Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021

The electrocardiogram (ECG) is a non-invasive representation of the electrical
activity of the heart. Although the twelve-lead ECG is the standard diagnostic
screening system for many cardiological issues, the limited accessibility of
twelve-lead ECG devices provides a rationale for smaller, lower-cost, and
easier to use devices. While single-lead ECGs are limiting
[[1](https://pubmed.ncbi.nlm.nih.gov/9740885/)], reduced-lead ECG systems hold
promise, with evidence that subsets of the standard twelve leads can capture
useful information [[2](https://pubmed.ncbi.nlm.nih.gov/12539095)],
[[3](https://www.sciencedirect.com/science/article/abs/pii/S0022073606005346)],
[[4](https://pubmed.ncbi.nlm.nih.gov/3812249)] and even be comparable to
twelve-lead ECGs in some limited contexts. In 2017 we challenged the public to
classify AF from a single-lead ECG, and in 2020 we challenged the public to
diagnose a much larger number of cardiac problems using twelve-lead
recordings. However, there is limited evidence to demonstrate the utility of
reduced-lead ECGs for capturing a wide range of diagnostic information.

In this year's Challenge, we ask the following question: **' Will two do?'**
This year's Challenge builds on [last year's
Challenge](/content/challenge-2020/)
[[5]](https://doi.org/10.1088/1361-6579/abc960), which asked participants to
classify cardiac abnormalities from twelve-lead ECGs. We are asking you to
build an algorithm that can classify cardiac abnormalities from twelve-lead,
six-lead, four-lead, three-lead, and two-lead ECGs. We will test each
algorithm on databases of these reduced-lead ECGs, and the differences in
performances of the algorithms on these databases will reveal the utility of
reduced-lead ECGs in comparison to standard twelve-lead EGCs.

心电图（electrocardiogram, ECG）是心脏电活动的无创表征。尽管十二导联心电图是诸多心血管疾病的标准诊断筛查手段，但十二导联心电图设备的可及性有限，这为体积更小、成本更低、操作更简便的设备研发提供了合理性支撑。单导联心电图存在应用局限性[1]，而少导联心电图系统则颇具前景：已有研究证实，标准十二导联的导联子集可捕获有效临床信息[2,3,4]，甚至在部分特定场景下可与十二导联心电图相媲美。2017年，我们面向公众发起了基于单导联心电图的心房颤动（Atrial Fibrillation, AF）分类挑战赛；2020年，我们又发起了基于十二导联心电记录的多类心脏疾病诊断挑战赛。不过目前针对少导联心电图可覆盖广泛诊断信息的实用性证据仍较为匮乏。

在本年度挑战赛中，我们提出核心议题：**“双导联是否足够？”** 本届挑战赛延续自2020年挑战赛[5]，后者要求参赛者基于十二导联心电图完成心脏异常分类任务。本次挑战赛将要求参赛者开发可基于十二导联、六导联、四导联、三导联及双导联心电图实现心脏异常分类的算法。我们将使用各类少导联心电图数据库对各算法进行测试，通过对比各算法在不同导联数数据库上的性能差异，以揭示少导联心电图相较于标准十二导联心电图的实用价值。