Use of Electrocardiographic Depolarization Abnormalities for Detection of Stress-Induced Ischemia as Defined by Myocardial Perfusion Imaging

Abstract

High-frequency mid-QRS (HFQRS) analysis was recently introduced as a tool for identification of stress-induced ischemia. The diagnostic performance of this electrocardiographic technique has not been determined in a large cohort of patients. This study compared the diagnostic performance of HFQRS analysis to conventional ST-segment analysis in detecting exercise-induced ischemia. The study included 996 patients (56 ± 10 years of age, 670 men) referred for exercise myocardial perfusion imaging (MPI), which served as the gold standard of ischemia. High-resolution electrocardiogram was used for computer analysis of HFQRS signals. Number of electrocardiographic leads with ≥50% decrease of HFQRS intensity (L(50%)) was used as an index of ischemia. Perfusion images were evaluated semiquantitatively. Receiver operating characteristic analysis demonstrated an L(50%) ≥3 as the criterion that yielded optimal sensitivity and specificity for diagnosing moderate/severe ischemia. Compared to ST-segment analysis HFQRS analysis was more sensitive (69% vs 39%, p <0.005) and more specific (86% vs 82%, p <0.05). L(50%) correlated with amount of MPI ischemia (R(2) = 0.75, p <0.0001). Multivariate logistic regression analysis demonstrated a significant incremental diagnostic value for the addition of HFQRS data to a model containing pretest and conventional exercise parameters. L(50%) was the best predictor of mild or moderate/severe MPI ischemia. In conclusion, computerized HFQRS analysis improved the diagnostic performance of conventional stress electrocardiogram in detecting exercise-induced ischemia. Thus, this technique might aid in the noninvasive evaluation of coronary artery disease.