The abnormal amplification of ventricular repolarization dispersion (VRD) has long been linked to proarrhythmia risk. Recently, the measure of VRD through electrocardiogram intervals has been strongly questioned. The search for an efficient and non-invasive surrogate marker of drug-induced dispersion effects constitute an urgent research challenge.
Herein, drug-induced ventricular dispersion is generated by d-Sotalol supply in an In-vitro rabbit heart model. A cilindrical chamber simulates the thorax and a multi-electrode net is used to obtain spatial electrocardiographic signals. Cardiac vector dynamics is captured by novel velocity cardiomarkers obtained by quaternion methods. Through statistical analysis and machine learning technics, we compute potential dispersion markers that could define proarrhythmic risk.
The cardiomarkers with the greatest statistical significance, both obtained from the electrical cardiac vector, were: the QTω, which is the difference between first and last maxima of angular velocity and λ21vT, the roundness of linear velocity. When comparing with the performance of the current standards (89%), this pair was able to correctly separate 21 out of 22 experiments achieving a performance of 95%. Moreover, the QTω computes in a much more robust basis the QT interval, the current index for drug regulation.
These velocity markers circumvent the problems of accuratelly finding the fiducial points such as the always tricky T-wave end. Given the high performance they achieved, it is provided a promising outcome for future applications to the detection of anomalous changes of heterogeneity that may be useful for the purposes of torsadogenic toxicity studies.