Tailoring Process for the Regional Personalization of Atrial Fibrillation with a Novel Cardiac Model

The personalization of mathematical models has the goal of helping in the identification of optimal antiarrhythmic therapies for each patient. Nevertheless, their need for high computational resources and long running times move them far away from real-time clinical practice. In this study, we present a novel cellular mathematical model which includes the main electrophysiological characteristics that allow personalization whereas requires a low number of resources and time. This model incorporates some important dynamics seen in real myocardium tissue. Moreover, we present a tailoring process that allows the regional model personalization. The simplified-mathematical model and the tailoring procedure have been compared against the simulations obtained from an already validated detailed-mathematical model. The simplified-mathematical model demonstrated its accuracy both during regular rhythms and during Atrial Fibrillation (i.e., similar regional locations of drivers). This novel simplified-mathematical model and its personalization framework open the door to producing fast and personalized simulations from patients' data. Those individualized models will allow the in-silico evaluation of ablation therapies to improve the current clinical treatment for cardiac arrhythmias.