Personalized imaging and modeling strategies for arrhythmia prevention and therapy. (March 2018) - Trayanova, Natalia A.; Boyle, Patrick M.; Nikolov, Plamen P.
Abstract: The goal of this article is to review advances in computational modeling of the heart, with a focus on recent non-invasive clinical imaging- and simulation-based strategies aimed at improving the diagnosis and treatment of patients with arrhythmias and structural heart disease. Following a brief overview of the field of computational cardiology, we present recent applications of the personalized virtual-heart approach in predicting the optimal targets for infarct-related ventricular tachycardia and atrial fibrillation ablation, and in determining risk of sudden cardiac death in myocardial infarction patients. The hope is that with such models at the patient bedside, therapies could be improved, invasiveness of diagnostic procedures minimized, and health-care costs reduced. Graphical abstract: Workflow for using image-based simulations to predict optimal targets for catheter ablation of ventricular (top) and atrial (bottom) arrhythmias. Top row modified with permission from Trayanova et al.[42] . Bottom row modified with permission from Zahid et al.[52] and Zahid et al.[53] . Highlights: Atrial and ventricular models have provided mechanistic insight into arrhythmogenesis. Personalized clinical imaging-based models of the heart are being developed. Efforts are underway to bring models to the clinic for diagnosis and arrhythmia treatment planning.