Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments

Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both po...

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Autores principales:	Xinyang Li, Xili Shi, Balvinder S. Handa, Arunashis Sau, Bowen Zhang, Norman A. Qureshi, Zachary I. Whinnett, Nick W. F. Linton, Phang Boon Lim, Prapa Kanagaratnam, Nicholas S. Peters, Fu Siong Ng
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	fibrillation cardiac arrhythmia electrocardiography electrograms ablation Physiology QP1-981
Acceso en línea:	https://doaj.org/article/96afc6244d214becb73df439d2161c9e
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spelling	oai:doaj.org-article:96afc6244d214becb73df439d2161c9e2021-11-11T09:35:07ZClassification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments1664-042X10.3389/fphys.2021.712454https://doaj.org/article/96afc6244d214becb73df439d2161c9e2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fphys.2021.712454/fullhttps://doaj.org/toc/1664-042XBackground: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both possible mechanisms by which fibrillation is sustained. Determining the underlying mechanisms of fibrillation may be helpful in tailoring treatment strategies. We investigated whether global fibrillation organisation, a surrogate for fibrillation mechanism, can be determined from electrocardiograms (ECGs) using band-power (BP) feature analysis and machine learning.Methods: In this study, we proposed a novel ECG classification framework to differentiate fibrillation organisation levels. BP features were derived from surface ECGs and fed to a linear discriminant analysis classifier to predict fibrillation organisation level. Two datasets, single-channel ECGs of rat VF (n = 9) and 12-lead ECGs of human AF (n = 17), were used for model evaluation in a leave-one-out (LOO) manner.Results: The proposed method correctly predicted the organisation level from rat VF ECG with the sensitivity of 75%, specificity of 80%, and accuracy of 78%, and from clinical AF ECG with the sensitivity of 80%, specificity of 92%, and accuracy of 88%.Conclusion: Our proposed method can distinguish between AF/VF of different global organisation levels non-invasively from the ECG alone. This may aid in patient selection and guiding mechanism-directed tailored treatment strategies.Xinyang LiXili ShiBalvinder S. HandaArunashis SauBowen ZhangNorman A. QureshiZachary I. WhinnettNick W. F. LintonPhang Boon LimPrapa KanagaratnamNicholas S. PetersFu Siong NgFrontiers Media S.A.articlefibrillationcardiac arrhythmiaelectrocardiographyelectrogramsablationPhysiologyQP1-981ENFrontiers in Physiology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fibrillation cardiac arrhythmia electrocardiography electrograms ablation Physiology QP1-981
spellingShingle	fibrillation cardiac arrhythmia electrocardiography electrograms ablation Physiology QP1-981 Xinyang Li Xili Shi Balvinder S. Handa Arunashis Sau Bowen Zhang Norman A. Qureshi Zachary I. Whinnett Nick W. F. Linton Phang Boon Lim Prapa Kanagaratnam Nicholas S. Peters Fu Siong Ng Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
description	Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both possible mechanisms by which fibrillation is sustained. Determining the underlying mechanisms of fibrillation may be helpful in tailoring treatment strategies. We investigated whether global fibrillation organisation, a surrogate for fibrillation mechanism, can be determined from electrocardiograms (ECGs) using band-power (BP) feature analysis and machine learning.Methods: In this study, we proposed a novel ECG classification framework to differentiate fibrillation organisation levels. BP features were derived from surface ECGs and fed to a linear discriminant analysis classifier to predict fibrillation organisation level. Two datasets, single-channel ECGs of rat VF (n = 9) and 12-lead ECGs of human AF (n = 17), were used for model evaluation in a leave-one-out (LOO) manner.Results: The proposed method correctly predicted the organisation level from rat VF ECG with the sensitivity of 75%, specificity of 80%, and accuracy of 78%, and from clinical AF ECG with the sensitivity of 80%, specificity of 92%, and accuracy of 88%.Conclusion: Our proposed method can distinguish between AF/VF of different global organisation levels non-invasively from the ECG alone. This may aid in patient selection and guiding mechanism-directed tailored treatment strategies.
format	article
author	Xinyang Li Xili Shi Balvinder S. Handa Arunashis Sau Bowen Zhang Norman A. Qureshi Zachary I. Whinnett Nick W. F. Linton Phang Boon Lim Prapa Kanagaratnam Nicholas S. Peters Fu Siong Ng
author_facet	Xinyang Li Xili Shi Balvinder S. Handa Arunashis Sau Bowen Zhang Norman A. Qureshi Zachary I. Whinnett Nick W. F. Linton Phang Boon Lim Prapa Kanagaratnam Nicholas S. Peters Fu Siong Ng
author_sort	Xinyang Li
title	Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
title_short	Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
title_full	Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
title_fullStr	Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
title_full_unstemmed	Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments
title_sort	classification of fibrillation organisation using electrocardiograms to guide mechanism-directed treatments
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/96afc6244d214becb73df439d2161c9e
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Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments

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