Cluitmans, Matthijs J.M.Lluch Álvarez, ÈricMorales, Hernán G.Heijman, JordiVaulders, Paul2020-03-202020-03-202018Cluitmans MJM, Lluch E, Morales HG, Heijman J, Volders P. Personalized computational framework to study arrhythmia mechanisms on top of ECGI-detected sub-strate. In: Computing in Cardiology Conference (CinC); 2018 Sep 23-26; Maastricht, Netherlands. New York: IEEE; 2018. DOI: 10.22489/CinC.2018.3252325-887Xhttp://hdl.handle.net/10230/43969Comunicació presentada a: Computing in Cardiology Conference (CinC) celebrat del 23 al 26 de setembre de 2018 a Maastricht, Països Baixos.Electrocardiographic Imaging (ECGI) can unmask electrical abnormalities that were difficult to detect using the standard 12-lead ECG. However, it is still challenging to interpret the potential arrhythmogenic consequence of electrical patterns found with ECGI. Here, we introduce a computational framework that allows personalized simulations of cardiac electrophysiology (EP) to mimic electrical substrate as detected in an individual, to study the interaction between that substrate and premature ventricular complexes (PVCs). In patient data, electrical substrate identified using ECGI shows regions of pronounced dispersion of local recovery (i.e., recovery gradients). A computational model of ventricular EP was developed and then used to mimic the recovery gradients and PVCs found in patients. We studied a variety of gradients (6-98 ms/cm) and coupling intervals of the extra stimulus (-70 to +260 ms relative to the end of local recovery), which showed that re-entry can only occur when dispersion of recovery is large (≥76 ms/cm), and the extra stimulus occurs just after local recovery ended (~+40 ms). In conclusion, this computational framework allows to identify the specific conditions under which ECGI-detected substrates and PVCs can lead to re-entry in a personalized approach.application/pdfeng© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://dx.doi.org/10.22489/CinC.2018.325 Licensed by their authors under the Creative Commons Attribution License 2.5info:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.22489/CinC.2018.325info:eu-repo/semantics/openAccess