Literature DB >> 33301952

Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis.

Mohammad Albatat1, Hermenegild Arevalo2, Jacob Bergsland3, Vilde Strøm2, Ilangko Balasingham4, Hans Henrik Odland5.   

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.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cardiac resynchronization therapy; Cardiology; Computational modeling; Electrophysiology; Heart failure

Year:  2020        PMID: 33301952     DOI: 10.1016/j.compbiomed.2020.104159

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  4 in total

1.  Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model.

Authors:  Lei Fan; Jenny S Choy; Farshad Raissi; Ghassan S Kassab; Lik Chuan Lee
Journal:  Comput Biol Med       Date:  2021-11-19       Impact factor: 4.589

2.  Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data.

Authors:  Svyatoslav Khamzin; Arsenii Dokuchaev; Anastasia Bazhutina; Tatiana Chumarnaya; Stepan Zubarev; Tamara Lyubimtseva; Viktoria Lebedeva; Dmitry Lebedev; Viatcheslav Gurev; Olga Solovyova
Journal:  Front Physiol       Date:  2021-12-14       Impact factor: 4.566

3.  Overview of Current Strategies Aiming at Improving Response to Cardiac Resynchronization Therapy.

Authors:  Yakup Yunus Yamantürk; Başar Candemir; Emir Baskovski; Kerim Esenboğa
Journal:  Anatol J Cardiol       Date:  2022-05       Impact factor: 1.475

4.  Determinants of the time-to-peak left ventricular dP/dt (Td) and QRS duration with different fusion strategies in cardiac resynchronization therapy.

Authors:  Hans Henrik Odland; Torbjørn Holm; Richard Cornelussen; Erik Kongsgård
Journal:  Front Cardiovasc Med       Date:  2022-09-15
  4 in total

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