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

Prognostic Role of Electrocardiographic Alternans in Ischemic Heart Disease

Background/Objectives: Noninvasive arrhythmic risk stratification in patients with ischemic heart disease is poor nowadays, and further investigations are needed. The most correct approach is based on the use of electrocardiogram (ECG) with the extraction of indices such as ECG alternans (ECGA). The aim of this study is to monitor the ECG evidence of ischemic coronary artery occlusion by the ECGA and to verify its ability to monitor the time course of balloon inflation, with the final goal of contributing to the exploration of the prognostic role of ECGA in ischemic heart disease. Methods: The ECGA amplitude and magnitude were computed by the correlation method (CM) on the STAFF III database, where ischemic coronary artery occlusion was induced in a controlled manner through coronary artery blockage by balloon inflation. ECGA computed during balloon inflation was also compared with periods before and after the inflation. Results: ECGA values became statistically higher during inflation than in the pre-inflation period and increased as inflation time increased, although not always in a statistically significant manner. ECGA went from values in the range 4-7 µV and 169-396 µV·beat before inflation to values in the range 5-9 µV and 208-573 µV·beat during 5 min of inflation (resulting statistically higher than before inflation), returning towards values in the range 4-8 µV and 182-360 µV·beat after inflation for amplitude and magnitude, respectively. Conclusions: CM-based ECGA detection was able to track the balloon inflation period. Our ECGA investigation represents a contribution in the field of research exploring its prognostic role as a noninvasive electrical risk index in ischemic heart disease.

Machine Learning approach for TWA detection relying on ensemble data design

BACKGROUND AND OBJECTIVE

T-wave alternans (TWA) is a fluctuation of the ST-T complex of the surface electrocardiogram (ECG) on an every-other-beat basis. It has been shown to be clinically helpful for sudden cardiac death stratification, though the lack of a gold standard to benchmark detection methods limits its application and impairs the development of alternative techniques. In this work, a novel approach based on machine learning for TWA detection is proposed. Additionally, a complete experimental setup is presented for TWA detection methods benchmarking.

METHODS

The proposed experimental setup is based on the use of open-source databases to enable experiment replication and the use of real ECG signals with added TWA episodes. Also, intra-patient overfitting and class imbalance have been carefully avoided. The Spectral Method (SM), the Modified Moving Average Method (MMA), and the Time Domain Method (TM) are used to obtain input features to the Machine Learning (ML) algorithms, namely, K Nearest Neighbor, Decision Trees, Random Forest, Support Vector Machine and Multi-Layer Perceptron.

RESULTS

There were not found large differences in the performance of the different ML algorithms. Decision Trees showed the best overall performance (accuracy 0.88 ± 0.04 , precision 0.89 ± 0.05 , Recall 0.90 ± 0.05 , F1 score 0.89 ± 0.03 ). Compared to the SM (accuracy 0.79, precision 0.93, Recall 0.64, F1 score 0.76) there was an improvement in every metric except for the precision.

CONCLUSIONS

In this work, a realistic database to test the presence of TWA using ML algorithms was assembled. The ML algorithms overall outperformed the SM used as a gold standard. Learning from data to identify alternans elicits a substantial detection growth at the expense of a small increment of the false alarm.

T-Wave Alternans in Nonpathological Preterm Infants

BACKGROUND

Sudden infant death syndrome is more frequent in preterm infants (PTI) than term infants and may be due to cardiac repolarization instability, which may manifest as T-wave alternans (TWA) on the electrocardiogram (ECG). Therefore, the aim of the present work was to analyze TWA in nonpathological PTI and to open an issue on its physiological interpretation.

METHODS

Clinical population consisted of ten nonpathological PTI (gestational age ranging from 29 3 7 to 34 2 7  weeks; birth weight ranging from 0.84 to 2.10 kg) from whom ECG recordings were obtained ("Preterm infant cardio-respiratory signals database" by Physionet). TWA was identified through the heart-rate adapting match filter method and characterized in terms of mean amplitude values (TWAA). TWA correlation with several other clinical and ECG features, among which gestational age-birth weight ratio, RR interval, heart-rate variability, and QT interval, was also performed.

RESULTS

TWA was variable among infants (TWAA = 26 ± 11 µV). Significant correlations were found between TWAA versus birth weight (ρ = -0.72, p = .02), TWAA versus gestational age-birth weight ratio (ρ = 0.76, p = .02) and TWAA versus heart-rate variability (ρ = -0.71, p = .02).

CONCLUSIONS

Our preliminary retrospective study suggests that nonpathological PTI show TWA of few tens of µV, the interpretation of which is still an open issue but could indicate a condition of cardiac risk possibly related to the low development status of the infant. Further investigations are needed to solve this issue.

Dofetilide-Induced Microvolt T-Wave Alternans

Dofetilide is an antiarrhythmic drug that selectively inhibits the rapid component of the delayed rectifier potassium current. The administration of dofetilide may cause ventricular arrhythmias and torsade de pointes. Electrocardiographic (ECG) microvolt T-wave alternans (TWA), an electrophysiologic phenomenon consisting in the beat-to-beat alternation of the T-wave amplitude requiring computerized algorithms to be detected, has also been associated to malignant ventricular arrhythmias. Aim of the present study was to evaluate if dofetilide induces TWA during the 24 hours following administration. The study population consisted of 22 healthy subjects ("ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects" database by Physionet) to whom a 500 μg-dose of dofetilide was administered. For each subject, 10 s ECG were acquired at baseline (0.5 hour before dofetilide administration) and at 15 time points during the 24 hours following the drug administration. ECG were then processed for automatic TWA detection by correlation method. In 21 subjects out of 22, after dofetilide administration, TWA significantly increased to a peak value (median TWA values went from 6 μV at baseline to a max 32 μV; p<; 0.05), on average after 5 hours, to then come back to values closer to baseline. Thus, in healthy subjects, dofetilide increases occurrence and levels (6 times baseline value on average) of TWA in the hours following its administration.

Benchmarking of a T-wave alternans detection method based on empirical mode decomposition

BACKGROUND AND OBJECTIVE

T-wave alternans (TWA) is a fluctuation of the ST-T complex occurring on an every-other-beat basis of the surface electrocardiogram (ECG). It has been shown to be an informative risk stratifier for sudden cardiac death, though the lack of gold standard to benchmark detection methods has promoted the use of synthetic signals. This work proposes a novel signal model to study the performance of a TWA detection. Additionally, the methodological validation of a denoising technique based on empirical mode decomposition (EMD), which is used here along with the spectral method, is also tackled.

METHODS

The proposed test bed system is based on the following guidelines: (1) use of open source databases to enable experimental replication; (2) use of real ECG signals and physiological noise; (3) inclusion of randomized TWA episodes. Both sensitivity (Se) and specificity (Sp) are separately analyzed. Also a nonparametric hypothesis test, based on Bootstrap resampling, is used to determine whether the presence of the EMD block actually improves the performance.

RESULTS

The results show an outstanding specificity when the EMD block is used, even in very noisy conditions (0.96 compared to 0.72 for SNR = 8 dB), being always superior than that of the conventional SM alone. Regarding the sensitivity, using the EMD method also outperforms in noisy conditions (0.57 compared to 0.46 for SNR=8 dB), while it decreases in noiseless conditions.

CONCLUSIONS

The proposed test setting designed to analyze the performance guarantees that the actual physiological variability of the cardiac system is reproduced. The use of the EMD-based block in noisy environment enables the identification of most patients with fatal arrhythmias.

A time-domain hybrid analysis method for detecting and quantifying T-wave alternans

T-wave alternans (TWA) in surface electrocardiograph (ECG) signals has been recognized as a marker of cardiac electrical instability and is hypothesized to be associated with increased risk for ventricular arrhythmias among patients. A novel time-domain TWA hybrid analysis method (HAM) utilizing the correlation method and least squares regression technique is described in this paper. Simulated ECGs containing artificial TWA (cases of absence of TWA and presence of stationary or time-varying or phase-reversal TWA) under different baseline wanderings are used to test the method, and the results show that HAM has a better ability of quantifying TWA amplitude compared with the correlation method (CM) and adapting match filter method (AMFM). The HAM is subsequently used to analyze the clinical ECGs, and results produced by the HAM have, in general, demonstrated consistency with those produced by the CM and the AMFM, while the quantifying TWA amplitudes by the HAM are universally higher than those by the other two methods.

Mechanical alternans is associated with mortality in acute hospitalized heart failure: prospective mechanical alternans study (MAS)

BACKGROUND

Acute hospitalized heart failure (AHHF) is associated with 40% to 50% risk of death or rehospitalization within 6 months after discharge. Timely (before hospital discharge) risk stratification of patients with AHHF is crucial. We hypothesized that mechanical alternans (MA) and T-wave alternans (TWA) are associated with postdischarge outcomes in patients with AHHF.

METHODS AND RESULTS

A prospective cohort study was conducted in the intensive cardiac care unit and enrolled 133 patients (59.6±15.7 years; 65% men) admitted with AHHF. Surface ECG and peripheral arterial blood pressure waveform via arterial line were recorded continuously during the intensive cardiac care unit stay. MA and TWA were measured by enhanced modified moving average method. All-cause death or heart transplant served as a combined primary end point. MA was observed in 28 patients (25%), whereas TWA was detected in 33 patients (33%). If present, MA was tightly coupled with TWA. Mean TWA amplitude was larger in patients with both TWA and MA when compared with patients with lone TWA (median, 37 [interquartile range, 26-61] versus 22 [21-23] μV; P=0.045). After a median of 10-month postdischarge, 42 (38%) patients died and 2 had heart transplants. MA was associated with the primary end point in univariable Cox model (hazard ratio, 1.84; 95% confidence interval, 1.00-3.40; P=0.05) and after adjustment for left ventricular ejection fraction, New York Heart Association HF class, and implanted implantable cardioverter defibrillator/cardiac resynchronization therapy defibrillator (hazard ratio, 2.12 95% confidence interval, 1.13-3.98; P=0.020). TWA without consideration of simultaneous MA was not significantly associated with primary end point (hazard ratio, 1.42; 95% confidence interval, 0.77-2.64; P=0.260).

CONCLUSIONS

MA is independently associated with outcomes in AHHF.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT01557465.

Performance evaluation of diverse T-wave alternans estimators under variety of noise characterizations and alternans distributions

Prognostic significance of microvolt T-wave alternans (TWA) has been established since their inclusion among important risk stratifiers for sudden cardiac death. Signal processing schemes employed for TWA estimation have their peculiar theoretical assumptions and reported statistics. An unbiased comparison of all these techniques is still a challenge. Choosing three classical schemes, this study aims to achieve holistic performance evaluation of diverse TWA estimators from a three dimensional standpoint, i.e., estimation statistics, alternan distribution and ECG signal quality. Three performance indices called average deviation (ϑ( L )), moment of deviation (ϑ( m )) and coefficient of deviation ([Formula: see text]) are devised to quantify estimator performance and consistency. Both synthetic and real physiological noises, as well as variety of temporal distributions of alternan waveforms are simulated to evaluate estimators' responses. Results show that modification of original estimation statistics, consideration of relevant noise models and a priori knowledge of alternan distribution is necessary for an unbiased performance comparison. Spectral method proves to be the most accurate for stationary TWA, even at SNRs as low as 5 dB. Correlation method's strength lies in accurately detecting temporal origins of multiple alternan episodes within a single analysis window. Modified moving average method gives best estimation at lower noise levels (SNR >25 dB) for non-stationary TWA. Estimation of both MMAM and CM is adversely effected by even small baseline drifts due to respiration, although CM gives considerably higher deviation levels than MMAM. Performance of SM is only effected when fundamental frequency of baseline drift due to respiration falls within the estimation band around 0.5 cpb.