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.

使用心脏和大脑容器壁MRI基于定量模型的ESU重新分类 中风是死亡的主要原因，也是全世界永久残疾的主要原因。缺血性中风是 主要的中风品种，约占美国的80％以上的中风。定义特定 缺血性中风的潜在病理生理学对于个性化的二级预防治疗至关重要 最大程度地降低复发事件的风险的目的。但是，即使目前进行大量诊断检查 临床实践，大部分缺血性中风被归类为未确定来源的栓塞中风 （ESU），使这些患者无法根据其特定的病理生理学量身定制最佳治疗。最近的 文献表明，在被诊断为ESU的受试者中，可能存在未发现的病变 在通往心房颤动的路径上的颅内动脉或心脏病理学中的动脉粥样硬化，所谓的 “心脏病”。这意味着有机会提高病因的敏感性和准确性 诊断以减少分类为ESU类别的缺血性中风，允许更具针对性的个性化 二级预防措施。磁共振成像（MRI）/颅外的新发展 动脉粥样硬化和心房心脏病可能会提供新的机会来检测这些目前未检测到的 病变并允许将ESUS患者重新分类为大动脉粥样硬化或心脏符号类别 导致重点治疗策略。 但是，在实践中使用这些成像方法仍然存在重大挑战：1）专业船 墙壁和心脏MRI（ESU-Imaging）以及图像分析算法需要集成到标准中 中风患者的护理工作流程； 2）需要基于模型的分析，结合了新发现 现有临床检查中的ESU成像和发现，以便可以定义新的“风险功能（RFS）” 重新分类； 3）必须研究使用这些RF对中风子类型重新分类的影响 前瞻性。在此提案中，我们计划开发基于模型的分析，该分析侧重于ESU成像和测试 在当前临床检查下被诊断为ESU的急性缺血性中风受试者中的假设 从ESU成像中绘制的新的RF将允许将ESU的子集重新分类为大动脉 动脉粥样硬化或心脏符号类别。具体目的将：1）建立新的容器墙和心脏MRI （ESU成像）和图像分析技术； 2）开发一个结合的多参数统计模型 来自标准中风检查和新ESU成像的信息，以识别一组可以重新分类的RF 缺血性中风病因； 3）评估模型对缺血性卒中亚型重新分类的影响。 如果成功，该建议将有助于建立包括缺血性中风的ESU成像的临床工作流程 进行工作并提供基于模型的算法，以帮助未来的中风子类型分类。