Journal
COMPUTERS IN BIOLOGY AND MEDICINE
Volume 128, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2020.104159
Keywords
Cardiac resynchronization therapy; Heart failure; Electrophysiology; Computational modeling; Cardiology
Categories
Funding
- European Union's H2020: MSCA: ITN program for the Wireless In-body Environment Communication WiBEC project [675353]
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This study aimed to investigate the performance of a newly developed method to analyze electrical wavefront propagation in a heart model and compare it to clinical benchmark studies. The results demonstrated the utility of maximum activation front (MAF) in predicting optimal electrode placements in different pacing scenarios including scar and multi-site LV pacing, showing the potential value of computational simulations in understanding and planning CRT.
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.
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