Recovery time dispersion measured by body surface mapping: noninvasive method of assessing vulnerability to ventricular tachyarrhythmias

Electrocardiographic imaging metrics to predict the risk of arrhythmia in patients with ischemic cardiomyopathy

Background

The leading cause of death in patients with ischemic cardiomyopathy is sudden cardiac death caused by ventricular arrhythmias. Accurate determination of arrhythmic risk in these patients is vital to allow clinicians to take appropriate preventive measures.

Objective

To review and summarize the literature on electrocardiographic imaging (ECGi) metrics that could be used to predict arrhythmic risk in patients with ischemic cardiomyopathy.

Methods

A comprehensive literature search was performed to retrieve research articles on non-invasive electrocardiographic mapping techniques. Inclusion criteria of the studies required the involvement of patients with ischemic cardiomyopathy or ischemic heart disease.

Results

A total of 17 papers were identified, five of which specifically utilized ECGi to acquire metrics associated with an increased risk of ventricular arrhythmia (VA). ECGi metrics, including activation time, repolarization time, activation-recovery interval, and voltage amplitude, were distinguishable between patients with ischemic cardiomyopathy, patients with a history of VA, and healthy controls.

Conclusion

ECGi allows non-invasive measurement of metrics which are associated with an increased risk of ventricular arrhythmias in patients with ischemic cardiomyopathy. ECGi may be a useful tool for risk assessment in these patients. Prospective studies are warranted for further validation and prediction of clinical endpoints.

Three-dimensional recovery time dispersion map by 64-channel magnetocardiography may demonstrate the location of a myocardial injury and heterogeneity of repolarization

BACKGROUND

QT dispersion reveals heterogeneities in the repolarization time in the three-dimensional (3D) structure of the ventricular myocardium. In this study, we report on a 3D function map of recovery time (RT) dispersions as measured by 64-channel magnetocardiography (MCG).

METHODS

MCG were simultaneously recorded in 29 controls and 21 patients with previous myocardial infarction (MI). The 3D current density was calculated from 64-channel MCG data in the Bz component using a space filter. The heart outline, reconstructed from the integrated the current density, revealed both the atrium and ventricle. The RT for the intervals between QRS onset and the time of the maximum dT/dt of T wave, and the peak to the end of the T wave (T(peak)-negative dT/dt) were automatically measured by means of a computer from 3D MCG data. The corrected RT (RTc) and corrected T(peak)-negative dT/dt were then calculated using Bazett's formula. The 3D RTc and the corrected T(peak)-negative dT/dt dispersion map were superimposed on the heart outline generated by MCG.

RESULTS

The RTc was significantly longer for the MI group than in the control group (67+/-25 ms1/2 vs. 16+/-6 ms1/2) (p<0.0001). The corrected T(peak)-negative dT/dt dispersions in each patient was also significantly longer for the MI group than in the control group (35+/-27 ms1/2 vs. 10+/-5 ms1/2) (p<0.0001). Furthermore, the 3D RTc and T(peak)-negative dT/dt dispersion maps corresponded with the space location of MI, as defined by Tc-99m tetrofosmin myocardial imaging

CONCLUSIONS

3D RTc and T(peak)-negative dT/dt dispersion maps in the ST segment, obtained by 64-channel MCG may be used demonstrate the location of a myocardial injury and heterogeneities of repolarization.

Imaging electrocardiographic dispersion of depolarization and repolarization during ischemia: simultaneous body surface and epicardial mapping

BACKGROUND

Myocardial ischemia creates abnormal electrophysiological substrates that result in life-threatening ventricular arrhythmias. Identifying patients at risk of such abnormalities by use of body surface electrical measures is controversial. We investigated the sensitivity of torso measures, recorded simultaneously with epicardial electrograms, to changes in dispersion of depolarization and repolarization during localized ventricular ischemia.

METHODS AND RESULTS

Ventricular epicardial electrograms were recorded from 5 anesthetized pigs with a 127-electrode sock. A controllable suture snare was used to ligate the left anterior descending coronary artery (LAD). The chest was reclosed, and a vest with 256 ECG electrodes was fitted to the torso. Simultaneous arrays of epicardial electrograms and torso ECGs were recorded during LAD occlusion and reperfusion. Activation-recovery intervals (ARIs), QTu and RTu dispersion (where u indicates upstroke), and QRST integrals were calculated, and these data were fitted to anatomically customized computational models of the swine ventricular epicardium and torso. LAD occlusion caused the epicardial ARI dispersion to steadily increase, whereas the location of shortest ARI shifted from the posterobasal ventricular tissue (control) to the anteroapical myocardium, distal to the suture snare. These changes were associated with a steady increase in the torso RTu dispersion as the shortest RTu interval moved from the right shoulder (control) to the sternum. QTu and RTu dispersion determined from the 12-lead ECG did not consistently reflect the myocardial changes.

CONCLUSIONS

Although changes in myocardial repolarization dispersion resulting from localized ischemia are not reliably reflected in temporal indices derived from the 12-lead ECG, they can be readily identified with high-resolution torso ECG mapping.

Computer analysis of multichannel ECG

Multichannel electrocardiography (MECG) is an extension of the conventional electrocardiography that is aimed at refining the non-invasive characterisation of cardiac activity. Body surface mapping is a graphical presentation of cardiac activity as measured from the body surface. Body surface maps can show the distribution of the potential at a selected moment in time or over a specified time interval. A new family of maps, based on the characteristics derived from the complete analysed beat, is described. Some new computer supported methods, which are able to calculate automatically different temporal maps, are proposed. MECG measurements can be seen in this context as a powerful research and clinical tool for improving the resolution of cardiac measurements.