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 ?brillation (AF) is the most prevalent sustained cardiac arrhythmia, leading to morbidity and mortality in 1-2% of the population and contributing signi?cantly 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 ?brosis, which confounds ablation strategies. There is an urgent need for new approaches that can result in swift and accurate iden- ti?cation of optimal ablation targets for PsAF and thereby improve the ef?cacy 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.
Catheter-based ablation, which has become a safe and effective therapy for other types of cardiac arrhythmias, is associated with low levels of success in the management of atrial fibrillation in patients with fibrotic remodeling. There is an urgent need for new methodologies that can result in accurate identification of critical sites for ablation and thereby improve the efficacy of the therapy. 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 persistent atrial fibrillation.
