Scientific Reports (Jul 2023)

Enhanced optimization-based method for the generation of patient-specific models of Purkinje networks

  • Lucas Arantes Berg,
  • Bernardo Martins Rocha,
  • Rafael Sachetto Oliveira,
  • Rafael Sebastian,
  • Blanca Rodriguez,
  • Rafael Alves Bonfim de Queiroz,
  • Elizabeth M. Cherry,
  • Rodrigo Weber dos Santos

DOI
https://doi.org/10.1038/s41598-023-38653-1
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 18

Abstract

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Abstract 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.