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Personalized arrhythmia simulations have the potential to improve diagnosis and guide therapy. Here, we introduce a computational framework for personalized simulations of ventricular electrophysiology (EP) incorporating scar. This framework was utilized in a patient who had ventricular fibrillation (VF).From delayed enhancement magnetic resonance imaging (MRI) an anatomical model was constructed. Regions of scar and border zone were segmented by thresholding. EP was then simulated using CARPentry. The Ten Tusscher ventricular EP model was adapted locally to reflect healthy, border zone or scar tissue. In this patient, three distinct premature ventricular complexes (PVCs) were identified using electrocardiographic imaging (ECGI), one of which induced VF. The clinically observed PVCs were replicated in the virtual model to study arrhythmia development, but VF could not be reproduced with a simple stimulation protocol that disregarded patient-specific conditions present at the time of actual VF induction. This could indicate that not only the virtual heart model, but also the stress test may need to be personalized for accurate arrhythmia simulations.In conclusion, this computational framework enables EP simulations based on MRI-detected scar, and allows to study the amount of personalization required.

Personalized Ventricular Arrhythmia Simulation Framework to Study Vulnerable Trigger Locations on Top of Scar Substrate