Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias

Background. Voltage mapping allows identifying the arrhythmogenic substrate during scar-related ventricular arrhythmia (VA) ablation procedures. Slow conducting channels (SCCs), defined by the presence of electrogram (EGM) signals with delayed components (EGM-DC), are responsible for sustaining VAs...

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Autores: Alcaine, Alejandro, Jáuregui, Beatriz, Soto-Iglesias, David, Acosta, Juan Carlos, Penela, Diego, Fernández-Armenta, Juan, Linhart, Markus, Andreu Martínez, David, Mont, Lluís, Laguna, Pablo, Camara, Oscar, Martínez, Juan Pablo, Berruezo Sánchez, Antonio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/45105
Acceso en línea:http://hdl.handle.net/10230/45105
http://dx.doi.org/10.1155/2020/4386841
Access Level:acceso abierto
Palabra clave:Arrítmia
Fibril·lació ventricular
Algorismes
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oai_identifier_str oai:recercat.cat:10230/45105
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
title Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
spellingShingle Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
Alcaine, Alejandro
Arrítmia
Fibril·lació ventricular
Algorismes
title_short Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
title_full Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
title_fullStr Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
title_full_unstemmed Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
title_sort Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
dc.creator.none.fl_str_mv Alcaine, Alejandro
Jáuregui, Beatriz
Soto-Iglesias, David
Acosta, Juan Carlos
Penela, Diego
Fernández-Armenta, Juan
Linhart, Markus
Andreu Martínez, David
Mont, Lluís
Laguna, Pablo
Camara, Oscar
Martínez, Juan Pablo
Berruezo Sánchez, Antonio
author Alcaine, Alejandro
author_facet Alcaine, Alejandro
Jáuregui, Beatriz
Soto-Iglesias, David
Acosta, Juan Carlos
Penela, Diego
Fernández-Armenta, Juan
Linhart, Markus
Andreu Martínez, David
Mont, Lluís
Laguna, Pablo
Camara, Oscar
Martínez, Juan Pablo
Berruezo Sánchez, Antonio
author_role author
author2 Jáuregui, Beatriz
Soto-Iglesias, David
Acosta, Juan Carlos
Penela, Diego
Fernández-Armenta, Juan
Linhart, Markus
Andreu Martínez, David
Mont, Lluís
Laguna, Pablo
Camara, Oscar
Martínez, Juan Pablo
Berruezo Sánchez, Antonio
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Arrítmia
Fibril·lació ventricular
Algorismes
topic Arrítmia
Fibril·lació ventricular
Algorismes
description Background. Voltage mapping allows identifying the arrhythmogenic substrate during scar-related ventricular arrhythmia (VA) ablation procedures. Slow conducting channels (SCCs), defined by the presence of electrogram (EGM) signals with delayed components (EGM-DC), are responsible for sustaining VAs and constitute potential ablation targets. However, voltage mapping, as it is currently performed, is time-consuming, requiring a manual analysis of all EGMs to detect SCCs, and its accuracy is limited by electric far-field. We sought to evaluate an algorithm that automatically identifies EGM-DC, classifies mapping points, and creates new voltage maps, named “Slow Conducting Channel Maps” (SCC-Maps). Methods. Retrospective analysis of electroanatomic maps (EAM) from 20 patients (10 ischemic, 10 with arrhythmogenic right ventricular dysplasia/cardiomyopathy) was performed. EAM voltage maps were acquired during sinus rhythm and used for ablation. Preprocedural contrast-enhanced cardiac magnetic resonance (Ce-CMR) imaging was available for the ischemic population. Three mapping modalities were analysed: (i) EAM voltage maps using standard (EAM standard) or manual (EAM screening) thresholds for defining core and border zones; (ii) SCC-Maps derived from the use of the novel SCC-Mapping algorithm that automatically identify EGM-DCs measuring the voltage of the local component; and (iii) Ce-CMR maps (when available). The ability of each mapping modality in identifying SCCs and their agreement was evaluated. Results. SCC-Maps and EAM screening identified a greater number of SCC entrances than EAM standard (3.45 ± 1.61 and 2.95 ± 2.31, resp., vs. 1.05 ± 1.10; ). SCC-Maps and EAM screening highly correlate with Ce-CMR maps in the ischemic population when compared to EAM standard (Lin’s correlation = 0.628 and 0.679, resp., vs. 0.212, ). Conclusion. The SCC-Mapping algorithm allows an operator-independent analysis of EGM signals showing better identification of the arrhythmogenic substrate characteristics when compared to standard voltage EAM.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/45105
http://dx.doi.org/10.1155/2020/4386841
url http://hdl.handle.net/10230/45105
http://dx.doi.org/10.1155/2020/4386841
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Journal of Interventional Cardiology. 2020 May 29;2020;4386841
info:eu-repo/grantAgreement/ES/1PE/DPI2016-75458-R
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmiasAlcaine, AlejandroJáuregui, BeatrizSoto-Iglesias, DavidAcosta, Juan CarlosPenela, DiegoFernández-Armenta, JuanLinhart, MarkusAndreu Martínez, DavidMont, LluísLaguna, PabloCamara, OscarMartínez, Juan PabloBerruezo Sánchez, AntonioArrítmiaFibril·lació ventricularAlgorismesBackground. Voltage mapping allows identifying the arrhythmogenic substrate during scar-related ventricular arrhythmia (VA) ablation procedures. Slow conducting channels (SCCs), defined by the presence of electrogram (EGM) signals with delayed components (EGM-DC), are responsible for sustaining VAs and constitute potential ablation targets. However, voltage mapping, as it is currently performed, is time-consuming, requiring a manual analysis of all EGMs to detect SCCs, and its accuracy is limited by electric far-field. We sought to evaluate an algorithm that automatically identifies EGM-DC, classifies mapping points, and creates new voltage maps, named “Slow Conducting Channel Maps” (SCC-Maps). Methods. Retrospective analysis of electroanatomic maps (EAM) from 20 patients (10 ischemic, 10 with arrhythmogenic right ventricular dysplasia/cardiomyopathy) was performed. EAM voltage maps were acquired during sinus rhythm and used for ablation. Preprocedural contrast-enhanced cardiac magnetic resonance (Ce-CMR) imaging was available for the ischemic population. Three mapping modalities were analysed: (i) EAM voltage maps using standard (EAM standard) or manual (EAM screening) thresholds for defining core and border zones; (ii) SCC-Maps derived from the use of the novel SCC-Mapping algorithm that automatically identify EGM-DCs measuring the voltage of the local component; and (iii) Ce-CMR maps (when available). The ability of each mapping modality in identifying SCCs and their agreement was evaluated. Results. SCC-Maps and EAM screening identified a greater number of SCC entrances than EAM standard (3.45 ± 1.61 and 2.95 ± 2.31, resp., vs. 1.05 ± 1.10; ). SCC-Maps and EAM screening highly correlate with Ce-CMR maps in the ischemic population when compared to EAM standard (Lin’s correlation = 0.628 and 0.679, resp., vs. 0.212, ). Conclusion. The SCC-Mapping algorithm allows an operator-independent analysis of EGM signals showing better identification of the arrhythmogenic substrate characteristics when compared to standard voltage EAM.This study was supported by personal grants to A. Alcaine (Refs. BES-2011-046644 and EEBB-I-15-09466); by projects PID2019-104881RB-I00 from Ministerio de Ciencia e Innovación (Spain) and DPI2016-75458-R from Ministerio de Economía y Competitividad (Spain); and by Gobierno de Aragón (Grupo Referencia BSICoS ref.: T39_20R) cofounded by FEDER 2014–2020. This work was also supported in part by the project PI14/00759, integrated in the Plan Nacional de I+D+i and cofounded by the Instituto de Salud Carlos III (ISCIII)-Subdirección General de Evaluación and European Regional Development Fund (European Union). The computation was performed by the ICTS NANBIOSIS, more specifically by the High Performance Computing Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN) at the University of Zaragoza. The CIBER-BBN is an initiative of Instituto de Salud Carlos III.Wiley202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/45105http://dx.doi.org/10.1155/2020/4386841reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésJournal of Interventional Cardiology. 2020 May 29;2020;4386841info:eu-repo/grantAgreement/ES/1PE/DPI2016-75458-R© 2020 Alejandro Alcaine et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/451052026-05-29T05:05:01Z
score 15,81155

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