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

基本信息

批准号：
10617841
负责人：
Patrick M Boyle
金额：
$ 63.43万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
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/10617841
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 Deposition Diagnosis Disease Electrophysiology (science)Elements Enrollment Equipoise Evaluation Event Experimental Designs Fibrosis Gadolinium Goals Heart Heart Abnormalities Heart Atrium Hemorrhage Image Individual Infrastructure Ischemic Stroke Knowledge Left Link MRI Scans Magnetic Resonance Imaging Maps Measurement Measures Mediating Medical Imaging Modeling Morbidity - disease rate Motion Muscle Cells Oral Outcome Output Patients Pattern Persons Phase Physics Populations at Risk Predisposition Recurrence Risk Risk Estimate Role Running Shapes Source Stroke Stroke prevention Structure Testing Thromboembolism Thrombosis Thrombus Time Validation Work adverse outcome appendage bioelectricity brain magnetic resonance imaging cerebral microinfarct clinical risk cohort comorbidity computer framework demographics embolic stroke experience follow-up heart rhythm hemodynamics high risk improved innovation insight mortality multimodality predictive modeling prospective recruit risk stratification simulation stroke risk stroke therapy structural determinants thromboembolic stroke thrombogenesis tool

项目摘要

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).

该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）影响了数百万人。美国人患中风的风险增加了五倍，中风是导致死亡和发病的主要原因。缺血性中风是由 AFib 患者的血栓栓塞引起的。在没有 AFib 的患者中，未确定的栓塞性中风。目前 AFib 和 ESUS 中的卒中风险分层工具（例如，ESUS）占缺血性卒中的另外 30%。 CHA2DS2-VASc）的预测准确性不足，导致许多患者要么未得到充分的中风预防治疗，要么过度治疗越来越多的证据表明，LA 纤维化治疗是一种机械联系。 AFib 和 ESUS 之间的研究是一项非常有前途的进展，可以为预防中风开辟新的途径。利用这个机会需要详细了解纤维化心房容易形成血栓的机制，无论有或没有 AFib，纤维化都会对 LA 产生复杂的结构、电和收缩影响。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相关的困难。计算模型的实验操作和获取提供了一种方法。解决这一关键知识差距的前所未有的机会具体来说，是创建一个多尺度、多层次的平台。物理框架，可以全面模拟每个独特的患者特异性 LA 的促血栓潜力我们的中心假设是 LA 纤维化是决定每个人患纤维化风险的关键机制因素。由结构、电和收缩因素引起的血栓栓塞性中风我们的方法包括三个具体目标。目标 1 将开发和校准一个集成电生理学、生物力学和机械学的计算框架我们将参数化患者特异性 LA 模型中的流体模型，特别注意解决纤维化的影响。该框架使用多模态磁共振成像采集患有既往中风和非 AFib 的 AFib 患者，目标 2 将使用新的计算框架来系统地表征机械连接。我们将检查每个人的纤维化程度/模式、LA 解剖结构、和对突发机电现象的敏感性相结合（有或没有模拟 AFib）来创建目标 3 将验证可通过计算建模表征的血栓形成环境。我们将在一项概念验证前瞻性临床研究中研究纤维化与复发性中风/脑微梗死的风险之间的关系。检查一组高危 ESUS 患者，但特别是目前没有口服抗凝药物的指征，我们将测试是否存在这种情况。模型预测的 LA 形状、纤维化模式、机电紊乱和血液紊乱的血栓形成组合我们经过验证的多物理建模框架将存在于经历更多不良后果的患者中。首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方法铺平道路处于抗凝治疗边缘候选者的患者（例如，具有中等风险评分的 ESUS 或 AFib 患者）。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Pulmonary vein flow split effects in patient-specific simulations of left atrial flow.

DOI：
10.1016/j.compbiomed.2023.107128
发表时间：
2023-09
期刊：
Computers in biology and medicine
影响因子：
7.7
作者：
通讯作者：

Cryoballoon temperature parameters during cryoballoon ablation predict pulmonary vein reconnection and atrial fibrillation recurrence.

冷冻球囊消融期间的冷冻球囊温度参数可预测肺静脉重新连接和心房颤动复发。

DOI：
10.1007/s10840-022-01429-0
发表时间：
2023
期刊：
Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
影响因子：
0
作者：
Chahine,Yaacoub;Afroze,Tanzina;Bifulco,SavannahF;Macheret,Fima;Abdulsalam,Nashwa;Boyle,PatrickM;Akoum,Nazem
通讯作者：
Akoum,Nazem

MRI-quantified left atrial epicardial adipose tissue predicts atrial fibrillation recurrence following catheter ablation.

DOI：
10.3389/fcvm.2022.1045742
发表时间：
2022
期刊：
Frontiers in cardiovascular medicine
影响因子：
3.6
作者：
通讯作者：

Epicardial adipose tissue is associated with left atrial volume and fibrosis in patients with atrial fibrillation.

DOI：
10.3389/fcvm.2022.1045730
发表时间：
2022
期刊：
Frontiers in cardiovascular medicine
影响因子：
3.6
作者：
通讯作者：

Non-Newtonian blood rheology impacts left atrial stasis in patient-specific simulations.

DOI：
10.1002/cnm.3597
发表时间：
2022-06
期刊：
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
影响因子：
2.1
作者：
Gonzalo, Alejandro;Garcia-Villalba, Manuel;Rossini, Lorenzo;Duran, Eduardo;Vigneault, Davis;Martinez-Legazpi, Pablo;Flores, Oscar;Bermejo, Javier;McVeigh, Elliot;Kahn, Andrew M.;del Alamo, Juan C.
通讯作者：
del Alamo, Juan C.