Study of repolarization heterogeneity and electrocardiographic morphology with a modeling approach

Increase of heart repolarization heterogeneity has been linked to severe or even life-threatening arrhythmia like torsades de pointes and other forms of ventricular tachycardia. Although electrocardiography (ECG) still remains as the most convenient and cost-effective method of monitoring electrical activity of the heart, the link between ECG morphology and repolarization heterogeneity is not clear. Previous attempts of using QT interval dispersion from multiple leads to assess the heterogeneity changes were not successful either.

The aim of this study is to use a cell-to-ECG model to study ECG morphology changes while varying transmural heterogeneity. The heterogeneity is simulated by increasing the difference of M cell Ikr block factors from either endocardial or epicardial cells. The model-simulated ECGs were processed and measured. The ECG parameters studied include QT interval dispersion of standard 12-lead ECG, QT peak dispersion, and T-peak to T-end interval (TpTe). An ECG vector magnitude signal based on 12-lead ECG was formed to estimate the global QT interval (vs lead-by-lead QT interval used for calculating QT dispersion) and also the global TpTe (TpTe_VM).

The results based on the model simulation show that the TpTe_VM is highly correlated with transmural dispersion of repolarization (TDR), with a correlation coefficient of 0.97. The correlation coefficients of QT interval dispersion and QT peak dispersion with TDR are 0.44 and 0.80, respectively.

In conclusion, the cell-to-ECG model provides a unique way to study electrophysiology and to link physiologic factors to ECG morphology changes. The simulation results suggest that global TpTe can be a strong indicator of TDR.