhythm; imaging modality; improved; individualized medicine; novel; optimal treatments; personalized medicine; predictive modeling; risk minimization; standard of care; stroke patient; targeted treatment; treatment strategy; treatment trial

Quantitative model-based ESUS reclassification using cardiac and cerebral vessel wall MRI Stroke is a major cause of death and the leading cause of permanent disability worldwide. Ischemic stroke is the dominant stroke variety, representing approximately 80+% of strokes in the United States. Defining the specific underlying pathophysiology of ischemic strokes is critical for personalized secondary prevention treatments with the goal of minimizing the risk of recurrent events. However, even with extensive diagnostic workup in current clinical practice, a large portion of ischemic strokes are classified as embolic stroke of undetermined source (ESUS), leaving these patients without optimal treatment tailored to their specific pathophysiology. Recent literature has demonstrated that among subjects diagnosed with ESUS, there may be under-detected lesions of atherosclerosis in intra/extracranial arteries or cardiac pathology on a path towards atrial fibrillation, a so called “atrial cardiopathy”. This implies that there are opportunities to improve the sensitivity and accuracy of etiologic diagnosis to reduce ischemic strokes classified into the ESUS category, allowing for more targeted, personalized secondary prevention measures. New developments in magnetic resonance imaging (MRI) of intra/extracranial atherosclerosis and atrial cardiopathy may provide new opportunities to detect these currently under-detected lesions and allow reclassification of ESUS patients into large-artery atherosclerosis or cardioembolic categories leading to focused treatment strategies. However, there are still significant challenges to using these imaging methods in practice: 1) Specialized vessel wall and cardiac MRI (ESUS-imaging) and image analysis algorithms need to be integrated into the standard of care workflow of stroke patients; 2) A model-based analysis will be needed that combines new findings from ESUS-imaging and findings from existing clinical workup so that new “risk features (RFs)” can be defined for reclassification; and 3) The impact of using these RFs on stroke subtype reclassification needs to be studied prospectively. In this proposal, we plan to develop a model-based analysis focused on ESUS-imaging and test the hypothesis that among acute ischemic stroke subjects diagnosed as ESUS under current clinical workup, a new set of RFs drawn from ESUS-imaging will allow reclassification of a subset of ESUS into large-artery atherosclerosis or cardioembolic categories. The specific aims will: 1) establish new vessel wall and cardiac MRI (ESUS-imaging) and image analysis techniques; 2) develop a multiparametric statistical model that combines information from the standard stroke workup and new ESUS-imaging to identify a set of RFs that can reclassify ischemic stroke etiology; and 3) evaluate the impact of the model on ischemic stroke subtype re-classification. If successful, this proposal will help to establish a clinical workflow that includes ESUS-imaging in ischemic stroke workup and provide a model-based algorithm to assist in future stroke subtype classification.

基于定量模型的心、脑血管壁MRI对ESUS的再分类 中风是世界范围内死亡的主要原因，也是导致永久性残疾的主要原因。缺血性中风是 占主导地位的中风种类，约占美国中风的80%以上。定义特定的 缺血性卒中的基本病理生理学对于个性化二级预防治疗至关重要 将复发事件的风险降至最低的目标。然而，即使在当前进行了广泛的诊断检查 临床实践中，很大一部分缺血性卒中被归类为来源不明的栓塞性卒中 (ESUS)，使这些患者得不到针对其特定病理生理的最佳治疗。近期 文献表明，在被诊断为ESUS的受试者中，可能存在未被发现的病变 导致心房颤动的颅内外动脉的动脉粥样硬化或心脏病理，即所谓的 “房性心脏病”。这意味着有机会提高病因学的敏感性和准确性。 诊断以减少归入ESUS类别的缺血性中风，允许更有针对性、个性化 二级预防措施。颅内外磁共振成像(MRI)的新进展 动脉粥样硬化和房性心脏病可能提供新的机会来检测目前未被发现的这些 并允许将ESUS患者重新分类为大动脉粥样硬化或心脏血栓类别 导致有针对性的治疗策略。 然而，在实践中使用这些成像方法仍然存在巨大的挑战：1)专用血管 壁和心脏磁共振成像(ESUS成像)和图像分析算法需要集成到 中风患者的护理工作流程；2)需要基于模型的分析，结合来自 ESUS-现有临床检查的成像和发现，以便可以为以下对象定义新的“风险特征(RF)” 3)使用这些RF对卒中亚型重新分类的影响需要研究 未雨绸缪。在此提案中，我们计划开发一个基于模型的分析，重点放在ESU-映像和测试上 假设在目前的临床检查下被诊断为ESU的急性缺血性中风患者中， 从ESU提取的新的RF集-成像将允许将ESU的子集重新分类为大动脉 动脉粥样硬化或心源性栓塞症。具体目标是：1)建立新的血管壁和心脏核磁共振 (ESUS-成像)和图像分析技术；2)开发多参数统计模型，将 来自标准卒中检查和新ESUS成像的信息，以识别一组可以重新分类的RF 3)评价模型对缺血性卒中亚型再分类的影响。 如果成功，这项提议将有助于建立包括缺血性中风的ESUS成像在内的临床工作流程 并提供了一种基于模型的算法来辅助将来的卒中亚型分类。