Mechanistic Relationships Between Fibrosis, Fibrillation, and Stroke: Multi-Scale, Multi-Physics Simulations

纤维化、颤动和中风之间的机制关系：多尺度、多物理场模拟

• 批准号: 10441932
• 负责人: Patrick M Boyle
• 金额: $ 66.13万
• 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: 2022-05-05 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10441932
• 关键词: 3-Dimensional; Address; Affect; American; Anatomy; Anticoagulation; Arrhythmia; Atrial Fibrillation; Attention; Attenuated; Biomechanics; Blood flow; Brain; Calibration; Cardiac; Cine Magnetic Resonance Imaging; Clinical; Clinical Research; Coagulation Process; Collagen; Communities; Complex; Computer Models; Custom; Data; Dependence; Deposition; Diagnosis; Disease; Electrophysiology (science); Elements; Enrollment; Equipoise; Evaluation; Event; Fibrosis; Gadolinium; Goals; Heart; Heart Abnormalities; Heart Atrium; Hemorrhage; Image; Individual; Infrastructure; Ischemic Stroke; Knowledge; Lead; Left; Link; Liquid substance; MRI Scans; Magnetic Resonance Imaging; Measurement; Measures; Mediating; Medical Imaging; Modeling; Morbidity - disease rate; Motion; Muscle Cells; Oral; Outcome; Output; Patients; Pattern; Persons; Phase; Physics; Predisposition; Recurrence; Risk; Role; Running; Shapes; Source; Stroke; Stroke prevention; Structure; Testing; Thromboembolism; Thrombosis; Thrombus; Time; Validation; Work; adverse outcome; appendage; base; bioelectricity; brain magnetic resonance imaging; cerebral microinfarct; clinical risk; cohort; comorbidity; computer framework; demographics; design; embolic stroke; experience; experimental study; follow-up; heart rhythm; hemodynamics; high risk; improved; innovation; insight; mortality; multimodality; predictive test; prospective; recruit; risk stratification; simulation; stroke risk; stroke therapy; thromboembolic stroke; thrombogenesis; thrombotic; tool

The main goals of this project are to identify mechanisms underlying thrombogenesis in patients with left atrial (LA) fibrosis and to validate this new knowledge via a prospective proof-of-concept clinical study. Atrial fibrillation (AFib) affects millions of Americans and carries a five-fold increased risk of stroke, a leading cause of mortality and morbidity. Around 30% of all ischemic strokes are caused by thromboembolism in AFib patients. In patients without AFib, embolic strokes of undetermined source (ESUS) account for an additional 30% of ischemic strokes. Current stroke risk stratification tools in AFib and ESUS (e.g., CHA2DS2-VASc) are deficient in predictive accuracy, leaving many patients either under-treated for stroke prevention or over- treated and subjected to unnecessary bleeding risk. The growing evidence that LA fibrosis serves as a mechanistic nexus between AFib and ESUS is a very promising advance that could open new avenues for stroke prevention. However, taking advantage of this opportunity requires detailed knowledge of the mechanism(s) by which fibrotic atria are prone to thrombosis, with or without AFib. Fibrosis has complex structural, electrical, and contractile effects in the LA. These phenomena may independently or synergistically influence thrombosis risk by altering LA hemodynamics, but prior work has not systematically assessed inter-dependencies or clarified each factor’s relative importance. This is due to difficulties associated with experimental manipulation and acquisition of clinical measurements. Advances in computational modeling offer an unprecedented opportunity to address this critical knowledge gap. Specifically, the stage is set to create a multi-scale, multi- physics framework that can comprehensively simulate the pro-thrombotic potential of each unique patient-specific LA fibrosis pattern. Our central hypothesis is that LA fibrosis is a key mechanistic factor in determining each individual’s risk of thromboembolic stroke due to structural, electrical, and contractile factors. Our approach consists of three specific aims. Aim 1 will develop and calibrate a computational framework that integrates electrophysiological, biomechanical, and mechano- fluidic modeling in patient-specific LA models, paying special attention to resolving the effects of fibrosis. We will parameterize the framework using multi-modality magnetic resonance imaging acquisitions in AFib patients with prior stroke and non-AFib, non-stroke controls. Aim 2 will use the new computational framework to systematically characterize mechanistic connections between LA fibrosis and thrombogenesis. We will examine how each individual’s mix of fibrosis extent/pattern, LA anatomy, and susceptibility to emergent electromechanical phenomena combine (with or without simulated AFib) to create a thrombogenic milieu that can be characterized by computational modeling. Aim 3 will validate the mechanistic connections between fibrosis and risk of recurrent stroke/brain microinfarction in a proof-of-concept prospective clinical study. We will examine a high-risk cohort of ESUS patients, but notably without a current indication for oral anticoagulation. We will test if model-predicted thrombogenic combinations of LA shape, fibrosis pattern, deranged electromechanics, and disrupted blood flow exist in patients who experience more adverse outcomes. Our validated multi-physics modeling framework will, for the first time, yield new insight on fibrosis-mediated stroke mechanisms, and pave the way for new treatments for millions of patients who are borderline candidates for anticoagulation (e.g., individuals with ESUS or AFib with intermediate risk scores).

本项目的主要目标是确定左心房（LA）纤维化患者血栓形成的潜在机制 并通过前瞻性概念验证临床研究来验证这一新知识。心房颤动（AFib）影响数百万人 在美国人中，中风的风险增加了五倍，中风是死亡率和发病率的主要原因。大约30% 缺血性中风由AFib患者的血栓栓塞引起。在无房颤的患者中， 来源（ESUS）占缺血性中风另外30%。目前AFib和ESUS中的卒中风险分层工具（例如， CHA 2DS 2-VASc）在预测准确性方面存在缺陷，导致许多患者在预防卒中方面治疗不足或过度治疗。 接受治疗并承受不必要的出血风险。越来越多的证据表明，左心房纤维化是一种机制性联系， AFib和ESUS之间的联系是一个非常有前途的进展，可以为预防中风开辟新的途径。但以 这种机会的优点需要详细了解纤维化心房易于血栓形成的机制， 有或没有房颤。纤维化在LA中具有复杂的结构、电和收缩效应。这些现象可能 通过改变LA血流动力学独立或协同影响血栓形成风险，但先前的工作尚未系统地 评估相互依赖性或澄清每个因素的相对重要性。这是由于与以下方面有关的困难： 实验操作和临床测量的获取。计算建模的进步提供了一个 这是一个前所未有的机会，可以弥补这一关键的知识差距。具体而言，该阶段旨在创建一个多尺度、多层次的 物理框架，可全面模拟每种独特患者特异性LA的促血栓形成潜力 纤维化模式。我们的中心假设是，LA纤维化是决定每个个体的风险的关键机制因素。 血栓栓塞性中风，由于结构，电气和收缩因素。我们的方法包括三个具体目标。 目标1将开发和校准一个计算框架，整合电生理学，生物力学和机械力学， 在患者特异性LA模型中进行流体建模，特别注意解决纤维化的影响。我们会进行急救 该框架在既往卒中和非AFib的AFib患者中使用多模态磁共振成像采集， 非中风控制。目标2将使用新的计算框架来系统地描述机械连接 左心房纤维化和血栓形成之间的联系我们将研究每个人的纤维化程度/模式，LA解剖结构， 和对紧急机电现象的易感性结合联合收割机（有或没有模拟房颤）， 可以通过计算建模表征的血栓形成环境。目标3将验证机械连接 在一项概念验证前瞻性临床研究中，纤维化与复发性卒中/脑微梗死风险之间的关系。我们将 检查ESUS患者的高风险队列，但值得注意的是，目前没有口服抗凝剂的适应症。我们将测试如果 模型预测的LA形状、纤维化模式、紊乱的机电和破裂的血液的血栓形成组合 血流存在于经历更多不良结果的患者中。我们经过验证的多物理场建模框架将为 第一次，对纤维化介导的中风机制产生新的见解，并为数百万人的新治疗铺平道路。 抗凝治疗的边缘候选者的患者（例如，具有中等风险评分的ESUS或AFib个体）。