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

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

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

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dc.contributor.author Alcaine, Alejandro
dc.contributor.author Jáuregui, Beatriz
dc.contributor.author Soto-Iglesias, David
dc.contributor.author Acosta, Juan Carlos
dc.contributor.author Penela, Diego
dc.contributor.author Fernández-Armenta, Juan
dc.contributor.author Linhart, Markus
dc.contributor.author Andreu Martínez, David
dc.contributor.author Mont, Lluís
dc.contributor.author Laguna, Pablo
dc.contributor.author Camara, Oscar
dc.contributor.author Martínez, Juan Pablo
dc.contributor.author Berruezo Sánchez, Antonio
dc.date.accessioned 2020-07-13T08:42:31Z
dc.date.available 2020-07-13T08:42:31Z
dc.date.issued 2020
dc.description.abstract 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.en
dc.description.sponsorship 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.
dc.format.mimetype application/pdf
dc.identifier.citation Alcaine A, Jáuregui B, Soto-Iglesias D, Acosta J, Penela D, Fernández-Armenta J, Linhart M, Andreu D, Mont L, Laguna P, Camara O, Martínez JP, Berruezo A. Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias. J Interv Cardiol. 2020 May 29;2020;4386841. DOI: 10.1155/2020/4386841
dc.identifier.doi http://dx.doi.org/10.1155/2020/4386841
dc.identifier.issn 1540-8183
dc.identifier.uri http://hdl.handle.net/10230/45105
dc.language.iso eng
dc.publisher Wiley
dc.relation.ispartof Journal of Interventional Cardiology. 2020 May 29;2020;4386841
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/DPI2016-75458-R
dc.rights © 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.
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.other Arrítmia
dc.subject.other Fibril·lació ventricular
dc.subject.other Algorismes
dc.title Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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