基于脑电图的多任务深度学习在Wolff-Parkinson-white综合征中的辅助通路定位

IF 4.4 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Jasper Hennecken, Bauke K. O. Arends, Thomas Mast, Lukas Dekker, Pim van der Harst, Yuri Blaauw, Wolfgang Dichtl, Thomas Senoner, Rutger J. Hassink, Peter Loh, René van Es, Rutger R. van de Leur
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引用次数: 0

摘要

背景:Wolff-Parkinson-White综合征以房室副通路(AP)和房室再进入性心律失常为特征。导管消融入路和成功取决于AP位置。现有的基于心电图(ECG)的基于规则的算法耗时长,易于观察者之间的变化,并且使用delta波极性作为二值变量。为了克服这些挑战,我们提出了一种基于深度神经网络(DNN)的模型。方法排除有隐蔽性传导通路、多条顺行传导通路及无窦性心律心电图的患者。在导管消融过程中通过电生理测试确定AP位置,并将AP分为右侧AP、间隔AP和左侧AP。多任务学习与辅助识别的存在的预激励,旁路通路和位置,其中可能需要通过间隔穿刺提高可用性和性能。DNN与Milstein和Arruda算法进行了比较。结果1997年至2023年间,645例接受导管消融治疗AP的患者被纳入研究。该模型是利用567例患者的1.394张心电图建立的。DNN在两个独立的队列中使用78个心电图进行测试。该模型优于Milstein算法和Arruda算法,受试者工作特征曲线下面积(AUROC)为0.92(95%置信区间:0.88 - 0.96),而Arruda算法的AUROC为0.80;p <.001)和Milstein算法(AUROC为.81;p & lt;措施)。结论我们的模型在预测辅助通路位置方面表现出优异的歧视性,同时优于传统技术。临床上,该工具可以改善术前计划和风险分层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Localization of accessory pathways in Wolff-Parkinson-white syndrome using ECG-based multi-task deep learning

Localization of accessory pathways in Wolff-Parkinson-white syndrome using ECG-based multi-task deep learning

Background

Wolff-Parkinson-White syndrome is characterized by accessory atrioventricular pathways (AP) and atrio-ventricular re-entry arrhythmias. Catheter ablation approach and success are determined by AP location. Existing rule-based algorithms based on the electrocardiogram (ECG) are time consuming, prone to inter-observer variability and use delta wave polarity as a binary variable. To overcome these challenges, we propose a model based on a deep neural network (DNN).

Methods

Patients with concealed pathways, multiple antegrade conducting pathways or without any sinus rhythm ECGs were excluded. AP location was determined based on electrophysiological testing during catheter ablation and categorized into right-sided, septal and left-sided APs. Multi-task learning with auxiliary identification of the presence of pre-excitation, parahisian pathways and locations where a transseptal puncture is potentially required was used to increase usability and performance. The DNN was compared to the Milstein and Arruda algorithms.

Results

Between 1997 and 2023, 645 patients who underwent catheter ablation for an AP were included in the study. The model was developed using 1.394 ECGs from 567 patients. The DNN was tested using 78 ECGs in two independent cohorts. The model outperformed both the Milstein and Arruda algorithms with an area under the receiver operating characteristic curve (AUROC) of .92 (95% confidence interval: .88–.96) compared to the Arruda algorithm (AUROC of .80; p <.001) and the Milstein algorithm (AUROC of .81; p <.001).

Conclusions

Our model showed excellent discriminatory performance in predicting the location of an accessory pathway while outperforming conventional techniques. Clinically, this tool can improve preoperative planning and risk stratification.

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来源期刊
CiteScore
9.50
自引率
3.60%
发文量
192
审稿时长
1 months
期刊介绍: EJCI considers any original contribution from the most sophisticated basic molecular sciences to applied clinical and translational research and evidence-based medicine across a broad range of subspecialties. The EJCI publishes reports of high-quality research that pertain to the genetic, molecular, cellular, or physiological basis of human biology and disease, as well as research that addresses prevalence, diagnosis, course, treatment, and prevention of disease. We are primarily interested in studies directly pertinent to humans, but submission of robust in vitro and animal work is also encouraged. Interdisciplinary work and research using innovative methods and combinations of laboratory, clinical, and epidemiological methodologies and techniques is of great interest to the journal. Several categories of manuscripts (for detailed description see below) are considered: editorials, original articles (also including randomized clinical trials, systematic reviews and meta-analyses), reviews (narrative reviews), opinion articles (including debates, perspectives and commentaries); and letters to the Editor.
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