120946 20240319081010.0 doi 10.1007/s11517-022-02648-3 sideral 131379 ART-2022-131379 eng Riccio, Jennifer Universidad de Zaragoza (orcid)0000-0002-6264-4229 Atrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays 2022 Access copy available to the general public Unrestricted Atrial fbrosis plays a key role in the initiation and progression of atrial fbrillation (AF). Atrial fbrosis is typically identifed by a peak-to-peak amplitude of bipolar electrograms (b-EGMs) lower than 0.5 mV, which may be considered as ablation targets. Nevertheless, this approach disregards signal spatiotemporal information and b-EGM sensitivity to catheter orientation. To overcome these limitations, we propose the dominant-to-remaining eigenvalue dominance ratio (EIGDR) of unipolar electrograms (u-EGMs) within neighbor electrode cliques as a waveform dispersion measure, hypothesizing that it is correlated with the presence of fbrosis. A simulated 2D tissue with a fbrosis patch was used for validation. We computed EIGDR maps from both original and time-aligned u-EGMs, denoted as R and RA, respectively, also mapping the gain in eigenvalue concentration obtained by the alignment, ΔRA. The performance of each map in detecting fbrosis was evaluated in scenarios including noise and variable electrode-tissue distance. Best results were achieved by RA, reaching 94% detection accuracy, versus the 86% of b-EGMs voltage maps. The proposed strategy was also tested in real u-EGMs from fbrotic and non-fbrotic areas over 3D electroanatomical maps, supporting the ability of the EIGDRs as fbrosis markers, encouraging further studies to confrm their translation to clinical settings. info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA info:eu-repo/grantAgreement/EC/H2020/860974/EU/Personalized Therapies for Atrial Fibrillation. A Translational Approach/PersonalizeAF This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 860974-PersonalizeAF info:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00 info:eu-repo/grantAgreement/ES/MICINN/PID2019-105674RB-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.2 2022 MATHEMATICAL & COMPUTATIONAL BIOLOGY 17 / 55 = 0.309 2022 Q2 T1 MEDICAL INFORMATICS 18 / 31 = 0.581 2022 Q3 T2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 60 / 110 = 0.545 2022 Q3 T2 ENGINEERING, BIOMEDICAL 56 / 96 = 0.583 2022 Q3 T2 0.653 2022 Computer Science Applications 2022 Q2 Biomedical Engineering 2022 Q2 6.1 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Alcaine, Alejandro (orcid)0000-0002-0166-2837 Rocher, Sara Martinez-Mateu, Laura Saiz, Javier Invers-Rubio, Eric Guillem, Maria S. Martínez, Juan Pablo Universidad de Zaragoza (orcid)0000-0002-7503-3339 Laguna, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 60, 11 (2022), 3091-3112 Med. biol. eng. comput. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 0140-0118 4097011 http://zaguan.unizar.es/record/120946/files/texto_completo.pdf Versión publicada 2348548 http://zaguan.unizar.es/record/120946/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:120946 articulos driver 2024-03-18-15:02:34 ARTICLE