95337 20210902121746.0 doi 10.1155/2020/4386841 sideral 118702 ART-2020-118702 eng Alcaine, Alejandro (orcid)0000-0002-0166-2837 Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias 2020 Access copy available to the general public Unrestricted 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; p<0.01). 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, p<0.01). 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. info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group info:eu-repo/grantAgreement/ES/ISCIII-FEDER/PI14-00759 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.279 2020 CARDIAC & CARDIOVASCULAR SYSTEMS 94 / 141 = 0.667 2020 Q3 T3 0.764 2020 Radiology, Nuclear Medicine and Imaging 2020 Q2 Cardiology and Cardiovascular Medicine 2020 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Jáuregui, Beatriz Soto-Iglesias, David Acosta, Juan Penela, Diego Fernández-Armenta, Juan Linhart, Markus Andreu, David Mont, Lluis Laguna, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 Cámara, Óscar Martínez, Juan Pablo Universidad de Zaragoza (orcid)0000-0002-7503-3339 Berruezo, Antonio 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 2020 (2020), 4386841 [13 pp.] J. interv. cardiol. Journal of Interventional Cardiology 0896-4327 4338218 http://zaguan.unizar.es/record/95337/files/texto_completo.pdf Versión publicada 39305 http://zaguan.unizar.es/record/95337/files/texto_completo.jpg?subformat=icon icon Versión publicada https://onlinelibrary.wiley.com/loi/15408183 Texto completo de la revista oai:zaguan.unizar.es:95337 articulos driver 2021-09-02-09:46:30 ARTICLE