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A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction

Pace mapping is commonly used to locate the origin of ventricular arrhythmias, especially premature ventricular contraction (PVC). However, this technique relies on clinicians’ ability to rapidly interpret ECG data. To avoid time-consuming interpretation of ECG morphology, some automated algorithms...

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Autores principales: He, Kaiyue, Sun, Jian, Wang, Yiwen, Zhong, Gaoyan, Yang, Cuiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943872/
https://www.ncbi.nlm.nih.gov/pubmed/33716789
http://dx.doi.org/10.3389/fphys.2021.641358
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author He, Kaiyue
Sun, Jian
Wang, Yiwen
Zhong, Gaoyan
Yang, Cuiwei
author_facet He, Kaiyue
Sun, Jian
Wang, Yiwen
Zhong, Gaoyan
Yang, Cuiwei
author_sort He, Kaiyue
collection PubMed
description Pace mapping is commonly used to locate the origin of ventricular arrhythmias, especially premature ventricular contraction (PVC). However, this technique relies on clinicians’ ability to rapidly interpret ECG data. To avoid time-consuming interpretation of ECG morphology, some automated algorithms or computational models have been explored to guide the ablation. Inspired by these studies, we propose a novel model based on spatial and morphological domains. The purpose of this study is to assess this model and compare it with three existing models. The data are available from the Experimental Data and Geometric Analysis Repository database in which three in vivo PVC patients are included. To measure the hit rate (A hit occurs when the predicted site is within 15 mm of the target) of different algorithms, 47 target sites are tested. Moreover, to evaluate the efficiency of different models in narrowing down the target range, 54 targets are verified. As a result, the proposed algorithm achieves the most hits (37/47) and fewest misses (9/47), and it narrows down the target range most, from 27.62 ± 3.47 mm to 10.72 ± 9.58 mm among 54 target sites. It is expected to be applied in the real-time prediction of the origin of ventricular activation to guide the clinician toward the target site.
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spelling pubmed-79438722021-03-11 A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction He, Kaiyue Sun, Jian Wang, Yiwen Zhong, Gaoyan Yang, Cuiwei Front Physiol Physiology Pace mapping is commonly used to locate the origin of ventricular arrhythmias, especially premature ventricular contraction (PVC). However, this technique relies on clinicians’ ability to rapidly interpret ECG data. To avoid time-consuming interpretation of ECG morphology, some automated algorithms or computational models have been explored to guide the ablation. Inspired by these studies, we propose a novel model based on spatial and morphological domains. The purpose of this study is to assess this model and compare it with three existing models. The data are available from the Experimental Data and Geometric Analysis Repository database in which three in vivo PVC patients are included. To measure the hit rate (A hit occurs when the predicted site is within 15 mm of the target) of different algorithms, 47 target sites are tested. Moreover, to evaluate the efficiency of different models in narrowing down the target range, 54 targets are verified. As a result, the proposed algorithm achieves the most hits (37/47) and fewest misses (9/47), and it narrows down the target range most, from 27.62 ± 3.47 mm to 10.72 ± 9.58 mm among 54 target sites. It is expected to be applied in the real-time prediction of the origin of ventricular activation to guide the clinician toward the target site. Frontiers Media S.A. 2021-02-24 /pmc/articles/PMC7943872/ /pubmed/33716789 http://dx.doi.org/10.3389/fphys.2021.641358 Text en Copyright © 2021 He, Sun, Wang, Zhong and Yang. 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
He, Kaiyue
Sun, Jian
Wang, Yiwen
Zhong, Gaoyan
Yang, Cuiwei
A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title_full A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title_fullStr A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title_full_unstemmed A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title_short A Novel Model Based on Spatial and Morphological Domains to Predict the Origin of Premature Ventricular Contraction
title_sort novel model based on spatial and morphological domains to predict the origin of premature ventricular contraction
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943872/
https://www.ncbi.nlm.nih.gov/pubmed/33716789
http://dx.doi.org/10.3389/fphys.2021.641358
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