Analysis of the Intraventricular Electrogram for Differentiation of Distinct Monomorphic Ventricular Arrhythmias

Abstract

This study investigated the effectiveness of correlation waveform analysis for identifying different ventricular electrogram morphologies of multiple VTs in the same patient. Patients with implantable antitachycardia devices are commonly subject to the occurrence of more than one distinct monomorphic VT. Each of these VTs may have unique therapeutic alternatives for termination. VTs with identical and different monomorphic configurations were recorded (1-500 Hz) using distal bipolar (1 cm) and distal unipolar electrograms from the right ventricular apex. Thirty-six distinct monomorphic VTs induced in 15 patients were analyzed. Nine VTs with identical morphologies (12/12 surface ECGs) were induced twice and used as a control. A template was created for each VT induced. Correlation waveform analysis was used to compare each depolarization of all other VTs induced subsequently in the same patient. The mean correlation coefficient (p mu) of cycle-by-cycle analysis was used as a discriminant function: p mu > or = 0.95 was considered matched; and p mu < 0.95 was considered distinct. From the control population, VTs were successfully classified as identical in 9 of 9 cases (100%) using both bipolar and unipolar electrograms. VTs with different monomorphic configurations were successfully classified as being different in 31 of 33 cases (94%) using bipolar electrogram analysis and in 29 of 33 cases (88%) using the unipolar. Template matching is effective for detecting: (1) the recurrence of VTs, which are identical; and (2) the occurrence of a VT with a different configuration. This method appears effective using either unipolar or bipolar intracardiac waveforms.

A Pilot Study Examining the Performance of Polynomial‐Modeled Ventricular Shock Electrograms for Rhythm Discrimination in Implantable Devices

“…Mathematical modeling of the surface electrocardiogram has been shown to be feasible using various methods, 8,9 albeit at the expense of using a large number of coefficients. Correlation waveform analysis has been used to capture the morphology of ventricular EGM during cardiac arrhythmia and to compare it to the same EGM during normal rhythm 10–12 . These correlation techniques reflect overall morphologic similarity between EGM beats; however, they do not “model” the EGM per se .…”

“…Correlation waveform analysis has been used to capture the morphology of ventricular EGM during cardiac arrhythmia and to compare it to the same EGM during normal rhythm. [10][11][12] These correlation techniques reflect overall morphologic similarity between EGM beats; however, they do not "model" the EGM per se. Correlation techniques are not affected by heart rate increases though an increase in amplitude is often seen with increasing sympathetic tone.…”

A Segmental Polynomial Model of Ventricular Electrograms as a Simple and Efficient Morphology Discriminator for Implantable Devices

“…Correlation waveform analysis has been used to capture the morphology of ventricular EGM during cardiac arrhythmia and to compare it to the same EGM during normal rhythm. [8][9][10] These correlation techniques reflect overall morphologic similarity between EGM beats, however they do not "model" the EGM per se. Correlation techniques are not affected by heart rate increases, though an increase in amplitude is often seen with increasing sympathetic tone.…”

Automatic Discrimination Between Supraventricular and Ventricular Tachycardia Using a Multilayer Perceptron in Implantable Cardioverter Defibrillators

“…The CWA criterion uses the correlation coefficient to compare EGMs acquired during tachycardia with a template obtained during sinus rhythm. 6 A sinus rhythmmatched waveform will produce a coefficient next to unity and indicates a SVT tachycardia, whereas lower values of the coefficient are usually provided by VT beats. EGMs were detected with a dynamic threshold scheme, centered with respect to the R wave and segmented from 80 ms before to 80 ms after the time center.…”

“…[3][4][5] Third, the morphological analysis of ICD-stored ventricular electrograms (EGMs) has been proposed, based on the different duration and shape of EGMs with supraventricular (SVT) and ventricular origin. The correlation waveform analysis (CWA) 6 and the estimation of the width of the QRS 7 have been used for this purpose, both based on the calculation of a single statistical parameter.…”