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Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study
Background: Non-invasive cardiac mapping—also known as Electrocardiographic imaging (ECGi)—is a novel, painless and relatively economic method to map the electrical activation and repolarization patterns of the heart, providing a valuable tool for early identification and diagnosis of conduction abn...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6460935/ https://www.ncbi.nlm.nih.gov/pubmed/31024330 http://dx.doi.org/10.3389/fphys.2019.00308 |
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author | Perez Alday, Erick Andres Whittaker, Dominic G. Benson, Alan P. Colman, Michael A. |
author_facet | Perez Alday, Erick Andres Whittaker, Dominic G. Benson, Alan P. Colman, Michael A. |
author_sort | Perez Alday, Erick Andres |
collection | PubMed |
description | Background: Non-invasive cardiac mapping—also known as Electrocardiographic imaging (ECGi)—is a novel, painless and relatively economic method to map the electrical activation and repolarization patterns of the heart, providing a valuable tool for early identification and diagnosis of conduction abnormalities and arrhythmias. Moreover, the ability to obtain information on cardiac electrical activity non-invasively using ECGi provides the potential for a priori information to guide invasive surgical procedures, improving success rates, and reducing procedure time. Previous studies have shown the influence of clinical variables, such as heart rate, heart size, endocardial wall, and body composition on surface electrocardiogram (ECG) measurements. The influence of clinical variables on the ECG variability has provided information on cardiovascular control and its abnormalities in various pathologies. However, the effects of such clinical variables on the Body Surface Potential (BSP) and ECGi maps have yet to be systematically investigated. Methods: In this study we investigated the effects of heart size, intracardiac thickness, and heart rate on BSP and ECGi maps using a previously-developed 3D electrophysiologically-detailed ventricles-torso model. The inverse solution was solved using the three different Tikhonov regularization methods. Results: Through comparison of multiple measures of error/accuracy on the ECGi reconstructions, our results showed that using different heart geometries to solve the forward and inverse problems produced a larger estimated focal excitation location. An increase of ~2 mm in the Euclidean distance error was observed for an increase in the heart size. However, the estimation of the location of focal activity was still able to be obtained. Similarly, a Euclidean distance increase was observed when the order of regularization was reduced. For the case of activation maps reconstructed at the same ectopic focus location but different heart rates, an increase in the errors and Euclidean distance was observed when the heart rate was increased. Conclusions: Non-invasive cardiac mapping can still provide useful information about cardiac activation patterns for the cases when a different geometry is used for the inverse problem compared to the one used for the forward solution; rapid pacing rates can induce order-dependent errors in the accuracy of reconstruction. |
format | Online Article Text |
id | pubmed-6460935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64609352019-04-25 Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study Perez Alday, Erick Andres Whittaker, Dominic G. Benson, Alan P. Colman, Michael A. Front Physiol Physiology Background: Non-invasive cardiac mapping—also known as Electrocardiographic imaging (ECGi)—is a novel, painless and relatively economic method to map the electrical activation and repolarization patterns of the heart, providing a valuable tool for early identification and diagnosis of conduction abnormalities and arrhythmias. Moreover, the ability to obtain information on cardiac electrical activity non-invasively using ECGi provides the potential for a priori information to guide invasive surgical procedures, improving success rates, and reducing procedure time. Previous studies have shown the influence of clinical variables, such as heart rate, heart size, endocardial wall, and body composition on surface electrocardiogram (ECG) measurements. The influence of clinical variables on the ECG variability has provided information on cardiovascular control and its abnormalities in various pathologies. However, the effects of such clinical variables on the Body Surface Potential (BSP) and ECGi maps have yet to be systematically investigated. Methods: In this study we investigated the effects of heart size, intracardiac thickness, and heart rate on BSP and ECGi maps using a previously-developed 3D electrophysiologically-detailed ventricles-torso model. The inverse solution was solved using the three different Tikhonov regularization methods. Results: Through comparison of multiple measures of error/accuracy on the ECGi reconstructions, our results showed that using different heart geometries to solve the forward and inverse problems produced a larger estimated focal excitation location. An increase of ~2 mm in the Euclidean distance error was observed for an increase in the heart size. However, the estimation of the location of focal activity was still able to be obtained. Similarly, a Euclidean distance increase was observed when the order of regularization was reduced. For the case of activation maps reconstructed at the same ectopic focus location but different heart rates, an increase in the errors and Euclidean distance was observed when the heart rate was increased. Conclusions: Non-invasive cardiac mapping can still provide useful information about cardiac activation patterns for the cases when a different geometry is used for the inverse problem compared to the one used for the forward solution; rapid pacing rates can induce order-dependent errors in the accuracy of reconstruction. Frontiers Media S.A. 2019-04-05 /pmc/articles/PMC6460935/ /pubmed/31024330 http://dx.doi.org/10.3389/fphys.2019.00308 Text en Copyright © 2019 Perez Alday, Whittaker, Benson and Colman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Perez Alday, Erick Andres Whittaker, Dominic G. Benson, Alan P. Colman, Michael A. Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title | Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title_full | Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title_fullStr | Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title_full_unstemmed | Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title_short | Effects of Heart Rate and Ventricular Wall Thickness on Non-invasive Mapping: An in silico Study |
title_sort | effects of heart rate and ventricular wall thickness on non-invasive mapping: an in silico study |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6460935/ https://www.ncbi.nlm.nih.gov/pubmed/31024330 http://dx.doi.org/10.3389/fphys.2019.00308 |
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