A validation of derived epicardial potential distributions by prediction of the coronary artery involved in acute myocardial infarction in humans

Abstract

We have developed computer algorithms that enable epicardial potential distributions to be calculated from electrocardiographic body surface data. To validate this inverse transformation we obtained body surface maps during the ST segment in 55 patients with acute infarction who subsequently underwent coronary arteriography and we constructed epicardial ST segment potential distributions for each patient. From the unlabeled epicardial maps one of us predicted the coronary artery that would be found to be involved in the infarction. These predictions were compared with the results of coronary arteriography and this showed that the analysis of the epicardial map correctly predicted the coronary artery involved in 40 of 55 patients (72.7%). In another eight patients the anatomy was partially predicted. In the 15 patients in whom the prediction was incorrect or partially correct (27.3%), 11 had critical disease or occlusions of the predicted coronary artery but the infarct-related artery was incorrectly identified. This verifies that sensible epicardial potential maps can be calculated from body surface electrocardiographic data, and that these data are sufficiently accurate to predict the vessel involved in acute infarction.