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Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia

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Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia

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dc.contributor.author Lopez-Perez, Alejandro es_ES
dc.contributor.author Sebastian, Rafael es_ES
dc.contributor.author Izquierdo, M. es_ES
dc.contributor.author Ruiz, Ricardo es_ES
dc.contributor.author Bishop, Martin es_ES
dc.contributor.author Ferrero De Loma-Osorio, José María es_ES
dc.date.accessioned 2024-01-31T19:02:57Z
dc.date.available 2024-01-31T19:02:57Z
dc.date.issued 2019-05-15 es_ES
dc.identifier.issn 1664-042X es_ES
dc.identifier.uri http://hdl.handle.net/10251/202276
dc.description.abstract [EN] In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this strategy show relatively low success rates; up to 50% of patients experience recurrent VT after the procedure. In the last decade, intensive research in the field of computational cardiac electrophysiology (EP) has demonstrated the ability of three-dimensional (3D) cardiac computational models to perform in-silico EP studies. However, the personalization and modeling of certain key components remain challenging, particularly in the case of the infarct border zone (BZ). In this study, we used a clinical dataset from a patient with a history of infarct-related VT to build an image-based 3D ventricular model aimed at computational simulation of cardiac EP, including detailed patient-specific cardiac anatomy and infarct scar geometry. We modeled the BZ in eight different ways by combining the presence or absence of electrical remodeling with four different levels of image-based patchy fibrosis (0, 10, 20, and 30%). A 3D torso model was also constructed to compute the ECG. Patient-specific sinus activation patterns were simulated and validated against the patient's ECG. Subsequently, the pacing protocol used to induce reentrant VTs in the EP laboratory was reproduced in-silico. The clinical VT was induced with different versions of the model and from different pacing points, thus identifying the slow conducting channel responsible for such VT. Finally, the real patient's ECG recorded during VT episodes was used to validate our simulation results and to assess different strategies to model the BZ. Our study showed that reduced conduction velocities and heterogeneity in action potential duration in the BZ are the main factors in promoting reentrant activity. Either electrical remodeling or fibrosis in a degree of at least 30% in the BZ were required to initiate VT. Moreover, this proof-of-concept study confirms the feasibility of developing 3D computational models for cardiac EP able to reproduce cardiac activation in sinus rhythm and during VT, using exclusively non-invasive clinical data. es_ES
dc.description.sponsorship This work was partially supported by the Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016 from the Ministerio de Economia, Industria y Competitividad of Spain (grant number DPI2016-75799-R) and AEI/FEDER, UE, and also by the Programa Estatal de Investigacion, Desarrollo e Innovacion Orientado a los Retos de la Sociedad from the Ministerio de Economia y Competitividad of Spain, and the European Commission (European Regional Development Funds-ERDF-FEDER) (award number TIN2014-59932-JIN). During this work, AL-P was financially supported by the Ministerio de Economia, Industria y Competitividad of Spain through the program Ayudas para contratos predoctorales para la formacion de doctores (grant number BES-2013-064089). es_ES
dc.language Inglés es_ES
dc.publisher Frontiers Media SA es_ES
dc.relation.ispartof Frontiers in Physiology es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Myocardial infarction (MI) es_ES
dc.subject Ventricular tachycardia (VT) es_ES
dc.subject Border zone (BZ) es_ES
dc.subject Electrical remodeling (ER) es_ES
dc.subject Fibrosis es_ES
dc.subject Slow conducting channel (SCC) es_ES
dc.subject Computational simulation es_ES
dc.subject Radiofrequency ablation (RFA) es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3389/fphys.2019.00580 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BES-2013-064089/ES/BES-2013-064089/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2014-59932-JIN/ES/CARACTERIZACION Y DIAGNOSTICO NO INVASIVO DE ARRITMIAS CARDIACAS MEDIANTE MODELADO COMPUTACIONAL 3D ANATOMO-FUNCIONAL DEL CORAZON Y TORSO HUMANO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//DPI2016-75799-R//TECNOLOGIAS COMPUTACIONALES PARA LA OPTIMIZACION DE TERAPIAS PERSONALIZADAS DE PATOLOGIAS AURICULARES Y VENTRICULARES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Lopez-Perez, A.; Sebastian, R.; Izquierdo, M.; Ruiz, R.; Bishop, M.; Ferrero De Loma-Osorio, JM. (2019). Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia. Frontiers in Physiology. 10:1-26. https://doi.org/10.3389/fphys.2019.00580 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3389/fphys.2019.00580 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 26 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 10 es_ES
dc.identifier.pmid 31156460 es_ES
dc.identifier.pmcid PMC6531915 es_ES
dc.relation.pasarela S\507965 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.subject.ods 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades es_ES
dc.subject.ods 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación es_ES


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