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: 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
• 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

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) 影响数百万人 美国人中风的风险增加了五倍，中风是死亡和发病的主要原因。约占总数的30% 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，未确定的栓塞性卒中 缺血性中风的另外 30% 是由 ESUS 引起的。当前 AFib 和 ESUS 中的中风风险分层工具（例如， 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 接受治疗并承受不必要的出血风险。越来越多的证据表明 LA 纤维化是一种机械联系 AFib 和 ESUS 之间的合作是一项非常有前途的进步，可以为预防中风开辟新途径。然而，采取 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， 有或没有 AFib。纤维化在洛杉矶具有复杂的结构、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。这是由于相关的困难 实验操作和临床测量的获取。计算建模的进步提供了 解决这一关键知识差距的前所未有的机会。具体来说，该阶段旨在创建一个多尺度、多层次的 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 纤维化模式。我们的中心假设是，LA 纤维化是决定每个人罹患以下疾病的风险的关键机制因素： 由于结构、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 在患者特定的 LA 模型中进行流体建模，特别注意解决纤维化的影响。我们将参数化 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， 非行程控制。目标 2 将使用新的计算框架来系统地表征机械连接 LA 纤维化和血栓形成之间的关系。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 可以通过计算建模来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，研究了纤维化与复发性中风/脑微梗塞风险之间的关系。我们将 检查一组高危 ESUS 患者，但值得注意的是目前没有口服抗凝药物的指征。我们将测试是否 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 血流存在于经历更多不良后果的患者中。我们经过验证的多物理场建模框架将，对于 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

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

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
• 作者: Chahine,Yaacoub;Afroze,Tanzina;Bifulco,SavannahF;Macheret,Fima;Abdulsalam,Nashwa;Boyle,PatrickM;Akoum,Nazem
• 通讯作者: Akoum,Nazem

Assessment of Blood Flow Transport in the Left Ventricle Using Ultrasound. Validation Against 4-D Flow Cardiac Magnetic Resonance.

• DOI: 10.1016/j.ultrasmedbio.2022.05.007
• 发表时间: 2022-09
• 期刊: ULTRASOUND IN MEDICINE AND BIOLOGY
• 影响因子: 2.9
• 作者: Postigo, A. N. D. R. E. A.;Viola, F. E. D. E. R. I. C. A.;Chazo, C. H. R. I. S. T. I. A. N.;Martinez-legazpi, P. A. B. L. O.;Gonzalez-mansilla, A. N. A.;Rodriguez-gonzalez, E. L. E. N. A.;Fernandez-aviles, F. R. A. N. C. I. S. C. O.;Alamo, Juan c del;Ebbers, T. I. N. O.;Bermejo, J. A. V. I. E. R.
• 通讯作者: Bermejo, J. A. V. I. E. R.

Prediction of Shock-Refractory Ventricular Fibrillation During Resuscitation of Out-of-Hospital Cardiac Arrest.

院外心脏骤停复苏期间电击难治性心室颤动的预测。

• DOI: 10.1161/circulationaha.122.063651
• 发表时间: 2023
• 期刊: Circulation
• 影响因子: 37.8
• 作者: Coult,Jason;Yang,BettyY;Kwok,Heemun;Kutz,JNathan;Boyle,PatrickM;Blackwood,Jennifer;Rea,ThomasD;Kudenchuk,PeterJ
• 通讯作者: Kudenchuk,PeterJ

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