Patient-specific thrombosis risk in atrial fibrillation by 4D CT imaging of atrial kinetics combined with computational fluid dynamics

通过心房动力学 4D CT 成像结合计算流体动力学研究心房颤动患者特异性血栓形成风险

• 批准号: 10317985
• 负责人: ANDREW KAHN
• 金额: $ 73.46万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10317985
• 关键词: Affect; Age; Algorithms; Anatomy; Anticoagulation; Arrhythmia; Atrial Fibrillation; Blood; Blood Viscosity; Blood coagulation; Blood flow; Brain; Cardiac; Clinical; Clinical Research; Coagulation Process; Complex; Computer Models; Consumption; Contrast Media; Data; Data Set; Demographic Factors; Engineering; Equilibrium; Goals; Heart; Heart Atrium; Hemorrhage; Hypertension; Image; Image Analysis; Injections; Kinetics; Lead; Left; Liquid substance; Measures; Methods; Modeling; Motion; Outcome; Patient risk; Patients; Pharmaceutical Preparations; Physics; Physiological; Pilot Projects; Population; Protocols documentation; Radiation Dose Unit; Recording of previous events; Resolution; Rheology; Risk; Stratification; Stroke; Techniques; Thrombosis; Thrombus; Time; Training; Travel; Uncertainty; United States; Variant; Work; X-Ray Computed Tomography; analysis pipeline; auricular appendage; base; blood rheology; clinical translation; cohort; comorbidity; comparison group; computer framework; cone-beam computed tomography; contrast enhanced; cost; disability; embolic stroke; heart imaging; hemodynamics; image processing; improved; improved outcome; innovation; insight; mortality; neglect; novel; patient stratification; predictive modeling; prevent; risk stratification; sex; simulation; spatiotemporal; statistics; stroke patient; stroke risk; thrombogenesis; tool

Atrial fibrillation (AF) is the most common arrhythmia, affecting approximately 35 million people worldwide. During AF, the heart's two upper chambers (the atria) beat weakly and irregularly creating regions of slow flow (blood stasis) where clots may form. Clots preferentially form within the left atrial appendage (LAA) and can travel to the brain resulting in stroke. The risk of embolic strokes in AF patients is reduced with anticoagulation medications but, due to the associated increased bleeding risk, these medications are not recommended for all AF patients. Determining if anticoagulation is beneficial requires assessing if patients' risk of stroke outweighs the bleeding risk. However, current methods to risk-stratify AF patients for stroke are not personalized and, for a large number of patients, leave uncertainty as to whether anticoagulation is beneficial. The main objective of this project is to develop novel CT imaging analyses to quantify the personalized risk of LAA thrombosis in AF patients. Our scientific premise is that blood stasis is a key ingredient of thrombosis because it permits thrombogenic reactive species to interact and initiate clot formation. Our preliminary data suggest the spatio- temporal dynamics of blood flow and wall motion in the atrium and LAA strongly correlate with thrombus formation. Our approach consists of three specific aims. In Aim 1 we will develop and validate a computational framework to quantify left atrial blood stasis by 4D CT imaging of atrial kinetics combined with computational fluid dynamics (CFD). We will develop image processing algorithms to quantify left atrial kinetics based on time- resolved CT scans, including the spatio-temporal dynamics of contrast opacification, imaged wall motion, and the non-Newtonian rheology of blood flow in the LAA. In Aim 2 we will establish the relationship between 4D atrial kinetics by multi-heartbeat contrast CT and blood stasis using CFD, in order to facilitate the clinical translation of stasis mapping by CT alone. We will also perform the first rigorous analysis of how uncertainty caused by imaging resolution, modeling assumptions, and physiological variability propagates into predictions of LAA blood stasis. In Aim 3 we will perform an outcome-based clinical pilot study to develop a personalized image-based thrombosis risk score. We will acquire CT data in patients with a history of LAA thrombus or AF- associated stroke and a matched comparison group of AF patients with no history of thrombosis. We will use this unique data set to develop a patient-specific image-based risk score incorporating CT contrast opacification analyses with functional and geometric parameters. Our team includes a cardiologist with a physics background specializing in imaging, an engineer with expertise in CFD analysis, and an engineer with expertise in quantitative analyses of cardiac imaging. Our translational goal is to provide clinicians with a novel image-based tool for personalized risk stratification of patients with atrial fibrillation to guide anticoagulation decisions and improve outcomes.

心房颤动 (AF) 是最常见的心律失常，影响全球约 3500 万人。 房颤期间，心脏的两个上腔室（心房）搏动微弱且不规则，形成慢流区域 （瘀血）可能形成凝块。血栓优先在左心耳 (LAA) 内形成，并且可以 旅行到大脑导致中风。抗凝治疗可降低 AF 患者发生栓塞性中风的风险 药物治疗，但由于相关的出血风险增加，不建议所有人使用这些药物 房颤患者。确定抗凝治疗是否有益需要评估患者中风的风险是否大于 出血风险。然而，目前对 AF 患者中风进行风险分层的方法并不是个性化的，并且对于 大量患者对抗凝是否有益留下了不确定性。主要目标 该项目旨在开发新型 CT 成像分析来量化左心耳血栓形成的个性化风险 房颤患者。我们的科学前提是，血瘀是血栓形成的关键因素，因为它允许 血栓形成反应物质相互作用并引发凝块形成。我们的初步数据表明空间 心房和左心耳血流和室壁运动的时间动态与血栓密切相关 形成。我们的方法包括三个具体目标。在目标 1 中，我们将开发并验证计算 通过心房动力学 4D CT 成像结合计算来量化左心房血瘀的框架 流体动力学（CFD）。我们将开发图像处理算法来量化基于时间的左心房动力学 分辨率 CT 扫描，包括对比混浊的时空动态、成像的室壁运动和 左心耳血流的非牛顿流变学。在目标 2 中，我们将建立 4D 之间的关系 通过多心跳对比CT和血瘀证CFD进行心房动力学分析，以利于临床 仅通过 CT 翻译停滞图。我们还将对不确定性如何进行首次严格分析 由成像分辨率、建模假设和生理变异性引起的影响会传播到预测中 LAA血瘀。在目标 3 中，我们将进行一项基于结果的临床试点研究，以开发个性化的 基于图像的血栓形成风险评分。我们将采集有左心耳血栓或房颤病史的患者的 CT 数据 相关中风患者和无血栓病史的 AF 患者的匹配对照组。我们将使用 该独特的数据集可开发基于患者特定图像的风险评分，并结合 CT 造影剂混浊 使用功能和几何参数进行分析。我们的团队包括一位具有物理学背景的心脏病专家 一名擅长成像的工程师，一名擅长CFD分析的工程师，一名擅长定量的工程师 心脏成像分析。我们的转化目标是为临床医生提供一种新颖的基于图像的工具 对房颤患者进行个性化风险分层以指导抗凝决策 并改善结果。