Alcaine, AlejandroJáuregui, BeatrizSoto-Iglesias, DavidAcosta, Juan CarlosPenela, DiegoFernández-Armenta, JuanLinhart, MarkusAndreu Martínez, DavidMont, LluísLaguna, PabloCamara, OscarMartínez, Juan PabloBerruezo Sánchez, Antonio2020-07-132020-07-132020Alcaine 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: 10.1155/2020/43868411540-8183http://hdl.handle.net/10230/45105Background. 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.application/pdfeng© 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.ArrítmiaFibril·lació ventricularAlgorismesinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1155/2020/4386841info:eu-repo/semantics/openAccess