SPATIAL FEATURES IN BODY-SURFACE POTENTIAL MAPS CAN IDENTIFY PATIENTSWITH A HISTORY OF SUSTAINED VENTRICULAR-TACHYCARDIA

Background Regional disparities of ventricular primary-repolarization properties contribute to an electrophysiological substrate for arrhyth mias. Such disparities can be assessed from body-surface distributions of ECG QRST areas. Our objective was to isolate and test those featur es of QRST-area distributions that would be suitable for identifying p atients at risk for life-threatening ventricular arrhythmias. Methods and Results We recorded ECGs simultaneously from 120 leads during sinu s rhythm for 204 patients taking no antiarrhythmic drugs: half had had sustained ventricular tachycardia (VT); the other half, a myocardial infarction but no history of VT. For each patient, we calculated the Q RST area in each lead and, using Karhunen-Loeve (K-L) expansion, reduc ed these data to 16 coefficients (each relating to one spatial feature , an eigenvector, derived from the total set of 204 QRST-area maps). U sing stepwise discriminant analysis, we selected feature subsets that best discriminated between the two groups, and we estimated by a boots trap procedure using 1000 trials how these subsets would perform on a prospective patient population. The mean diagnostic performance of the classifier for 1000 randomly selected training sets (n = 102 in each, with both groups equally represented) increased monotonically with th e number of features used for classification. The initial trend for th e corresponding test sets (n = 102 in each) was the same but reversed when the number of features exceeded eight. For an optimal set of eigh t spatial features, the sensitivity and specificity of the classifier for detecting patients with VT in 1000 test sets were (mean+/-SD) 90.3 +/-4.3% and 78.0+/-6.1%, and its positive and negative predictive accu racies were 80.7+/-4.2% and 59.2+/-4.2%, respectively. Use of QRS dura tion as a supplementary feature to eight K-L coefficients can, in the test sets, increase specificity to 80.9+/-5.4% and positive predictive accuracy to 82.8+/-3.9% compared with the results for the optimal num ber of eight K-L features alone. Conclusions Multiple body-surface ECG s contain valuable spatial features that can identify the presence of an arrhythmogenic substrate in the myocardium of patients at risk for ventricular arrhythmias. Our results compare very favorably with those achieved by any other known test, invasive or noninvasive, for arrhyt hmogenicity.