Mason Federico, Pandey Amitabh C, Gadaleta Matteo, Topol Eric J, Muse Evan D, Quer Giorgio
Scripps Research Translational Institute, La Jolla, 92037, CA, USA.
Department of Information Engineering, University of Padova, Padova, 35131, Italy.
NPJ Digit Med. 2024 Aug 1;7(1):201. doi: 10.1038/s41746-024-01193-7.
The 12-lead electrocardiogram (ECG) is an integral component to the diagnosis of a multitude of cardiovascular conditions. It is performed using a complex set of skin surface electrodes, limiting its use outside traditional clinical settings. We developed an artificial intelligence algorithm, trained over 600,000 clinically acquired ECGs, to explore whether fewer leads as input are sufficient to reconstruct a 12-lead ECG. Two limb leads (I and II) and one precordial lead (V3) were required to generate a reconstructed 12-lead ECG highly correlated with the original ECG. An automatic algorithm for detection of ECG features consistent with acute myocardial infarction (MI) performed similarly for original and reconstructed ECGs (AUC = 0.95). When interpreted by cardiologists, reconstructed ECGs achieved an accuracy of 81.4 ± 5.0% in identifying ECG features of ST-segment elevation MI, comparable with the original 12-lead ECGs (accuracy 84.6 ± 4.6%). These results will impact development efforts to innovate ECG acquisition methods with simplified tools in non-specialized settings.
12导联心电图（ECG）是多种心血管疾病诊断中不可或缺的组成部分。它通过一组复杂的皮肤表面电极进行检测，这限制了其在传统临床环境之外的使用。我们开发了一种人工智能算法，该算法在超过60万份临床采集的心电图上进行训练，以探究较少的导联作为输入是否足以重建12导联心电图。生成与原始心电图高度相关的重建12导联心电图需要两个肢体导联（I和II）和一个胸前导联（V3）。一种用于检测与急性心肌梗死（MI）一致的心电图特征的自动算法，对原始心电图和重建心电图的表现相似（曲线下面积[AUC]=0.95）。当由心脏病专家解读时，重建心电图在识别ST段抬高型心肌梗死的心电图特征方面的准确率为81.4±5.0%，与原始12导联心电图相当（准确率84.6±4.6%）。这些结果将影响在非专业环境中使用简化工具创新心电图采集方法的开发工作。
