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: 10687837
• 负责人: ANDREW KAHN
• 金额: $ 65.63万
• 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/10687837
• 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; Left; Liquid substance; Maps; Measures; Methods; Modeling; Motion; Outcome; Patient risk; Patients; Persons; Pharmaceutical Preparations; Physics; Physiological; Pilot Projects; Population; Protocols documentation; Radiation Dose Unit; Recording of previous events; Resolution; Rheology; Risk; Risk Reduction; Stratification; Stroke; Techniques; Thrombosis; Thrombus; Time; Travel; Uncertainty; United States; Variant; Work; X-Ray Computed Tomography; analysis pipeline; auricular appendage; blood rheology; clinical translation; cohort; comorbidity; comparison group; computer framework; cone-beam computed tomography; contrast enhanced; contrast enhanced computed tomography; 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; translational goal

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，全世界约有3500万人。 在AF期间，心脏的两个上室（心房）弱和不规则地击败了缓慢流动的区域 （血液停滞）可能形成凝块。在左心附属物（LAA）内优先形成凝块，可以 前往大脑，导致中风。通过抗凝患者降低AF患者的栓塞中风的风险 药物但是，由于相关的出血风险增加，不建议所有人使用这些药物 AF患者。确定抗凝是否有益，需要评估患者中风的风险是否超过 出血风险。但是，当前的风险分离AF患者中风患者的方法不是个性化的，并且 大量患者，关于抗凝作用是否有益留下不确定性。主要目标 该项目是开发新颖的CT成像分析，以量化LAA血栓形成的个性化风险 在AF患者中。我们的科学前提是血迹是血栓形成的关键要素，因为它允许 血栓形成活性物种相互作用并引发凝块形成。我们的初步数据表明时空 中庭血流和壁运动的时间动力学和LAA与血栓密切相关 形成。我们的方法包括三个特定目标。在AIM 1中，我们将开发和验证计算 通过4D CT成像的心房动力学与计算 流体动力学（CFD）。我们将开发图像处理算法，以量化基于时间的左心动力学 已解决的CT扫描，包括对比度无关的时空动力学，成像壁运动和 LAA中血流的非牛顿流变学。在AIM 2中，我们将建立4D之间的关系 使用CFD进行多心脏对比CT和血液暂停的心房动力学，以促进临床 单独使用CT的停滞映射的翻译。我们还将对如何不确定性进行第一次严格分析 由成像分辨率，建模假设和生理可变性引起的预测 Laa Blood Stasis。在AIM 3中，我们将进行基于结果的临床试点研究，以开发个性化 基于图像的血栓形成风险评分。我们将在具有LAA血栓或AF-患者的患者中获取CT数据 相关的中风和无血栓形成病史的AF患者的匹配比较组。我们将使用 这个独特的数据集，以开发出特定于患者的基于图像的风险评分，并结合了CT对比度的无效化 使用功能和几何参数进行分析。我们的团队包括具有物理背景的心脏病专家 专门从事成像，具有CFD分析专业知识的工程师以及具有定量专业知识的工程师 心脏成像的分析。我们的翻译目标是为临床医生提供一种新颖的基于图像的工具 用于心房颤动患者的个性化风险分层以指导抗凝决定 并改善结果。