The dominant T wave

Basis and applicability of noninvasive inverse electrocardiography: a comparison between cardiac source models

The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the inverse problem of electrocardiography. The method to solve the inverse problem depends on the chosen cardiac source model to describe cardiac electrical activity. In this paper, we describe the theoretical basis of two inverse methods based on the most commonly used cardiac source models: the epicardial potential model and the equivalent dipole layer model. We discuss similarities and differences in applicability, strengths and weaknesses and sketch a road towards improved inverse solutions by targeted use, sequential application or a combination of the two methods.

Novel non-invasive ECG imaging method based on the 12-lead ECG for reconstruction of ventricular activation: A proof-of-concept study

Aim

Current non-invasive electrocardiographic imaging (ECGi) methods are often based on complex body surface potential mapping, limiting the clinical applicability. The aim of this pilot study was to evaluate the ability of a novel non-invasive ECGi method, based on the standard 12-lead ECG, to localize initial site of ventricular activation in right ventricular (RV) paced patients. Validation of the method was performed by comparing the ECGi reconstructed earliest site of activation against the true RV pacing site determined from cardiac computed tomography (CT).

Methods

This was a retrospective study using data from 34 patients, previously implanted with a dual chamber pacemaker due to advanced atrioventricular block. True RV lead position was determined from analysis of a post-implant cardiac CT scan. The ECGi method was based on an inverse-ECG algorithm applying electrophysiological rules. The algorithm integrated information from an RV paced 12-lead ECG together with a CT-derived patient-specific heart-thorax geometric model to reconstruct a 3D electrical ventricular activation map.

Results

The mean geodesic localization error (LE) between the ECGi reconstructed initial site of activation and the RV lead insertion site determined from CT was 13.9 ± 5.6 mm. The mean RV endocardial surface area was 146.0 ± 30.0 cm² and the mean circular LE area was 7.0 ± 5.2 cm² resulting in a relative LE of 5.0 ± 4.0%.

Conclusion

We demonstrated a novel non-invasive ECGi method, based on the 12-lead ECG, that accurately localized the RV pacing site in relation to the ventricular anatomy.

Feasibility study of a 3D camera to reduce electrode repositioning errors during longitudinal ECG acquisition

INTRODUCTION

Longitudinal monitoring of sometimes subtle waveform changes of the 12‑lead electrocardiogram (ECG) is complicated by patient-specific and technical factors, such as the inaccuracy of electrode repositioning. This feasibility study uses a 3D camera to reduce electrode repositioning errors, reduce ECG waveform variability and enable detailed longitudinal ECG monitoring.

METHODS

Per subject, three clinical ECGs were obtained during routine clinical follow-up. Additionally, two ECGs were recorded guided by two 3D cameras, which were used to capture the precordial electrode locations and direct electrode repositioning. ECG waveforms and parameters were quantitatively compared between 3D camera guided ECGs and clinical ECGs. Euclidian distances between original and repositioned precordial electrodes from 3D guided ECGs were measured.

RESULTS

Twenty subjects (mean age 65.1 ± 8.2 years, 35% females) were included. The ECG waveform variation between routine ECGs was significantly higher compared to 3D guided ECGs, for both the QRS complex (correlation coefficient = 0.90 vs 0.98, p < 0.001) and the STT segment (correlation coefficient = 0.88 vs. 0.96, p < 0.001). QTc interval variation was reduced for 3D camera guided ECGs compared to routine clinical ECGs (5.6 ms vs. 9.6 ms, p = 0.030). The median distance between 3D guided repositioned electrodes was 10.0 [6.4-15.2] mm, and did differ between males and females (p = 0.076).

CONCLUSIONS

3D guided repositioning of precordial electrodes resulted in, a low repositioning error, higher agreement between waveforms of consecutive ECGs and a reduction of QTc variation. These findings suggest that longitudinal monitoring of disease progression using 12‑lead ECG waveforms is feasible in clinical practice.

Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads

Electrocardiographic (ECG) T-wave endpoint (T_end) identification suffers lack of reliability due to the presence of noise and variability among leads. T_end identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve T_end identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable T_end identification. To this aim T_end measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that T_end distributions have not statistically different median values (CHS: 340 ms vs. 340 ms, respectively; AMIP: 325 ms vs. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10^-27). Thus, measuring T_end from the 15-dependent-lead DTWs is statistically equivalent to measuring T_end from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic T_end identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the T_end determination from 15 dependent lead DTWs.

A new algorithm for estimating the ν-index using sinusoidal basis functions

Recently it was shown that the spatial dispersion of ventricular repolarization (SHVR) can be assessed from the surface ECG using a metric termed ν-index. In this paper, a new algorithm is presented for estimating the ν-index, allowing the inclusion of higher order terms with ease, even in the presence of noise, leading to more accurate estimates. We first introduced a new analytical model for the derivative of the average transmembrane potentials during repolarization (the dominant T-wave) based on trigonometric functions. This functional set is closed under the operation of derivation. Therefore, the nonlinear iterative optimization required by previous methods is no longer necessary. Then, we suggested an iterative linear matrix factorization method to properly estimate the leads factors and the ν-index. Several synthetic SHVR (in the range 20 to 70 ms) were simulated, employing a publicly-available forward electrophysiological model (ECGSIM), leading to a total of 240 synthetic 8-lead electrocardiographical recordings (ECG), each composed of 128 beats. Then the ν-index was estimated with the newly introduced method and compared (root mean square error, RMSE) with the theoretical values, available for each series. The simulation results confirmed the theoretical expectations and indeed showed that the ν-index estimates were improved by increasing the number of lead factors included (RMSE=0:295±0:037 vs 0:280±0:038 for 2 and 8 lead factors respectively).

Use of the dominant T wave to enhance reliability of T-wave offset identification

T-wave offset (Toff) identification may be jeopardized by the presence of a significant inter-method (IMV) and inter-lead (ILV) Toff variability. Thus, the aim of the present study was to investigate if the dominant T wave (DTW) may be used to enhance Toff-identification reliability. DTWs and 15-lead ECG T waves of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were analyzed for Toff identification using Zhang et al.'s (M1) and Daskalov and Christov's (M2) methods. Results indicate that IMV is significantly reduced when identifying Toff from the DTW rather than from single ECG leads in both populations (CHS: 5ms vs. 5-15ms; AMIP: 10ms vs. 10-20ms). Moreover, when analyzing ILV, Toff was found to be equivalent (correlation=0.71-0.98; P<10(-14)) to the median Toff among leads, but required only one identification instead of 15. Thus, the DTW can be used to enhance Toff-identification reliability.

Some theoretical results on the observability of repolarization heterogeneity on surface ECG

Assessing repolarization heterogeneity (RH) from surface ECG recording is an open issue in modern electrocardiography, despite the fact that several indexes measured on the T-wave have been proposed and tested. To understand how RH occurring at myocite level is reflected on T-wave shapes, in this paper we propose a mathematical framework that combines a simple statistical model of cardiac repolarization times with the dominant T-wave formalism. Within this framework we compare different T-wave features such as T-wave amplitude, T-wave amplitude variability or QT intervals and we describe mathematically how they are linked to the spatial and temporal components of repolarization heterogeneity.

Amplitude of Dominant T-Wave Alternans assessment on ECGs obtained from a biophysical model

The Amplitude of Dominant T-Wave Alternans (ADTWA) is a recently introduced index which quantifies the presence of microvolt T Wave Alternans (TWA) on surface ECG recordings. In this paper we investigate the reliability of ADTWA and its robustness against broadband noise. At this regard, we generated synthetic 12-leads ECG recordings through a forward electrophysiological model and we added TWA, at different extent, by modulating the variation of the repolarization times of transmembrane action potentials across even and odd beats. Using a stochastic model, we derived an analytical relationship between the repolarization variation injected into the model and TWA at the surface, thus offering a strategy to evaluate lead sensitivity. In terms of robustness, the results of the simulations show that ADTWA correctly measured the amplitude of synthetic TWA with an average error of 3.3% ± 5.8% in absence of noise. When a 100 μV peak-to-peak broadband noise is present, its effects on estimation errors were kept limited by singular value decomposition on which ADTWA builds.

Non-invasive imaging of cardiac activation and recovery

The sequences of activation and recovery of the heart have physiological and clinical relevance. We report on progress made over the last years in the method that images these timings based on an equivalent double layer on the myocardial surface serving as the equivalent source of cardiac activity, with local transmembrane potentials (TMP) acting as their strength. The TMP wave forms were described analytically by timing parameters, found by minimizing the difference between observed body surface potentials and those based on the source description. The parameter estimation procedure involved is non-linear, and consequently requires the specification of initial estimates of its solution. Those of the timing of depolarization were based on the fastest route algorithm, taking into account properties of anisotropic propagation inside the myocardium. Those of recovery were based on electrotonic effects. Body surface potentials and individual geometry were recorded on: a healthy subject, a WPW patient and a Brugada patient during an Ajmaline provocation test. In all three cases, the inversely estimated timing agreed entirely with available physiological knowledge. The improvements to the inverse procedure made are attributed to our use of initial estimates based on the general electrophysiology of propagation. The quality of the results and the required computation time permit the application of this inverse procedure in a clinical setting.

Non-invasive imaging of cardiac activation and recovery

The sequences of activation and recovery of the heart have physiological and clinical relevance. We report on progress made over the last years in the method that images these timings based on an equivalent double layer on the myocardial surface serving as the equivalent source of cardiac activity, with local transmembrane potentials (TMP) acting as their strength. The TMP wave forms were described analytically by timing parameters, found by minimizing the difference between observed body surface potentials and those based on the source description. The parameter estimation procedure involved is non-linear, and consequently requires the specification of initial estimates of its solution. Those of the timing of depolarization were based on the fastest route algorithm, taking into account properties of anisotropic propagation inside the myocardium. Those of recovery were based on electrotonic effects. Body surface potentials and individual geometry were recorded on: a healthy subject, a WPW patient and a Brugada patient during an Ajmaline provocation test. In all three cases, the inversely estimated timing agreed entirely with available physiological knowledge. The improvements to the inverse procedure made are attributed to our use of initial estimates based on the general electrophysiology of propagation. The quality of the results and the required computation time permit the application of this inverse procedure in a clinical setting.

Adaptive singular value cancelation of ventricular activity in single-lead atrial fibrillation electrocardiograms

The proper analysis and characterization of atrial fibrillation (AF) from surface electrocardiographic (ECG) recordings requires to cancel out the ventricular activity (VA), which is composed of the QRS complex and the T wave. Historically, for single-lead ECGs, the averaged beat subtraction (ABS) has been the most widely used technique. However, this method is very sensitive to QRST wave variations and, moreover, high-quality cancelation templates may be difficult to obtain when only short length and single-lead recordings are available. In order to overcome these limitations, a new QRST cancelation method based on adaptive singular value cancelation (ASVC) applied to each single beat is proposed. In addition, an exhaustive study about the optimal set of complexes for better cancelation of every beat is also presented for the first time. The whole study has been carried out with both simulated and real AF signals. For simulated AF, the cancelation performance was evaluated making use of a cross-correlation index and the normalized mean square error (nmse) between the estimated and the original atrial activity (AA). For real AF signals, two additional new parameters were proposed. First, the ventricular residue (VR) index estimated the presence of ventricular activity in the extracted AA. Second, the similarity (S) evaluated how the algorithm preserved the AA segments out of the QRST interval. Results indicated that for simulated AF signals, mean correlation, nmse, VR and S values were 0.945 +/- 0.024, 0.332 +/- 0.073, 1.552 +/- 0.386 and 0.986 +/- 0.012, respectively, for the ASVC method and 0.866 +/- 0.042, 0.424 +/- 0.120, 2.161 +/- 0.564 and 0.922 +/- 0.051 for ABS. In the case of real signals, the mean VR and S values were 1.725 +/- 0.826 and 0.983 +/- 0.038, respectively, for ASVC and 3.159 +/- 1.097 and 0.951 +/- 0.049 for ABS. Thus, ASVC provides a more accurate beat-to-beat ventricular QRST representation than traditional techniques. As a consequence, VA cancelation is optimized and the AA can be extracted more precisely. Finally, the study has proven that optimal VA cancelation is achieved when a number between 20 and 30 complexes is selected following a correlation-based strategy.