Prediction of arrhythmogenesis in non-ischemic cardiac resynchronization therapy patients

We aim to develop a patient-specific computational model to predict the risk of Ventricular Tachycardia (VT) in patients with a Biventricular Cardiac Resynchronization Therapy (BiV-CRT) device. Patients are indeed at risk of developing arrhythmias due to BiV-CRT pacing, a known potential complication that requires preventive evaluation. We consider three non-ischemic fibrotic patients. Patient-specific left ventricle geometries and fibrosis are extracted from Cine-MRI and LGE-MRI. The electrophysiology model, based on the monodomain equation and the Ten Tusscher-Panfilov (TTP06) ionic model, is personalized using pre-operative Electro-Anatomical Mapping System data. The TTP06 parameters are adapted to reflect the altered electrical properties of the fibrotic tissue. To test inducibility, we use an $S1-S2$ stimulation protocol: $S1$ simulates the clinical BiV-CRT pacing with a patient-specific VV-delay, followed by an $S2$ ectopic impulse. This procedure is repeated for 10 ectopic sites. The arrhythmogenic risk is quantified by the number of ectopic sites that generate a reentry loop. The model's prediction of VT risk in our simulations matches the clinical outcome for all three patients, recognizing the two with spontaneous VT episodes and the one non-arrhythmic patient. Arrhythmic patients show a higher number of ectopic sites from which a reentry loop is generated compared to the non-arrhythmic patient. This study provides a preliminary attempt toward the use of computational tools to assess the vulnerability of the arrhythmic substrate during BiV-CRT pacing in non-ischemic patients. In the future, such tools could serve as a noninvasive diagnostic metric to inform clinicians about possible therapies to be associated with BiV-CRT.