Abstract
Action potential duration restitution (APDR) curves present spatial variations due to the electrophysiological heterogeneities present in the heart. Enhanced spatial APDR dispersion in ventricle has been suggested as an arrhythmic risk marker. In this study, we propose a method to noninvasively quantify dispersion of APDR slopes at tissue level by making only use of the surface electrocardiogram (ECG). The proposed estimate accounts for rate normalized differences in the steady-state T-wave peak to T-wave end interval (T(pe)). A methodology is developed for its computation, which includes compensation for the T(pe) memory lag after heart-rate (HR) changes. The capability of the proposed estimate to reflect APDR dispersion is assessed using a combination of ECG signal processing, and computational modeling and simulation. Specifically, ECG recordings of control subjects undergoing a tilt test trial are used to measure that estimate, while its capability to provide a quantification of APDR dispersion at tissue level is assessed by using a 2-D ventricular tissue simulation. From this simulation, APDR dispersion, denoted as ∆α(SIM), is calculated, and pseudo-ECGs are derived. Estimates of APDR dispersion measured from the pseudo-ECGs show to correlate with ∆α(SIM), being the mean relative error below 5%. A comparison of the ECG estimates obtained from tilt test recordings and the ∆α(SIM) values measured in silico simulations at tissue level show that differences between them are below 20 % , which is within physiological variability limits. Our results provide evidence that the proposed estimate is a noninvasive measurement of APDR dispersion in ventricle. Additional results from this study confirm that T(pe) adapts to HR changes much faster than the QT interval.
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