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Enhancing premature ventricular contraction localization through electrocardiographic imaging and cardiac digital twins

Sánchez, Jorge ; Llorente-Lipe, Inés; Espinosa, Cristian Barrios ORCID iD icon 1; Loewe, Axel ORCID iD icon 1; Hernández-Romero, Ismael; Vicente-Puig, Jorge; Ros, Santiago; Atienza, Felipe; Carta-Bergaz, Alejandro; Climent, Andreu M.; Guillem, Maria S.
1 Institut für Biomedizinische Technik (IBT), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Premature ventricular contractions (PVCs) represent a common and clinically significant cardiac arrhythmia, contributing to a spectrum of cardiovascular disorders. Accurate localization of the origin of PVCs is essential for devising targeted therapeutic strategies and refining our comprehension of ventricular arrhythmogenesis. Traditionally, the 12-lead ECG has been the go-to diagnostic tool for PVCs. However, individual anatomical differences and inter-patient electrophysiology variability limit its effectiveness. This study presents a new method that combines electrocardiographic imaging (ECGI) with the concept of cardiac digital twins (ECGI-DT) to improve the accuracy of pinpointing the source of PVCs. By simulating a database of PVCs, we developed an ECGI-DT capable of estimating the origins of PVCs with much greater precision than possible previously. This study shows a notable improvement in identifying the initial site of PVC origin using ECGI-DT compared to ECGI alone: the average localization error dropped from 30.69 ± 23.71 mm with standard ECGI to 7.81 ± 3.82 mm using the ECGI-DT method. This marked reduction in error highlights the potential of ECGI-DT in revolutionizing PVC diagnosis and treatment. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000181049
Veröffentlicht am 22.12.2025
Originalveröffentlichung
DOI: 10.1016/j.compbiomed.2025.109994
Scopus
Zitationen: 4
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biomedizinische Technik (IBT)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 05.2025
Sprache Englisch
Identifikator ISSN: 0010-4825, 1879-0534
KITopen-ID: 1000181049
Erschienen in Computers in Biology and Medicine
Verlag Elsevier
Band 190
Seiten 109994
Vorab online veröffentlicht am 22.03.2025
Schlagwörter ECGI, Digital twins, PVC, Computer modeling, Therapy personalization
Nachgewiesen in Dimensions
OpenAlex
Scopus
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