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Enhanced optimization-based method for the generation of patient-specific models of Purkinje networks.
Berg, Lucas Arantes; Rocha, Bernardo Martins; Oliveira, Rafael Sachetto; Sebastian, Rafael; Rodriguez, Blanca; de Queiroz, Rafael Alves Bonfim; Cherry, Elizabeth M; Dos Santos, Rodrigo Weber.
Affiliation
  • Berg LA; Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Brazil. berg@ice.ufjf.br.
  • Rocha BM; Department of Computer Science, University of Oxford, Oxford, UK. berg@ice.ufjf.br.
  • Oliveira RS; Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
  • Sebastian R; Department of Computer Science, Federal University of São João del-Rei, São João del-Rei, Brazil.
  • Rodriguez B; Department of Computer Science, Universitat de Valencia, Valencia, Spain.
  • de Queiroz RAB; Department of Computer Science, University of Oxford, Oxford, UK.
  • Cherry EM; Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
  • Dos Santos RW; Department of Computer Science, Federal University of Ouro Preto, Ouro Preto, Brazil.
Sci Rep ; 13(1): 11788, 2023 07 21.
Article in En | MEDLINE | ID: mdl-37479707
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Benchmarking / Heart Type of study: Prognostic_studies Limits: Humans Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: Brasil Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Benchmarking / Heart Type of study: Prognostic_studies Limits: Humans Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: Brasil Country of publication: Reino Unido