Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves

Abstract

Abstract-Objective: We propose two electrocardiogram (ECG)-derived markers of T-wave morphological variability in the temporal, dw, and amplitude, da, domains. Two additional markers, d NL w and d NL a , restricted to measure the non-linear information present within dw and da are also proposed. Methods: We evaluated the accuracy of the proposed markers in capturing T-wave time and amplitude variations in 3 situations: (1) In a simulated set up with presence of additive Laplacian noise, (2) when modifying the spatio-temporal distribution of electrical repolarization with an electro-physiological cardiac model and (3) in ECG records from healthy subjects undergoing a tilt table test. Results: The metrics dw, da, d NL w and d NL a followed T-wave time and amplitude induced variations under different levels of noise, were strongly associated with changes in the spatiotemporal dispersion of repolarization, and showed to provide additional information to differences in the heart rate, QT and Tpe intervals, and in the T-wave width and amplitude. Conclusion: The proposed ECG-derived markers robustly quantify T-wave morphological variability, being strongly associated with changes in the dispersion of repolarization. Significance: The proposed ECG-derived markers can help to quantify the variability in the dispersion of ventricular repolarization, showing a great potential to be used as arrhythmic risk predictors in clinical situations.

T‐Wave Morphology Restitution Predicts Sudden Cardiac Death in Patients With Chronic Heart Failure

“…Next, the 2 most distant RRI bins from the median RRI, distributed symmetrically around this median RRI (Figure B, green bin), were chosen as those defining the maximum intrasubject RRI range, ΔRRI (Figure B, blue and red bins, respectively), ie, ΔRRI=RRI 2 −RRI 1 . Representative T‐waves. Two T‐waves representative of the average T‐wave morphology for RRI 1 and RRI 2 were computed using a warping method recently described by our group . According to our hypothesis, these 2 T‐waves, called mean warped T‐waves, capture information regarding the dispersion of repolarization at RRI 1 and RRI 2 . Quantification of T‐wave morphological differences.…”

“…According to our hypothesis, these 2 T‐waves, called mean warped T‐waves, capture information regarding the dispersion of repolarization at RRI 1 and RRI 2 . Quantification of T‐wave morphological differences. The morphological differences between the 2 mean warped T‐waves were quantified using a previously defined index, d w . Figure .D1 shows both mean warped T‐waves, where their morphological difference can be appreciated.…”

“…We applied a recently developed methodology that quantifies the morphological differences between T‐waves to quantify T‐wave morphological change per RR increment. We called this index T‐wave morphology restitution (TMR), and we demonstrated its usefulness in the prediction of arrhythmic risk leading to SCD in chronic heart failure (CHF) patients.…”

T-wave Morphology Restitution Dependency with Heart Rate Range and Its Association with Sudden Cardiac Death in Chronic Heart Failure

“…2. Mean warped T-waves: The mean warped T-waves of the T-waves within RRI PI 1 (i) and RRI PI 2 (i) were calculated by time-warping as in [9]. Each mean warped T-waves is a representative of the average T-wave morphology at RRI PI 1 (i) and RRI PI 2 (i), and compensate for the possible morphological differences introduced by eventual different histories of RRIs [5].…”

“…Quantification of the T-wave morphological differences: The morphological differences between the i-th [9]. Before applying the methodology, the gravity centres of both mean warped T-waves were aligned to only account on changes in the T-wave morphology, and not on global shifts (see [9] for details). 4.…”