Methodological principles of T wave alternans analysis: a unified framework

Crescendo in depolarization and repolarization heterogeneity heralds development of ventricular tachycardia in hospitalized patients with decompensated heart failure

BACKGROUND

A critical need exists for reliable warning markers of in-hospital life-threatening arrhythmias. We used a new quantitative method to track interlead heterogeneity of depolarization and repolarization to detect premonitory changes before ventricular tachycardia (VT) in hospitalized patients with acute decompensated heart failure.

METHODS AND RESULTS

Ambulatory ECGs (leads V(1), V(5), and aVF) recorded before initiation of drug therapy from patients enrolled in the PRECEDENT (Prospective Randomized Evaluation of Cardiac Ectopy with Dobutamine or Nesiritide Therapy) trial were analyzed. R-wave heterogeneity (RWH) and T-wave heterogeneity (TWH) were assessed by second central moment analysis and T-wave alternans (TWA) by modified moving average analysis. Of 44 patients studied, 22 had experienced episodes of VT (≥4 beats at heart rates >100 beats/min) following ≥120 minutes of stable sinus rhythm, and 22 were age- and sex-matched patients without VT. TWA increased from 18.6±2.1 μV (baseline, mean±SEM) to 27.9±4.6 μV in lead V(5) at 15 to 30 minutes before VT (P<0.05) and remained elevated until the arrhythmia occurred. TWA results in leads V(1) and aVF were similar. RWH and TWH were elevated from 164.1±33.1 and 134.5±20.6 μV (baseline) to 299.8±54.5 and 239.2±37.0 μV at 30 to 45 minutes before VT (P<0.05), respectively, preceding the crescendo in TWA by 15 minutes. Matched patients without VT did not display elevated RWH (185.5±29.4 μV) or TWH (157.1±27.2 μV) during the 24-hour period.

CONCLUSIONS

This investigation is the first clinical demonstration of the potential utility of tracking depolarization and repolarization heterogeneity to detect crescendos in electrical instability that could forewarn of impending nonsustained VT. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00270400.

Allelic variant of NOS1AP effects on cardiac alternans of repolarization during exercise testing

INTRODUCTION

A repolarization abnormality manifested as T-wave alternans (TWA) in electrocardiogram (ECG) predicts cardiovascular mortality. A common variant in the NOS1AP gene is associated with mortality and QT interval duration, possibly in a gender-specific manner, but data is lacking on potential association with TWA. This study tested association between rs10494366 in NOS1AP and both TWA and 4-year mortality.

MATERIAL AND METHODS

A total of 1963 Finnish Cardiovascular Study participants (36.6% female, 57.1 ± 13.0 years) were genotyped and their maximal TWA values were measured from continuous ECG recordings during clinical exercise test at rest, exercise and recovery.

RESULTS

We observed a significant gender-specific effect of NOS1AP genotype on TWA. In all subjects, there was no statistically significant difference between the three genotypes (TT, TG, GG) in the responses of TWA over the entire exercise test (time-by-genotype interaction p = 0.057). In women, after adjustment for age, coronary heart disease and β-blocker medication status, changes of TWA over different phases of exercise test were significantly associated with NOS1AP genotype (time-by-genotype interaction p = 0.001). In men, NOS1AP rs10494366 was not associated with TWA. During follow-up (mean 47 months), 113 patients died. NOS1AP rs10494366 was not a statistically significant predictor of mortality.

CONCLUSION

The NOSIAP variant rs10494366 influences TWA and TWA response during clinical exercise test in females. Gender-specific effects have also been previously reported for the influence of the variant on QT interval. If replicated, these findings should prompt studies to further elucidate the mechanisms underlying the gender differences in NOS1AP effects on repolarization.

Microvolt T-wave alternans physiological basis, methods of measurement, and clinical utility--consensus guideline by International Society for Holter and Noninvasive Electrocardiology

This consensus guideline was prepared on behalf of the International Society for Holter and Noninvasive Electrocardiology and is cosponsored by the Japanese Circulation Society, the Computers in Cardiology Working Group on e-Cardiology of the European Society of Cardiology, and the European Cardiac Arrhythmia Society. It discusses the electrocardiographic phenomenon of T-wave alternans (TWA) (i.e., a beat-to-beat alternation in the morphology and amplitude of the ST-segment or T-wave). This statement focuses on its physiological basis and measurement technologies and its clinical utility in stratifying risk for life-threatening ventricular arrhythmias. Signal processing techniques including the frequency-domain Spectral Method and the time-domain Modified Moving Average method have demonstrated the utility of TWA in arrhythmia risk stratification in prospective studies in >12,000 patients. The majority of exercise-based studies using both methods have reported high relative risks for cardiovascular mortality and for sudden cardiac death in patients with preserved as well as depressed left ventricular ejection fraction. Studies with ambulatory electrocardiogram-based TWA analysis with Modified Moving Average method have yielded significant predictive capacity. However, negative studies with the Spectral Method have also appeared, including 2 interventional studies in patients with implantable defibrillators. Meta-analyses have been performed to gain insights into this issue. Frontiers of TWA research include use in arrhythmia risk stratification of individuals with preserved ejection fraction, improvements in predictivity with quantitative analysis, and utility in guiding medical as well as device-based therapy. Overall, although TWA appears to be a useful marker of risk for arrhythmic and cardiovascular death, there is as yet no definitive evidence that it can guide therapy.

Repolarization alternans heterogeneity in healthy subjects and acute myocardial infarction patients

An association between heterogeneity of repolarization alternans (RA) and cardiac electrical instability has been reported. Characterization of RA in health and identification of physiological RA heterogeneity may help discrimination of abnormal RA cases more likely associated to arrhythmic events. Thus, aim of the present study was the identification of a physiological RA region in terms of mean temporal location (MRAD) with respect to the T apex, and mean amplitude (MRAA), by application of our heart-rate adaptive match filter method to clinical ECG recordings from 51 control healthy (CH) subjects and 43 acute myocardial infarction (AMI) patients. Results indicate that RA occurring within the first half of the T wave is dominant in both CH and AMI populations (74.5% and 53.5% of cases, respectively; P<0.05). Definition of physiological RA region in the MRAD vs. MRAA plane (-83 ms ≤ MRAD ≤ 23 ms, 0≤ MRAA ≤ 30 μV) provided 0% and 32.6% abnormal RA cases among the CH subjects and AMI patients, respectively. We conclude that myocardial infarction may associate with an RA occurring early (MRAD<-83 ms) or late (MRAD >23 ms) along the JT segment, in addition or in alternative to an abnormally high RA amplitude (MRAA >30 μV).

A nonparametric surrogate-based test of significance for T-wave alternans detection

We present a nonparametric adaptive surrogate test that allows for the differentiation of statistically significant T-wave alternans (TWA) from alternating patterns that can be solely explained by the statistics of noise. The proposed test is based on estimating the distribution of noise-induced alternating patterns in a beat sequence from a set of surrogate data derived from repeated reshuffling of the original beat sequence. Thus, in assessing the significance of the observed alternating patterns in the data, no assumptions are made about the underlying noise distribution. In addition, since the distribution of noise-induced alternans magnitudes is calculated separately for each sequence of beats within the analysis window, the method is robust to data nonstationarities in both noise and TWA. The proposed surrogate method for rejecting noise was compared to the standard noise-rejection methods used with the spectral method (SM) and the modified moving average (MMA) techniques. Using a previously described realistic multilead model of TWA and real physiological noise, we demonstrate the proposed approach that reduces false TWA detections while maintaining a lower missed TWA detection, compared with all the other methods tested. A simple averaging-based TWA estimation algorithm was coupled with the surrogate significance testing and was evaluated on three public databases: the Normal Sinus Rhythm Database, the Chronic Heart Failure Database, and the Sudden Cardiac Death Database. Differences in TWA amplitudes between each database were evaluated at matched heart rate (HR) intervals from 40 to 120 beats per minute (BPM). Using the two-sample Kolmogorov-Smirnov test, we found that significant differences in TWA levels exist between each patient group at all decades of HRs. The most-marked difference was generally found at higher HRs, and the new technique resulted in a larger margin of separability between patient populations than when the SM or MMA were applied to the same data.

Automatic microvolt T-wave alternans identification in relation to ECG interferences surviving preprocessing

The aim was to investigate the effect of interferences surviving preprocessing (residual noise, baseline wanderings, respiration modulation, replaced beats, missed beats and T-waves misalignment) on automatic identification of T-wave alternans (TWA), an ECG index of risk for sudden cardiac death. The procedures denominated fast-Fourier-transform spectral method (FFTSM), complex-demodulation method (CDM), modified-moving-average method (MMAM), Laplacian-likelihood-ratio method (LLRM), and adaptive-match-filter method (AMFM) were applied to interferences-corrupted synthetic ECG tracings and Holter ECG recordings from control-healthy subjects (CH-group; n=25) and acute-myocardial-infarction patients (AMI group; n=25). The presence of interferences in simulated data caused detection of false-positive TWA by all techniques but the FFTSM and AMFM. Clinical applications evidenced a discrepancy in that the FFTSM and LLRM detected no more than one TWA case in each population, whereas the CDM, MMAM, and AMFM detected TWA in all CH-subjects and AMI-patients, with significantly lower TWA amplitude in the former group. Because the AMFM is not prone to false-positive TWA detections, the latter finding suggests TWA as a phenomenon having continuously changing amplitude from physiological to pathological conditions. Only occasional detection of TWA by the FFTSM and LLRM in clinics can be ascribed to their limited ability in identifying TWA in the presence of interferences surviving preprocessing.

T wave alternans evaluation using adaptive time-frequency signal analysis and non-negative matrix factorization

Each year 400,000 North Americans die from sudden cardiac death (SCD). Identifying those patients at risk of SCD remains a formidable challenge. T wave alternans (TWA) evaluation is emerging as an important tool to risk stratify patients with heart diseases. TWA is a heart rate dependent phenomenon that manifests on the surface electrocardiogram (ECG) as a change in the shape or amplitude of the T wave every second heart beat. The presence of large magnitude TWA often presages lethal ventricular arrhythmias. Because the TWA signal is typically in the microvolt range, accurate detection algorithms are required to control for confounding noise and changing physiological conditions (i.e. data nonstationarity). In this study, we address the limitations of two common TWA estimation methods, spectral method (SM) and modified moving average (MMA). To overcome their limitations, we propose a modified TWA quantification framework, called Adaptive SM, that uses non-linear time-frequency distribution (TFD). In order to increase the robustness of TWA detection in ambulatory ECGs, we also propose a new technique, called non-negative matrix factorization (NMF)-Adaptive SM. We present the analytical background of these methods, and evaluate their accuracy in detecting synthetic TWA signal in simulated and real-world ambulatory ECG recordings under conditions of noise and data non-stationarity. The results of the numerical simulations support the effectiveness of the proposed approaches for TWA analysis, which may ultimately improve SCD risk assessment.

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.

T-wave alternans detection using a Bayesian approach and a Gibbs sampler

The problem of detecting T-wave alternans (TWA) in ECG signals has received considerable attention in the biomedical community. This paper introduces a Bayesian model for the T waves contained in ECG signals. A block Gibbs sampler was recently studied to estimate the parameters of this Bayesian model (including wave locations, amplitudes and shapes). This paper shows that the samples generated by this Gibbs sampler can be used efficiently for TWA detection via different statistical tests constructed from odd and even T-wave amplitude samples. The proposed algorithm is evaluated on real ECG signals subjected to synthetic TWA and compared with two classical algorithms.

P- and T-wave delineation in ECG signals using a Bayesian approach and a partially collapsed Gibbs sampler

Detection and delineation of P- and T-waves are important issues in the analysis and interpretation of electrocardiogram (ECG) signals. This paper addresses this problem by using Bayesian inference to represent a priori relationships among ECG wave components. Based on the recently introduced partially collapsed Gibbs sampler principle, the wave delineation and estimation are conducted simultaneously by using a Bayesian algorithm combined with a Markov chain Monte Carlo method. This method exploits the strong local dependency of ECG signals. The proposed strategy is evaluated on the annotated QT database and compared to other classical algorithms. An important feature of this paper is that it allows not only for the detection of P- and T-wave peaks and boundaries, but also for the accurate estimation of waveforms for each analysis window. This can be useful for some ECG analysis that require wave morphology information.

Microvolt T-wave alternant: pathomechanism and evaluation of a new marker of arrhythmia risk

A mikrovolt T-hullám-alternáns, angolul microvolt T-wave alternant (µV-TWA), a T-hullám amplitúdójának ütésről ütésre történő mikrovoltszinten mérhető váltakozása. Mivel ez a változás igen kicsi, csak finom, érzékeny digitális jelfeldolgozó technikával mérhető. Jelenlegi álláspont szerint a µV-TWA megjelenése előre jelezheti a letális, malignus kamrai tachyarrythmiák kialakulásának valószínűségét, a hirtelen szívhalál bekövetkeztét. Az elmúlt tíz évben experimentális és klinikai vizsgálatok próbálták magyarázni a µV-TWA kialakulásának patomechanizmusát és a mögöttes sejtszintű folyamatokat. Azonban a mai napig nem sikerült a µV-TWA-t kialakító celluláris folyamatokat megfelelően tisztázni. Összefoglaló tanulmányunkban áttekintjük azokat a témával foglalkozó közleményeket, amelyek a folyamatban szerepet játszó akciós potenciál repolarizációjában fontosak voltak és áttörést jelentettek az elmúlt években. Részletezzük az akciós potenciál és ionáram-fluktuáció, a citoplazmatikus kalciumkoncentráció-szabályozás, a béta-adrenerg receptorok, valamint a connexinek szerepét a µV-TWA és a következményes kamrai tachyarrhythmiák kialakításában. Ismertetjük továbbá a µV-TWA detektálására jelenleg alkalmazott technikákat, azok felhasználási lehetőségeit a hirtelen szívhalál veszélyeztetettségének felmérésében.

Nonlinear trend estimation of the ventricular repolarization segment for T-wave alternans detection

Repolarization alternans or T-wave alternans (TWA) is a subject of great interest as it has been shown as a risk stratifier for sudden cardiac death. As TWA consists of subtle and nonvisible variations of the ST-T complex, its detection may become more difficult in noisy environments, such as stress testing or Holter recordings. In this paper, a technique based on the empirical-mode decomposition (EMD) to separate the useful information of the ST-T complex from noise and artifacts is proposed. The identification of the useful part of the signal is based on the study of complexity in the EMD domain by means of the Hjorth descriptors. As a result, a robust technique to extract the trend of the ST-T complex has been achieved. The evaluation of the method is carried out with the spectral method (SM) over several public domain databases with ECGs sampled at different frequencies. The results show that the SM with the proposed technique outperforms the traditional SM by more than 2 dB. Also, the robustness of this technique is guaranteed as it does not introduce any additional distortion to the detector in noiseless conditions.

A multilead scheme based on periodic component analysis for T-wave alternans analysis in the ECG

T-wave alternans (TWA) is a cardiac phenomenon that appears in the electrocardiogram (ECG) and is associated with the mechanisms leading to sudden cardiac death (SCD). In this study, we propose the use of a multilead TWA analysis scheme that combines the Laplacian likelihood ratio (LLR) method and periodic component analysis (piCA), an eigenvalue decomposition technique whose aim is to extract the most periodic sources of the signal. The proposed scheme is evaluated in different scenarios--from synthetic signals to stress test ECGs--and is compared to other reported schemes based on the LLR method. Results demonstrate that the piCA-based scheme provides a superior ability to detect TWA than previously reported schemes, and has the potential to improve the prognostic value of testing for TWA.

Adaptive time-frequency matrix features for T wave alternans analysis

T wave alternans (TWA) has been associated with ventricular arrhythmias. Hence, TWA detection can risk stratify patients with heart disease who may experience sudden death from ventricular arhythmias. However, accurate TWA detection is technically challenging due to the low microvolt TWA signal and the confounding effect of biological noise such as movement, myopotentials or respiration. In this paper, we propose nonnegative matrix factorization (NMF)-Adaptive spectral method to increase the robustness of TWA detection in ambulatory electrocardiograms (ECGs). The proposed method applies a non-linear time-frequency (TF) analysis and NMF to the aligned ST-T waveforms. This method separates the TWA signal from the other non-desired ECG signal components, and detects TWA with high accuracy. The performance of our proposed method is validated in a clinical study using ECGs which confirms a TWA detection of 92% compared to 47% using the conventional spectral method.

Correlation method versus enhanced modified moving average method for automatic detection of T-wave alternans

Enhanced modified moving average method (EMMAM) and correlation method (CM) for microvolt TWA identification are compared by aid of simulated ECG tracings (cases of absence of TWA and presence of stationary or time-varying TWA) and ECG recordings from healthy subjects (H-group) and patients who survived an acute myocardial infarction (AMI-group). The two competing methods were found to be equivalent when analyzing clean ECGs affected by stationary TWA. Non-stationary TWA is correctly tracked by the CM, whereas it is identified as stationary by the EMMAM. Moreover, the EMMAM suffers for its tendency to identify as TWA noise and other kinds of repolarization variability. Such limitation is most likely the cause of its false-positive TWA production. Finally, only the CM incorporates a local threshold criterion in the TWA detection algorithm which allows better discrimination between H and AMI groups, who are well known to be at increased risk to develop TWA.

Sleep apnoea induces cardiac electrical instability assessed by T-wave alternans in patients with congestive heart failure

AIMS

To assess the involvement of sleep apnoea in nocturnal sudden cardiac death (SCD) by evaluating cardiac electrical instability using T-wave alternans (TWA), a risk marker for lethal cardiac arrhythmias, and severity of sleep apnoea in congestive heart failure (CHF) patients.

METHODS AND RESULTS

A total of 40 CHF patients simultaneously underwent overnight simplified respiratory polygraphy and 24 h continuous electrocardiography. Peak TWA during both daytime and nighttime were calculated by the modified moving average method. The patients were divided into two groups; 30 patients with daytime predominant TWA (whose peak TWA was higher during daytime than during nighttime) and 10 with nighttime predominant. Apnoea-hypopnoea index (AHI) was significantly higher in patients with nighttime predominant TWA than in those with daytime predominant (35.9 +/- 8.1 vs. 23.9 +/- 14.4 events/h, P = 0.02), and was an independent predictor of nighttime predominant TWA (odds ratio, 1.08; 95% confidence interval, 1.01-1.16; P = 0.03). Moreover, peak TWA during the night was correlated positively with AHI (P < 0.001), and AHI was an independent determinant of nocturnal TWA value (r(2) = 0.27, P = 0.009).

CONCLUSION

In CHF patients, sleep apnoea induces cardiac electrical instability manifested as TWA, reflecting increased risk of nocturnal SCD. Moreover, some CHF patients with sleep apnoea exhibit nighttime predominant TWA. Therefore, TWA should also be evaluated during the night.

An artificial vector model for generating abnormal electrocardiographic rhythms

We present generalizations of our previously published artificial models for generating multi-channel ECG to provide simulations of abnormal cardiac rhythms. Using a three-dimensional vectorcardiogram (VCG) formulation, we generate the normal cardiac dipole for a patient using a sum of Gaussian kernels, fitted to real VCG recordings. Abnormal beats are specified either as perturbations to the normal dipole or as new dipole trajectories. Switching between normal and abnormal beat types is achieved using a first-order Markov chain. Probability transitions can be learned from real data or modeled by coupling to heart rate and sympathovagal balance. Natural morphology changes from beat-to-beat are incorporated by varying the angular frequency of the dipole as a function of the inter-beat (RR) interval. The RR interval time series is generated using our previously described model whereby time- and frequency-domain heart rate (HR) and heart rate variability characteristics can be specified. QT-HR hysteresis is simulated by coupling the Gaussian kernels associated with the T-wave in the model with a nonlinear factor related to the local HR (determined from the last n RR intervals). Morphology changes due to respiration are simulated by introducing a rotation matrix couple to the respiratory frequency. We demonstrate an example of the use of this model by simulating HR-dependent T-wave alternans (TWA) with and without phase-switching due to ectopy. Application of our model also reveals previously unreported effects of common TWA estimation methods.

Comparison of source separation techniques for multilead T-wave alternans detection in the ECG

T-wave alternans (TWA) is a cardiac phenomenon associated with the mechanisms leading to sudden cardiac death. In this work, we evaluate different source separation techniques for multilead detection of TWA in the electrocardiogram (ECG). Two periodicity-based techniques - periodic component analysis (πCA) and the newly proposed spectral ratio maximization (SRM) - are compared to two independence-based techniques - FastICA and JADE - and to principal component analysis (PCA). According to simulation results, the best detection performance is obtained with the periodicity-based schemes.

Adrenergic stimulation promotes T-wave alternans and arrhythmia inducibility in a TNF-alpha genetic mouse model of congestive heart failure

T-wave alternans (TWA) is a proarrhythmic repolarization instability that is common in congestive heart failure (CHF). Although transgenic mice are commonly used to study the mechanisms of arrhythmogenesis in CHF, little is known about the dynamics of TWA in these species. We hypothesized that TWA is present in a TNF-alpha model of CHF and can be further promoted by adrenergic stimulation. We studied 16 TNF-alpha mice and 12 FVB controls using 1) in vivo intracardiac electrophysiological testing and 2) ambulatory telemetry during 30 min before and after an intraperitoneal injection of isoproterenol. TWA was examined using both linear and nonlinear filtering applied in the time domain. In addition, changes in the mean amplitude of the T wave and area under the T wave were computed. During intracardiac electrophysiological testing, none of the animals had TWA or inducible arrhythmias before the injection of isoproterenol. After the injection, sustained TWA and inducible ventricular tachyarrhythmias were observed in TNF-alpha mice but not in FVB mice. In ambulatory telemetry, before the isoproterenol injection, the cardiac cycle length (CL) was longer in TNF-alpha mice than in FVB mice (98 +/- 9 and 88 +/- 3 ms, P = 0.04). After the injection of isoproterenol, the CL became 8% and 6% shorter in TNF-alpha and FVB mice (P < 10(-4)); however, the 2% difference between the groups in the magnitude of CL changes was not significant. In TNF-alpha mice, the magnitude of TWA was 1.5-2 times greater than in FVB mice both before and after the isoproterenol injection. The magnitude of TWA increased significantly after the isoproterenol injection compared with the baseline in TNF-alpha mice (P = 0.003) but not in FVB mice. The mean amplitude of the T wave and area under the T wave increased 60% and 80% in FVB mice (P = 0.006 and 0.009) but not in TNF-alpha mice. In conclusion, TWA is present in a TNF-alpha model of CHF and can be further promoted by adrenergic stimulation, along with the enhanced susceptibility for ventricular arrhythmias.

Comparative analysis of methods for automatic detection and quantification of microvolt T-wave alternans

Microvolt T-wave alternans (TWA), consisting of every-other-beat changes in ECG T-wave morphology, is an index of susceptibility to malignant ventricular arrhythmias, requiring automatic techniques to be identified. Five of these, namely, fast-Fourier-transform spectral method (FFTSM), complex-demodulation method (CDM), modified-moving-average method (MMAM), Laplacian-likelihood-ratio method (LLRM) and adaptive-match-filter method (AMFM), were applied here to simulated and sample clinical data. The aim was to compare individual methods ability to properly identify stationary and time-varying TWA, avoiding false-positive detections. The MMAM provided false-positive TWA when applied to simulated ECGs affected by amplitude variability, but TWA. Stationary TWA was properly quantified by the MMAM and, occasionally, underestimated by all other methods. The AMFM properly identified time-varying TWA. By contrast, the FFTSM detected not-stationary TWA as stationary, the MMAM introduced a time-delay in the estimated TWA-amplitude signal, while the CDM and LLRM were reliable only in the presence of slow-varying TWA. Altogether, the AMFM accomplished the best compromise between the needs to avoid false-positive TWA and to detect and characterize true-positive TWA. Results of our simulation approach were useful to explain different TWA levels measured by each competing methods applied to sample Holter ECGs from healthy subjects and coronary artery disease patients.

Comparison of quantitative T-wave alternans profiles of healthy subjects and ICD patients

BACKGROUND

Current relevance of T-wave alternans is based on its association with electrical disorder and elevated cardiac risk. Quantitative reports would improve understanding on TWA augmentation mechanisms during mental stress or prior to tachyarrhythmias. However, little information is available about quantitative TWA values in clinical populations. This study aims to create and compare TWA profiles of healthy subjects and ICD patients, evaluated on treadmill stress protocols.

METHODS

Apparently healthy subjects, not in use of any medication were recruited. All eligible ICD patients were capable of performing an attenuated stress test. TWA analysis was performed during a 15-lead treadmill test. The derived comparative profile consisted of TWA amplitude and its associated heart rate, at rest (baseline) and at peak TWA value. Chi-square or Mann-Whitney tests were used with p values < or = 0.05. Discriminatory performance was evaluated by a binary logistic regression model.

RESULTS

31 healthy subjects (8F, 23M) and 32 ICD patients (10F, 22M) were different on baseline TWA (1 +/- 2 microV; 8 +/- 9 muV; p < 0.001) and peak TWA values (26 +/- 13 microV; 37 +/- 20 microV; p = 0,009) as well as on baseline TWA heart rate (79 +/- 10 bpm; 67 +/- 15 bpm; p < 0.001) and peak TWA heart rate (118 +/- 8 bpm; 90 +/- 17 bpm; p < 0.001). The logistic model yielded sensitivity and specificity values of 88.9% and 92.9%, respectively.

CONCLUSIONS

Healthy subjects and ICD patients have distinct TWA profiles. The new TWA profile representation (in amplitude-heart rate pairs) may help comparison among different research protocols.

Detecting space-time alternating biological signals close to the bifurcation point

Time-alternating biological signals, i.e., alternans, arise in variety of physiological states marked by dynamic instabilities, e.g., period doubling. Normally, a sequence of large-small-large transients, they can exhibit variable patterns over time and space, including spatial discordance. Capture of the early formation of such alternating regions is challenging because of the spatiotemporal similarities between noise and the small-amplitude alternating signals close to the bifurcation point. We present a new approach for automatic detection of alternating signals in large noisy spatiotemporal datasets by exploiting quantitative measures of alternans evolution, e.g., temporal persistence, and by preserving phase information. The technique specifically targets low amplitude, relatively short alternating sequences and is validated by combinatorics-derived probabilities and empirical datasets with white noise. Using high-resolution optical mapping in live cardiomyocyte networks, exhibiting calcium alternans, we reveal for the first time early fine-scale alternans, close to the noise level, which are linked to the later formation of larger regions and evolution of spatially discordant alternans. This robust method aims at quantification and better understanding of the onset of cardiac arrhythmias and can be applied to general analysis of space-time alternating signals, including the vicinity of the bifurcation point.

T-wave alternans found in preventricular tachyarrhythmias in CCU patients using a wavelet transform-based methodology

Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. However, closer visual inspection of the data revealed this to be a likely false positive result.

Anger-induced T-wave alternans predicts future ventricular arrhythmias in patients with implantable cardioverter-defibrillators

OBJECTIVES

This study sought to determine whether T-wave alternans (TWA) induced by anger in a laboratory setting predicts future ventricular arrhythmias in patients with implantable cardioverter-defibrillators (ICDs).

BACKGROUND

Anger can precipitate spontaneous ventricular tachycardia/ventricular fibrillation and induce TWA. Whether anger-induced TWA predicts future arrhythmias is unknown.

METHODS

Sixty-two patients with ICDs underwent ambulatory electrocardiography during a mental stress protocol, 3 months after the ICD was implanted. T-wave alternans was analyzed using time-domain methods. After a > or =1 year follow-up, ICD stored data was reviewed to determine incidence of ICD-terminated ventricular tachycardia/ventricular fibrillation.

RESULTS

Patients with ICD-terminated arrhythmias during follow-up (n = 10) had higher TWA induced by anger, 13.2 microV (interquartile range [IQR] 9.3 to 16 microV), compared with those patients without future ventricular arrhythmias, 9.3 microV (IQR 7.5 to 11.5 microV, p < 0.01). Patients in the highest quartile of anger-induced TWA (>11.9 microV, n = 15) were more likely to experience arrhythmias by 1 year than those in the lower quartiles (33% vs. 4%) and during extended follow-up (40% vs. 9%, p < 0.01 for both). In multivariable regression controlling for ejection fraction, prior clinical arrhythmia, and wide QRS, anger-induced TWA remained a significant predictor of arrhythmia, with likelihood in the top quartile 10.8 times that of other patients (95% confidence interval: 1.6 to 113, p < 0.05).

CONCLUSIONS

Anger-induced TWA predicts future ventricular arrhythmias in patients with ICDs, suggesting that emotion-induced repolarization instability may be 1 mechanism linking stress and sudden death. Whether there is a clinical role for anger-induced TWA testing requires further study.

Multilead analysis of T-wave alternans in the ECG using principal component analysis

T-wave alternans (TWA) is a cardiac phenomenon associated with the mechanisms leading to sudden cardiac death. Several methods exist to automatically detect and estimate TWA in the ECG on a single-lead basis, and their main drawback is their poor sensitivity to low-amplitude TWA. In this paper, we propose a multilead analysis scheme to improve the detection and estimation of TWA. It combines principal component analysis with a single-lead method based on the generalized likelihood ratio test. The proposed scheme is evaluated and compared to a single-lead scheme by means of a simulation study, in which different types of simulated and physiological noise are considered under realistic conditions. Simulation results show that the multilead scheme can detect TWA with an SNR 30 dB lower and allows the estimation of TWA with an SNR 25 dB lower than the single-lead scheme. The two analysis schemes are also applied to stress test ECG records. Results show that the multilead scheme provides a higher detection power and that TWA detections obtained with this scheme are significantly different in healthy volunteers and ischemic patients, whereas they are not with the single-lead scheme.

T-wave alternans: reviewing the clinical performance, understanding limitations, characterizing methodologies

Accurate recognition of individuals at higher immediate risk of sudden cardiac death (SCD) is still an open question. The fortuitous nature of acute cardiovascular events just does not seem to fit the well-known model of ventricular tachycardia/fibrillation induction in a static arrhythmogenic substrate by a synchronous trigger. On the mechanism of SCD, a dynamical electrical instability would better explain the rarity of the simultaneous association of a correct trigger and an appropriate cardiac substrate. Several studies have been conducted trying to measure this cardiac electrical instability (or any valid surrogate) in an ECG beat stream. Among the current possible candidates we can number QT prolongation, QT dispersion, late potentials, T-wave alternans (TWA), and heart rate turbulence. This article reviews the particular role of TWA in the current cardiac risk stratification scenario. TWA findings are still heterogeneous, ranging from very good to nearly null prognostic performance depending on the clinical population observed and clinical protocol in use. To fill the current gaps in the TWA base of knowledge, practitioners, and researchers should better explore the technical features of the several technologies available for TWA evaluation and pay greater attention to the fact that TWA values are responsive to several factors other than medications. Information about the cellular and subcellular mechanisms of TWA is outside the scope of this article, but the reader is referred to some of the good papers available on this topic whenever this extra information could help the understanding of the concepts and facts covered herein.

Cardiac repolarization analysis using the surface electrocardiogram

Sudden cardiac death (SCD) is a challenging health problem in the western world. Analysis of cardiac repolarization from the electrocardiogram (ECG) provides valuable information for stratifying patients according to their risk of suffering from arrhythmic events that could end in SCD, as well as for assessing efficacy of antiarrhythmic therapies. In this paper, we start by exploring the cellular basis of ECG repolarization waveforms under both normal and pathological conditions. We then describe basic preprocessing steps that need to be accomplished on the ECG signal before extracting repolarization indices. A comprehensive review of techniques aimed to characterize spatial or temporal repolarization dispersion is provided, together with a summary of their usefulness for clinical risk stratification. Techniques that describe spatial dispersion of repolarization are based on either differences in repolarization duration or T-wave loop morphology. Techniques that evaluate temporal dispersion of repolarization include the analysis of QT interval adaptation to heart rate changes, QT interval and T-wave variability, and T-wave alternans.

Enhanced modified moving average analysis of T-wave alternans using a curve matching method: a simulation study

T-wave alternans (TWA) are beat-to-beat amplitude oscillations in the T-waves of electrocardiograms (ECGs). Numerous clinical studies have demonstrated the link between these oscillations and ventricular arrhythmias. Several methods have been developed in recent years to detect and quantify this important feature. Most methods estimate the amplitude differences between pairs of consecutive T-waves. One such method is known as modified moving average (MMA) analysis. The TWA magnitude is obtained by means of the maximum absolute difference of even and odd heartbeat series averages computed at T-waves or ST-T complexes. This method performs well for different levels of TWA, noise, and phase shifts, but it is sensitive to the alignment of the T-waves. In this paper we propose a preprocessing stage for the MMA method to ensure an optimal alignment of such averages. The alignment is performed by means of a continuous time warping technique. Our assessment study demonstrates the improved performance of the proposed algorithm.

An Open-Source Standard T-Wave Alternans Detector for Benchmarking

We describe an open source algorithm suite for T-Wave Alternans (TWA) detection and quantification. The software consists of Matlab implementations of the widely used Spectral Method and Modified Moving Average with libraries to read both WFDB and ASCII data under windows and Linux. The software suite can run in both batch mode and with a provided graphical user interface to aid waveform exploration. Our software suite was calibrated using an open source TWA model, described in a partner paper [1] by Clifford and Sameni. For the PhysioNet/CinC Challenge 2008 we obtained a score of 0.881 for the Spectral Method and 0.400 for the MMA method. However, our objective was not to provide the best TWA detector, but rather a basis for detailed discussion of algorithms.

An Artificial Multi-Channel Model for Generating Abnormal Electrocardiographic Rhythms

We present generalizations of our previously published artificial models for generating multi-channel ECG so that the simulation of abnormal rhythms is possible. Using a three-dimensional vectorcardiogram (VCG) formulation, we generate the normal cardiac dipole for a patient using a sum of Gaussian kernels, fitted to real VCG recordings. Abnormal beats are then specified either as new dipoles, or as perturbations of the existing dipole. Switching between normal and abnormal beat types is achieved using a hidden Markov model (HMM). Probability transitions can be learned from real data or modeled by coupling to heart rate and sympathovagal balance. Natural morphology changes form beat-to-beat are incorporated as before from varying the angular frequency of the dipole as a function of the inter-beat (RR) interval. The RR interval time series is generated using our previously described model whereby time-and frequency-domain heart rate (HR) and heart rate variability (HRV) characteristics can be specified. QT-HR hysteresis is simulated by coupling the Gaussian kernels associated with the T-wave in the model with a nonlinear factor related to the local HR (determined from the last n RR intervals). Morphology changes due to respiration are simulated by coupling the RR interval to the angular frequency of the dipole. We demonstrate an example of the use of this model by simulating T-Wave Alternans (TWA). The magnitude of the TWA effect is modeled as a disturbance on the T-loop of the dipole with a magnitude that differs in each of the three VCG planes. The effect is then turned on or off using a HMM. The values of the transition matrix are determined by the local heart rate, such that when the HR ramps up towards 100 BPM, the probability of observing a TWA effect rapidly but smoothly increases. In this way, no 'sudden' switching from non-TWA to TWA is observed, and the natural tendency for TWA to be associated with a critical HR-related activation level is simulated. Finally, to generate multi-lead signals, the VCG is mapped to any set of clinical leads using a Dower-like transform derived from a least-squares optimization between known VCGs and known lead morphologies. ECGs with calibrated amounts of TWA were generated by this model and included in the PhysioNet/CinC Challenge 2008 data set.

T-wave alternans analysis improvement by means of curve alignment prior to distance calculation

Tracking of repolarization instabilities in the ECG, such as T-wave alternans (TWA), has become a popular non-invasive method to assess the vulnerability to malignant arrhythmic events. These instabilities are usually characterized by small amplitude changes and their measurement is difficult due to the presence of noise and artifacts. Several methods have been recently proposed to address this problem. Most of them are based on amplitude analysis of beat-to-beat alternation of the T wave. This paper describes a preprocessing stage intended to be used prior to amplitude analysis and aimed at improving the alignment between consecutive T waves. This increases the accuracy of the difference calculation.

The PhysioNet / Computers in Cardiology Challenge 2008: T-Wave Alternans

The 9th annual PhysioNet/Computers in Cardiology challenge invited participants to measure T-wave alternans (TWA) in a set of 100 two-minute electrocardiograms that included subjects with a variety of risk factors for sudden cardiac death (including ventricular tachyarrhythmias, transient myocardial ischemia, and acute myocardial infarctions), healthy controls, and synthetic ECGs with calibrated amounts of artificial TWA. The participants' TWA estimates were used to develop a ranking of the 100 test cases in order of TWA content, and the Kendall rank correlation coefficient between this reference ranking and each individual participant's ranking of the 100 cases was calculated as a score (between -1 and 1; actual scores were between 0.11 and 0.92). The challenge yielded insights into the strengths and weaknesses of classic and novel TWA analyses, open-source implementations of a variety of methods, and a set of freely available ECGs with reference rankings of TWA content.

Characterization of T wave alternans with ambulatory electrocardiography

T wave alternans (TWA) is a marker of ventricular electrical instability considered to be predictive for ventricular tachyarrhythmias. Techniques have been developed to detect TWA at the microv level as a method for arrhythmia risk stratification of persons at high risk for sudden cardiac death. Currently, TWA is typically calculated using spectral analysis, whereby TWA is presumed to assume characteristics of stationarity. In contrast, a nonspectral method known as modified moving average analysis is purported to detect transient TWA that would not be observed using a spectral approach. The purpose of this pilot study work was to establish the basic TWA signal properties obtained with a device developed by GE Medical Systems using a descriptive, correlational study design. Ambulatory electrocardiography (AECG) recordings (N = 24) were digitized and processed, and TWA was calculated via the modified moving average technique. Findings showed that noise was positively correlated with TWA in AECG channel 1 (r = .899, p < .01) and AECG channel 2 (r = .758, p < .01). However, no significant difference (p = .237) was observed in TWA values between the AECG channels. A weak positive correlation was found between TWA and heart rate, expressed as beats per min (r = .262). Heart rate mildly predicted TWA (R = 0.34). Nonstationarity was evaluated by testing for trend and randomness. TWA values measured from AECG recordings were found to be influenced moderately by noise and minimally by heart rate and lead placement.

Rhythms of high-grade block in an ionic model of a strand of regionally ischemic ventricular muscle

Electrical alternans, a beat-to-beat alternation in the electrocardiogram or electrogram, is frequently seen during the first few minutes of acute myocardial ischemia, and is often immediately followed by malignant cardiac arrhythmias such as ventricular tachycardia and ventricular fibrillation. As ischemia progresses, higher-order periodic rhythms (e.g., period-4) can replace the period-2 alternans rhythm. This is also seen in modelling work on a two-dimensional (2-D) sheet of regionally ischemic ventricular muscle. In addition, in the experimental work, ventricular arrhythmias are overwhelmingly seen only after the higher-order rhythms arise. We investigate an ionic model of a strand of ischemic ventricular muscle, constructed as a 3-cm-long 1-D cable with a centrally located 1-cm-long segment exposed to an elevated extracellular potassium concentration ([K(+)](o)). As [K(+)](o) is raised in this "ischemic segment" to represent one major effect of ongoing ischemia, the sequence of rhythms {1:1-->2:2 (alternans)-->2:1} is seen. With further increase in [K(+)](o), one sees higher-order periodic 2N:M rhythms {2:1-->4:2-->4:1-->6:2-->6:1-->8:2-->8:1}. In a 2N:M cycle, only M of the 2N action potentials generated at the proximal end of the cable successfully traverse the ischemic segment, with the remaining ones being blocked within the ischemic segment. Finally, there is a transition to complete block {8:1-->2:0-->1:0} (in an n:0 rhythm, all action potentials die out within the ischemic segment). Changing the length of the ischemic segment results in different rhythms and transitions being seen: e.g., when the ischemic segment is 2 cm long, the period-6 rhythms are not seen; when it is 0.5 cm long, there is a 3:1 rhythm interposed between the 2:1 and 1:0 rhythms. We discuss the relevance of our results to the experimental observations on the higher-order rhythms that presage reentrant ischemic ventricular arrhythmias.

Predicting Arrhythmia-Free Survival Using Spectral and Modified-Moving Average Analyses of T-Wave Alternans

BACKGROUND

T-wave alternans (TWA) is a promising electrocardiogram (ECG) predictor of sudden cardiac arrest, yet needs specialized recordings for conventional spectral analysis. Modified moving average (MMA) analysis is a new approach that can measure TWA from routine ECGs, thus widening its applicability. However, MMA-TWA has not been calibrated against spectral TWA nor outcome in high risk patients. We hypothesized that spectral and MMA-TWA would both predict arrhythmia-free survival on long-term prospective follow-up.

METHODS AND RESULTS

In 41 patients with left ventricular systolic dysfunction (ejection fraction 31 +/- 13%), we studied TWA simultaneously using spectral and MMA during pacing (< 110 beats/min). MMA amplified TWA over spectral analyses (13.0 +/- 8.28 microV vs 1.96 +/- 5.15 microV, P < 0.001). On 542 +/- 311 days' follow-up, from clinic visits, telephonic interviews, and device interrogations, there were 11 deaths or sustained ventricular arrhythmias ('events'). Positive spectral TWA (>or=1.9 microV) identified patients with from those without events (P = 0.02). Receiver-operating characteristics for MMA-TWA showed that the cutpoint >or= 10.75 microV was optimal for the combined endpoint. Kaplan-Meier analysis using this MMA-TWA cutpoint trended to predict events (P = 0.06), while MMA combined with spectral TWA identified events (P = 0.01).

CONCLUSIONS

MMA amplifies TWA compared to traditional spectral analyses, but both likely reflect similar pathophysiology. Validation in larger populations will enable MMA-TWA to be widely applied to stratify risk for sudden cardiac arrest.

Characterization of repolarization alternans during ischemia: time-course and spatial analysis

T-wave alternans (TWA) has been linked to increased vulnerability to ventricular fibrillation in different settings including myocardial ischemia. In this study, we propose a methodology for the characterization of TWA induced by transient, regional ischemia. We studied the prevalence, magnitude and spatio-temporal relationship between TWA and ischemia in 95 patients undergoing percutaneous transluminal coronary angioplasty (PTCA). Two electrocardiogram records of each patient, a control recording before PTCA and the PTCA record, were analyzed using a robust, recently proposed method for TWA analysis. The detected episodes were characterized in terms of their time-course, lead distribution and alternans waveform. One third of the patients (33.7%) showed TWA episodes during PTCA. The highest prevalence (51.7%) and amplitude were found in patients with left anterior descendent artery occlusion. The onset of TWA was detected after the first 1-2 min of occlusion, suggesting that some level of ischemia must be attained before TWA arises, while disappearance of TWA following reperfusion was much more rapid. The TWA lead distributions and waveforms showed distinct distributions according to the occluded artery reflecting the regional nature of the TWA phenomenon.

T-wave alternans and the susceptibility to ventricular arrhythmias

T-wave alternans (TWA) reflects beat-to-beat fluctuations in the electrocardiographic T-wave, and is associated with dispersion of repolarization and the mechanisms for sudden cardiac arrest (SCA). This review examines the bench-to-bedside literature that, over decades, has linked alternans of repolarization in cellular, whole-heart, and human studies with spatial dispersion of repolarization, alternans of cellular action potential, and fluctuations in ionic currents that may lead to ventricular arrhythmias. Collectively, these studies provide a foundation for the clinical use of TWA to reflect susceptibility to ventricular arrhythmias in several disease states. This review then provides a contemporary evidence-based framework for the use of TWA to enhance risk stratification for SCA, identifying populations for whom TWA is best established, those for whom further studies are required, and areas for additional investigation.