AuthorsM. Albatat, H. Arevalo, J. Bergsland, V. Strøm, I. Balasingham and H. H. Odland
TitleOptimal pacing sites in cardiac resynchronization by left ventricular activation front analysis
AfilliationScientific Computing
Project(s)Department of Computational Physiology
StatusPublished
Publication TypeJournal Article
Year of Publication2021
JournalComputers in Biology and Medicine
Volume128
Pagination104159
PublisherElsevier
ISSN0010-4825
KeywordsCardiac resynchronization therapy, Cardiology, Computational modeling, electrophysiology, Heart failure
Abstract

Cardiac resynchronization therapy (CRT) can substantially improve dyssynchronous heart failure and reduce mortality. However, about one-third of patients who are implanted, derive no measurable benefit from CRT. Non-response may partly be due to suboptimal activation of the left ventricle (LV) caused by electrophysiological heterogeneities. The goal of this study is to investigate the performance of a newly developed method used to analyze electrical wavefront propagation in a heart model including myocardial scar and compare this to clinical benchmark studies. We used computational models to measure the maximum activation front (MAF) in the LV during different pacing scenarios. Different heart geometries and scars were created based on cardiac MR images of three patients. The right ventricle (RV) was paced from the apex and the LV was paced from 12 different sites, single site, dual-site and triple site. Our results showed that for single LV site pacing, the pacing site with the largest MAF corresponded with the latest activated regions of the LV demonstrated during RV pacing, which also agrees with previous markers used for predicting optimal single-site pacing location. We then demonstrated the utility of MAF in predicting optimal electrode placements in more complex scenarios including scar and multi-site LV pacing. This study demonstrates the potential value of computational simulations in understanding and planning CRT.

URLhttp://www.sciencedirect.com/science/article/pii/S001048252030490X
DOI10.1016/j.compbiomed.2020.104159
Citation KeyALBATAT2021104159