Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Applied Sciences Année : 2022

Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data

Carlos Albors
Èric Lluch
  • Fonction : Auteur
Juan Francisco Gomez
Konstantinos Mountris
Tommaso Mansi
  • Fonction : Auteur
Svyatoslav Khamzin
  • Fonction : Auteur
Arsenii Dokuchaev
  • Fonction : Auteur
Olga Solovyova
  • Fonction : Auteur
Esther Pueyo
Maxime Sermesant
Rafael Sebastian
Hernán Morales
Oscar Camara

Résumé

Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables benchmarking analysis of different cardiac computational modeling solutions with quantitative metrics. We present a benchmark analysis of a meshless-based method with finite-element methods for the prediction of cardiac electrical patterns in CRT, based on a subset of the CRT-EPiggy19 dataset. A data assimilation strategy was designed to personalize the most relevant parameters of the electrophysiological simulations and identify the optimal CRT lead configuration. The simulation results obtained with the meshless model were equivalent to FEM, with the most relevant aspect for accurate CRT predictions being the parameter personalization strategy (e.g., regional conduction velocity distribution, including the Purkinje system and CRT lead distribution).

Dates et versions

hal-03863600 , version 1 (21-11-2022)

Identifiants

Citer

Carlos Albors, Èric Lluch, Juan Francisco Gomez, Nicolas Cedilnik, Konstantinos Mountris, et al.. Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data. Applied Sciences, 2022, 12 (13), pp.6438. ⟨10.3390/app12136438⟩. ⟨hal-03863600⟩
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