The novel Constructive Optimization method generated patient-specific Purkinje networks that accurately reproduced local activation times with an RMSE below 2 ms for the patient-specific mesh.
The novel Constructive Optimization method successfully generates patient-specific Purkinje networks that accurately reproduce geometrical features and local activation times, providing a valuable tool for cardiac electrophysiology simulations.
Cardiac Purkinje networks are a fundamental part of the conduction system and are known to initiate a variety of cardiac arrhythmias. However, patient-specific modeling of Purkinje networks remains a challenge due to their high morphological complexity. This work presents a novel method based on optimization principles for the generation of Purkinje networks that combines geometric and activation accuracy in branch size, bifurcation angles, and Purkinje-ventricular-junction activation times. Three biventricular meshes with increasing levels of complexity are used to evaluate the performance of our approach. Purkinje-tissue coupled monodomain simulations are executed to evaluate the generated networks in a realistic scenario using the most recent Purkinje/ventricular human cellular models and physiological values for the Purkinje-ventricular-junction characteristic delay. The results demonstrate that the new method can generate patient-specific Purkinje networks with controlled morphological metrics and specified local activation times at the Purkinje-ventricular junctions.
Berg et al. (Fri,) conducted a other in Cardiac electrophysiology. Constructive Optimization (CO) method vs. Reference Purkinje networks was evaluated on Root mean square error (RMSE) of local activation times (LAT). The novel Constructive Optimization method generated patient-specific Purkinje networks that accurately reproduced local activation times with an RMSE below 2 ms for the patient-specific mesh.