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  • Title: Body surface ECG potential maps in acute myocardial infarction.
    Author: McMechan SR, MacKenzie G, Allen J, Wright GT, Dempsey GJ, Crawley M, Anderson J, Adgey AA.
    Journal: J Electrocardiol; 1995; 28 Suppl():184-90. PubMed ID: 8656109.
    Abstract:
    An algorithm for the early detection of acute myocardial infarction (MI) using body surface electrocardiographic potential mapping has been developed. The mapping system consists of a 64-hydrogel electrode harness applied rapidly to the anterior chest, from which electrocardiographic signals are stored on a memory card and processed by computer. At each of the 64 points, QRS and ST-T isointegrals and 10 other features of the QRST segment are measured. Using these measurements, new variables are derived that express the shape of the three-dimensional geometric surface of the map. The isointegrals, features, and shape variables are used in a variety of techniques to discriminate between MI and control subjects. Maps were recorded from 69 patients at initial presentation of chest pain suggestive of acute MI and from 80 healthy control subjects. Using a multiple logistic regression technique, 14 variables were identified that correctly classified 79 of the 80 control subjects (specificity, 98.8%) and 65 of the 69 MI patients (sensitivity, 94.2%). The algorithm based on these 14 variables was applied prospectively to maps recorded on a further 48 control subjects and 59 patients with acute MI. Of the MI patients, 31 had inferior, 13 inferoposterior, 10 anterior, 2 posterior, 1 lateral, 1 inferior with right bundle branch block, and 1 anterior non Q wave MI. The algorithm correctly classified all 48 control subjects (specificity, 100%) and 57 of the 59 MI patients (sensitivity, 96.6%). Marked differences in the three-dimensional geometric map surfaces between the control subjects and MI patients were demonstrated. Variables derived from these surfaces form the basis of an algorithm with a high sensitivity and specificity for the automated detection of acute MI. The design of adaptive algorithms and their application to patients with chest pain and atypical electrocardiographic changes, particularly ST depression, may lead to the earlier detection of MI and greater numbers of patients receiving thrombolytic therapy.
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