Life-threatening ventricular arrhythmia prediction in patients with dilated cardiomyopathy using explainable electrocardiogram-based deep neural networks
Zabihi Sammani, Arjan; van de Leur, Rutger R; Henkens, Michiel T H M; Meine, Mathias; Loh, Peter; Hassink, Rutger J; Oberski, Daniel L; Heymans, Stephane R B; Doevendans, Pieter A; Asselbergs, Folkert W; te Riele, Anneline S J M; van Es, René
(2022) Europace, volume 24, issue 10, pp. 1645 - 1654
(Article)
Abstract
Aims While electrocardiogram (ECG) characteristics have been associated with life-threatening ventricular arrhythmias (LTVA) in dilated cardiomyopathy (DCM), they typically rely on human-derived parameters. Deep neural networks (DNNs) can discover complex ECG patterns, but the interpretation is hampered by their ‘black-box’ characteristics. We aimed to detect DCM patients at risk of
... read more
LTVA using an inherently explainable DNN. Methods and results In this two-phase study, we first developed a variational autoencoder DNN on more than 1 million 12-lead median beat ECGs, compressing the ECG into 21 different factors (F): FactorECG. Next, we used two cohorts with a combined total of 695 DCM patients and entered these factors in a Cox regression for the composite LTVA outcome, which was defined as sudden cardiac arrest, spontaneous sustained ventricular tachycardia, or implantable cardioverter-defibrillator treated ventricular arrhythmia. Most patients were male (n = 442, 64%) with a median age of 54 years [interquartile range (IQR) 44–62], and median left ventricular ejection fraction of 30% (IQR 23–39). A total of 115 patients (16.5%) reached the study outcome. Factors F8 (prolonged PR-interval and P-wave duration, P, 0.005), F15 (reduced P-wave height, P = 0.04), F25 (increased right bundle branch delay, P = 0.02), F27 (P-wave axis P, 0.005), and F32 (reduced QRS-T voltages P = 0.03) were significantly associated with LTVA. Conclusion Inherently explainable DNNs can detect patients at risk of LTVA which is mainly driven by P-wave abnormalities.
show less
Download/Full Text
Keywords: Arrhythmias, Cardiac/complications, Cardiomyopathy, Dilated/complications, Death, Sudden, Cardiac/etiology, Deep neural network, Defibrillators, Implantable, Dilated cardiomyopathy, Electrocardiography/methods, Female, Humans, Implantable cardioverter-defibrillator, Male, Middle Aged, Neural Networks, Computer, Prognosis, Risk Factors, Stroke Volume, Sudden cardiac death, Ventricular Function, Left/physiology, Journal Article
ISSN: 1099-5129
Publisher: Oxford University Press
Note: Publisher Copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.
(Peer reviewed)