ENHANCED DETECTION OF DISTINGUISHING FEATURES IN SIGNAL-AVERAGED ELECTROCARDIOGRAMS FROM PATIENTS WITH VENTRICULAR-TACHYCARDIA BY COMBINED SPATIAL AND SPECTRAL ANALYSES OF ENTIRE CARDIAC CYCLE

Background Signals generated by myocardium responsible for ventricular tachycardia (VT) contribute to the entire QRS complex, ST segment, an d T wave and are spatially distributed over the entire torso. However, current methods of signal-averaged ECG analysis restrict interrogatio n to the terminal QRS complex, do not include data on the body surface distributions of the distinguishing features detected, and have a lim ited clinical value because of a low positive predictive accuracy. Acc ordingly, we tested the hypothesis that frequency analysis of the enti re cardiac cycle of spatially selected ECGs based on isoharmonic maps of the body surface enhance the detection of the unique spectral featu res in signal-averaged ECGs that differentiate patients with from thos e without VT. Methods and Results Isoharmonic maps of the body surface were calculated during sinus rhythm with the use of forward problem s olutions for 32 patients with sustained VT, 30 without VT, and 10 heal thy subjects and analyzed over a bandwidth of 0.05 to 470 Hz. Spectra of ECGs at the maximum and minimum of each patient's isoharmonic map o f 1 to 7 Hz demonstrated a broadened bandwidth of significant separati on (P<.05) for patients with from those without VT compared with the s eparation achieved with the use of Frank ECGs alone. Furthermore, the statistical significance within the bands of separation was greater fo r spatially selected ECGs compared with the Frank leads. Frank leads s eparated patients over the band from 11 to 84 Hz with a mean value of P=.0094. ECGs at the maximum of 1-to-7-Hz isoharmonic maps separated p atients over the 8-to-111-Hz band with a mean value of P=.0062 (range, P<.05 to P<.0000001). ECGs at the minimum of 1-to-7-Hz isoharmonic ma ps extended the low-frequency end of the band of separation, which cov ered 0 to 69 Hz with a mean value of P=.0039 (range, P<.05 to P<.00000 01). Subgroup analysis verified that results were independent of QRS d uration. Conclusions Spectral analysis of ECGs that are spatially sele cted for each patient is superior to orthogonal ECGs and augments dete ction of distinguishing features in ECGs that identify risk of VT. The new data acquired from analysis of spatially selected ECGs from indiv idual patients provide the information on the specific frequency bands and an improved ECG-lead system required to refine methods of analysi s of the signal-averaged ECG.