Key result
Patient-specific modeling shows localized reentries anchor in slow conduction areas during persistent versus paroxysmal AF.
Why the study?
The mechanisms behind atrial fibrillation remained long debated, and reliable numerical prediction of its induction and sustainment was needed.
A novel computational model integrating patient-specific conduction velocities can simulate AF mechanisms, showing that substrate characteristics dictate the stability and anchoring of reentrant drivers.
Patient-specific models may inform persistent AF ablation; leaves open whether targeting anchored drivers improves outcomes.
In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model. Our new model parametrization is then adopted to predict the formation and self-sustainment of localized reentries characterizing atrial fibrillation, by numerically simulating the onset of ectopic beats from the pulmonary veins. We investigate the paroxysmal and the persistent form of AF starting from electro-anatomical maps of two patients. The model's response to stimulation shows how substrate characteristics play a key role in inducing and sustaining these arrhythmias. Localized reentries are less frequent and less stable in case of paroxysmal AF, while they tend to anchor themselves in areas affected by severe slow conduction in case of persistent AF.
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Pagani et al. (2021) studied Atrial fibrillation (n=2). Computational modeling based on conduction velocities was evaluated on Formation and self-sustainment of localized reentries. A novel computational model using patient-specific conduction velocities showed localized reentries are less stable in paroxysmal AF but anchor in slow conduction areas in persistent AF.
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