000120946 001__ 120946
000120946 005__ 20240319081010.0
000120946 0247_ $$2doi$$a10.1007/s11517-022-02648-3
000120946 0248_ $$2sideral$$a131379
000120946 037__ $$aART-2022-131379
000120946 041__ $$aeng
000120946 100__ $$0(orcid)0000-0002-6264-4229$$aRiccio, Jennifer$$uUniversidad de Zaragoza
000120946 245__ $$aAtrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays
000120946 260__ $$c2022
000120946 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120946 5203_ $$aAtrial 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.
000120946 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-105674RB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 860974-PersonalizeAF$$9info:eu-repo/grantAgreement/EC/H2020/860974/EU/Personalized Therapies for Atrial Fibrillation. A Translational Approach/PersonalizeAF$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA$$9info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA$$9info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group$$9info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón
000120946 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000120946 590__ $$a3.2$$b2022
000120946 592__ $$a0.653$$b2022
000120946 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b17 / 55 = 0.309$$c2022$$dQ2$$eT1
000120946 593__ $$aComputer Science Applications$$c2022$$dQ2
000120946 591__ $$aMEDICAL INFORMATICS$$b18 / 31 = 0.581$$c2022$$dQ3$$eT2
000120946 593__ $$aBiomedical Engineering$$c2022$$dQ2
000120946 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b60 / 110 = 0.545$$c2022$$dQ3$$eT2
000120946 591__ $$aENGINEERING, BIOMEDICAL$$b56 / 96 = 0.583$$c2022$$dQ3$$eT2
000120946 594__ $$a6.1$$b2022
000120946 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000120946 700__ $$0(orcid)0000-0002-0166-2837$$aAlcaine, Alejandro
000120946 700__ $$aRocher, Sara
000120946 700__ $$aMartinez-Mateu, Laura
000120946 700__ $$aSaiz, Javier
000120946 700__ $$aInvers-Rubio, Eric
000120946 700__ $$aGuillem, Maria S.
000120946 700__ $$0(orcid)0000-0002-7503-3339$$aMartínez, Juan Pablo$$uUniversidad de Zaragoza
000120946 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza
000120946 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000120946 773__ $$g60, 11 (2022), 3091-3112$$pMed. biol. eng. comput.$$tMEDICAL & BIOLOGICAL ENGINEERING & COMPUTING$$x0140-0118
000120946 8564_ $$s4097011$$uhttps://zaguan.unizar.es/record/120946/files/texto_completo.pdf$$yVersión publicada
000120946 8564_ $$s2348548$$uhttps://zaguan.unizar.es/record/120946/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000120946 909CO $$ooai:zaguan.unizar.es:120946$$particulos$$pdriver
000120946 951__ $$a2024-03-18-15:02:34
000120946 980__ $$aARTICLE