Meshless electrophysiological modeling of cardiac resynchronization therapy: benchmark analysis with finite-element methods in experimental data

Albors Lucas, Carlos; Lluch Álvarez, Èric; Gomez, Juan Francisco; Cedilnik, Nicolas; Mountris, Konstantinos A.; Mansi, Tommaso; Khamzin, Svyatoslav; Dokuchaev, Arsenii; Solovyova, Olga; Pueyo, Esther; Sermesant, Maxime; Sebastian, Rafael; Morales, Hernán G.; Camara, Oscar

Meshless electrophysiological modeling of cardiac resynchronization therapy: benchmark analysis with finite-element methods in experimental data

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dc.contributor.author Albors Lucas, Carlos
dc.contributor.author Lluch Álvarez, Èric
dc.contributor.author Gomez, Juan Francisco
dc.contributor.author Cedilnik, Nicolas
dc.contributor.author Mountris, Konstantinos A.
dc.contributor.author Mansi, Tommaso
dc.contributor.author Khamzin, Svyatoslav
dc.contributor.author Dokuchaev, Arsenii
dc.contributor.author Solovyova, Olga
dc.contributor.author Pueyo, Esther
dc.contributor.author Sermesant, Maxime
dc.contributor.author Sebastian, Rafael
dc.contributor.author Morales, Hernán G.
dc.contributor.author Camara, Oscar
dc.date.accessioned 2023-03-06T07:33:40Z
dc.date.available 2023-03-06T07:33:40Z
dc.date.issued 2022
dc.description.abstract 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).
dc.description.sponsorship This work was supported in part by the Spanish Ministry of Science and Innovation (TIN2011-28067, REDINSCOR RD06/003/008, PID2019-105674RB-I00), the Spanish Industrial and Technological Development Center (cvREMOD-CEN-20091044), the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502), the Government of Aragón (Spain) (LMP94_21), the Directorate General of Science Policy of the Generalitat Valenciana (Spain) (PROMETEU 2016/088), the Seventh Framework Programme (FP7/2007-2013) for research, technological and demonstration under grant agreement VP2HF (no. 611823), by the RSF grant no. 19-14-00134, and by European Regional Development Fund (ERDF) DPI2016-75799-R (AEI/ERDF, EU).
dc.format.mimetype application/pdf
dc.identifier.citation Albors C, Lluch È, Gomez JF, Cedilnik N, Mountris KA, Mansi T, Khamzin S, Dokuchaev A, Solovyova O, Pueyo E, Sermesant M, Sebastian R, Morales HG, Camara O. Meshless electrophysiological modeling of cardiac resynchronization therapy: benchmark analysis with finite-element methods in experimental data. Appl Sci. 2022;12(13):6438. DOI: 10.3390/app12136438
dc.identifier.doi http://dx.doi.org/10.3390/app12136438
dc.identifier.issn 2076-3417
dc.identifier.uri http://hdl.handle.net/10230/56057
dc.language.iso eng
dc.publisher MDPI
dc.relation.ispartof Applied Sciences. 2022;12(13):6438.
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/611823
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/TIN2011-28067
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105674RB-I00
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/MDM-2015-0502
dc.rights © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject.keyword electrophysiology
dc.subject.keyword parameter optimisation
dc.subject.keyword smoothed particle hydrodynamics
dc.subject.keyword meshless model
dc.subject.keyword cardiac resynchronization therapy
dc.subject.keyword CRT-EPiggy19 challenge
dc.title Meshless electrophysiological modeling of cardiac resynchronization therapy: benchmark analysis with finite-element methods in experimental data
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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