Simulation Guidance of Ablation Therapy for Persistent Atrial Fibrillation

项目总结 此应用程序响应PAR-15-085：生物医学、生物学、 行为、环境和临床研究(机构间U01)，前沿挑战：预测性 改进临床工作流程、标准操作程序、特定于患者的多尺度模型 用于诊断和治疗计划的建模。 房颤(房颤)是最常见的持续性心律失常，其发病率和病死率均高于fi。 占人口的1-2%，对全球卫生保健费用的贡献很大。fi。对于房颤可以- 不能用药物治疗，推荐的治疗方法是基于导管的消融，以隔离心律失常的触发因素和 消除永久性心律失常的底物。然而，该手术的结果很差(50%成功- 持续性房颤(PSAF)患者存在广泛的心房fi波群，这令人困惑 消融策略。迫切需要新的方法，能够迅速和准确地识别- 对PSAF的最佳消融靶点进行fi阳离子处理，从而改善fi的精度并增加容差 对于治疗，以及减少术后并发症和重复消融。 该应用程序的总体目标是开发和验证一种新的个性化多尺度 确定纤维基质导管消融最佳靶点的建模策略 PSAF患者。我们建议开发和验证从房颤的MRI图像重建的心房模型。 伴有PSAF和纤维化重塑的患者。这些模型将从分子上整合力学功能。 水平到完整器官中的电生理相互作用。我们将对模拟器进行参数化和验证- 在移植的人和动物模型中进行实验测量的方法。我们将使用 经过验证的个性化建模策略，用于在回溯性患者研究中确定一组 最佳消融损伤，以最低的复发可能性终止房颤。该项目的最终结果将是 一项试验性的未来患者研究，房颤消融将直接针对模拟预测的靶点进行。 拟议研究的成功实施将为临床研究的重大范式转变铺平道路。 纤维重塑患者的房颤消融治疗可显著改善患者的 该疗法的疗效。重要的是，这个项目的完成将导致#年的重大飞跃。 计算模型在心脏病诊断和治疗中的整合。

PROJECT SUMMARY This application is in response to PAR-15-085: Predictive Multiscale Models for Biomedical, Biological, Behavioral, Environmental and Clinical Research (Interagency U01), with Cutting Edge Challenge: Predictive multiscale models to improve clinical workflow, standard operating procedures, patient-specific modeling for diagnosis and therapy planning. Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, leading to morbidity and mortality in 1-2% of the population and contributing significantly to global health care costs. For patients in whom AF can- not be treated by drugs, the recommended therapy is catheter-based ablation to isolate arrhythmia triggers and eliminate the substrate for arrhythmia perpetuation. However, outcomes of the procedure are poor ( 50% suc- cess rate) in patients with persistent AF (PsAF) due to the presence of extensive atrial fibrosis, which confounds ablation strategies. There is an urgent need for new approaches that can result in swift and accurate iden- tification of optimal ablation targets for PsAF and thereby improve the efficacy of and increase the tolerance for the therapy, as well as reduce post-procedure complications and repeated ablations. The overall objective of this application is to develop and validate a novel personalized multiscale modeling strategy for determining the optimal targets for catheter ablation of the fibrotic substrate in patients with PsAF. We propose to develop and validate atrial models reconstructed from MRI images of pa- tients with PsAF and fibrotic remodeling. The models will integrate mechanistically functions from the molecular level to the electrophysiological interactions in the intact organ. We will parametrize and validate the simula- tion approach with experimental measurements in explanted human atria and animal models. We will use the validated personalized modeling strategy to determine, in retrospective patient studies, what constitutes a set of optimal ablation lesions that terminate AF with the least likelihood of recurrence. The project will culminate with a pilot prospective patient study, where AF ablation will be executed directly at the simulation-predicted targets. Successful execution of the proposed studies will pave the way for a major paradigm shift in the clinical procedure of AF ablation in patients with fibrotic remodeling, resulting in a dramatic improvement in the efficacy of the therapy. Importantly, completion of this project will result in a major leap forward in the integration of computational modeling in the diagnosis and treatment of cardiac disease.