Cardiac cells stimulated with an axial current-like waveform reproduce electrophysiological properties of tissue fibers.

BACKGROUND AND OBJECTIVE: In silico electrophysiological models are generally validated by comparing simulated results with experimental data. When dealing with single-cell and tissue scales simultaneously, as occurs frequently during model development and calibration, the effects of inter-cellular coupling should be considered to ensure the trustworthiness of model predictions. The hypothesis of this paper is that the cell-tissue mismatch can be reduced by incorporating the effects of conduction into the single-cell stimulation current. METHODS: Five different stimulation waveforms were applied to the human ventricular O'Hara-Rudy cell model. The waveforms included the commonly used monophasic and biphasic (symmetric and asymmetric) pulses, a triangular waveform and a newly proposed asymmetric waveform (stimulation A) that resembles the transmembrane current associated with AP conduction in tissue. A comparison between single-cell and fiber simulated results was established by computing the relative difference between the values of AP-derived properties at different scales, and by evaluating the differences in the contributions of ionic conductances to each evaluated property. As a proof of the benefit, we investigated multi-scale differences in the simulation of the effects induced by dofetilide, a selective IKr blocker with high torsadogenic risk, on ventricular repolarization at different pacing rates. RESULTS: Out of the five tested stimulation waveforms, stimulation A produced the closest correspondence between cell and tissue simulations in terms of AP properties at steady-state and under dynamic pacing and of ionic contributors to those AP properties. Also, stimulation A reproduced the effects of dofetilide better than the other alternative waveforms, mirroring the 'beat-skipping' behavior observed at fast pacing rates in experiments with human tissue. CONCLUSIONS: The proposed stimulation current waveform accounts for inter-cellular coupling effects by mimicking cell excitation during AP conduction. The proposed waveform improves the correspondence between simulation scales, which could improve the trustworthiness of single-cell simulations without adding computational cost.

Assessment of ventricular repolarization instability in terms of T-wave alternans induced by head-down bed-rest immobilization.

OBJECTIVE: To assess the effects of different durations of simulated microgravity exposure on ventricular repolarization (VR) in terms of T-wave alternans (TWA) as well as to test whether an increase in VR heterogeneity could be detected once normal gravity was restored. APPROACH: A total of 63 healthy volunteers were recruited in several head-down bed-rest (HDBR) experiments in the context of the European Space Agency bed-rest strategy. TWA is evaluated during the night period using ambulatory ECG recordings, before, during and after long- (60 d), mid- (21 d) and short- (5 d) duration HDBR by the long-term averaging technique. MAIN RESULTS: 5-21 d of exposure to simulated microgravity by means of the HDBR model do not lead to a significant increase of cardiac electrical instability in healthy myocardial substrates up to the point of eliciting TWA on the surface ECG. However, TWA indices increased after long-term HDBR exposure, once normal gravity was re-established, indicative of incipient electrical instability on VR at the conclusion of 60 d of HDBR. SIGNIFICANCE: The results of this work underline the importance of focusing future research on immediate effects after long-term microgravity exposure, both simulated by HDBR or from space mission scenarios, once partial gravity conditions are re-established. A deeper insight in the understanding of human body reactions in these scenarios results crucial in the design of future long-duration spaceflight missions, to mitigate any potential risk that can limit astronaut's performance.

DENIS: Solving cardiac electrophysiological simulations with volunteer computing.

Cardiac electrophysiological simulations are computationally intensive tasks. The growing complexity of cardiac models, together with the increasing use of large ensembles of models (known as populations of models), make extensive simulation studies unfeasible for regular stand-alone computers. To address this problem, we developed DENIS, a cardiac electrophysiology simulator based on the volunteer computing paradigm. We evaluated the performance of DENIS by testing the effect of simulation length, task deadline, and batch size, on the time to complete a batch of simulations. In the experiments, the time to complete a batch of simulations did not increase with simulation length, and had little dependence on batch size. In a test case involving the generation of a population of models, DENIS was able to reduce the simulation time from years to a few days when compared to a stand-alone computer. Such capacity makes it possible to undertake large cardiac simulation projects without the need for high performance computing infrastructure.

Post-Ventricular Premature Contraction Phase Correction Improves the Predictive Value of Average T-Wave Alternans in Ambulatory ECG Recordings.

OBJECTIVE: We proposed and evaluated a method for correcting possible phase shifts provoked by the presence of ventricular premature contractions (VPCs) for a better assessment of T-wave alternans (TWA).  Methods: First, we synthesized ECG signals with artificial TWA in the presence of different noise sources. Then, we assessed the prognostic value for sudden cardiac death (SCD) of the long-term average of TWA amplitude (the index of average alternans, ) in ambulatory ECG signals from congestive heart failure (CHF) and evaluated whether it is sensitive to the presence of VPCs. RESULTS: The inclusion of the phase correction after VPC in the processing always improved estimation accuracy of the under different noisy conditions and regardless of the number of the VPCs included in the sequence. It also presented a positive impact on the prognostic value of with increased hazard ratios (from 17% to 29%, depending of the scenario) in comparison to the noninclusion of this step. CONCLUSION: The proposed methodology for estimation, which corrects for the possible phase reversal on TWA after the presence of VPCs, represents a robust TWA estimation approach with a significant impact on the prognostic value of for SCD stratification in CHF patients. SIGNIFICANCE: An accurate TWA estimation has a potential direct clinical impact on noninvasive SCD stratification, allowing better identification of patients at higher risk and helping clinicians in adopting the most appropriate therapeutic strategy.

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model.

BACKGROUND: Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. METHODS: The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. RESULTS: The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. CONCLUSION: The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients.

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

BACKGROUND: Patients with chronic heart failure are at high risk of sudden cardiac death (SCD). Increased dispersion of repolarization restitution has been associated with SCD, and we hypothesize that this should be reflected in the morphology of the T-wave and its variations with heart rate. The aim of this study is to propose an electrocardiogram (ECG)-based index characterizing T-wave morphology restitution (TMR), and to assess its association with SCD risk in a population of chronic heart failure patients. METHODS AND RESULTS: Holter ECGs from 651 ambulatory patients with chronic heart failure from the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study were available for the analysis. TMR was quantified by measuring the morphological variation of the T-wave per RR increment using time-warping metrics, and its predictive power was compared to that of clinical variables such as the left ventricular ejection fraction and other ECG-derived indices, such as T-wave alternans and heart rate variability. TMR was significantly higher in SCD victims than in the rest of patients (median 0.046 versus 0.039, P<0.001). When TMR was dichotomized at TMR=0.040, the SCD rate was significantly higher in the TMR≥0.040 group (P<0.001). Cox analysis revealed that TMR≥0.040 was strongly associated with SCD, with a hazard ratio of 3.27 (P<0.001), independently of clinical and ECG-derived variables. No association was found between TMR and pump failure death. CONCLUSIONS: This study shows that TMR is specifically associated with SCD in a population of chronic heart failure patients, and it is a better predictor than clinical and ECG-derived variables.

Limitations in electrophysiological model development and validation caused by differences between simulations and experimental protocols.

Models of ion channel dynamics are usually built by fitting isolated cell experimental values of individual parameters while neglecting the interaction between them. Another shortcoming regards the estimation of ionic current conductances, which is often based on quantification of Action Potential (AP)-derived markers. Although this procedure reduces the uncertainty in the calculation of conductances, many studies evaluate electrophysiological AP-derived markers from single cell simulations, whereas experimental measurements are obtained from tissue preparations. In this work, we explore the limitations of these approaches to estimate ion channel dynamics and maximum current conductances and how they could be overcome by using multiscale simulations of experimental protocols. Four human ventricular cell models, namely ten Tusscher and Panfilov (2006), Grandi et al. (2010), O'Hara et al. (2011), and Carro et al. (2011), were used. Two problems involving scales from ion channels to tissue were investigated: 1) characterization of L-type calcium voltage-dependent inactivation ICa,L; 2) identification of major ionic conductance contributors to steady-state AP markers, including APD90, APD75, APD50, APD25, Triangulation and maximal and minimal values of V and dV/dt during the AP (Vmax, Vmin, dV/dtmax, dV/dtmin). Our results show that: 1) ICa,L inactivation characteristics differed significantly when calculated from model equations and from simulations reproducing the experimental protocols. 2) Large differences were found in the ionic currents contributors to APD25, Triangulation, Vmax, dV/dtmax and dV/dtmin between single cells and 1D-tissue. When proposing any new model formulation, or evaluating an existing model, consistency between simulated and experimental data should be verified considering all involved effects and scales.

Automatic SVM classification of sudden cardiac death and pump failure death from autonomic and repolarization ECG markers.

BACKGROUND: Considering the rates of sudden cardiac death (SCD) and pump failure death (PFD) in chronic heart failure (CHF) patients and the cost-effectiveness of their preventing treatments, identification of CHF patients at risk is an important challenge. In this work, we studied the prognostic performance of the combination of an index potentially related to dispersion of repolarization restitution (Δα), an index quantifying T-wave alternans (IAA) and the slope of heart rate turbulence (TS) for classification of SCD and PFD. METHODS: Holter ECG recordings of 597 CHF patients with sinus rhythm enrolled in the MUSIC study were analyzed and Δα, IAA and TS were obtained. A strategy was implemented using support vector machines (SVM) to classify patients in three groups: SCD victims, PFD victims and other patients (the latter including survivors and victims of non-cardiac causes). Cross-validation was used to evaluate the performance of the implemented classifier. RESULTS: Δα and IAA, dichotomized at 0.035 (dimensionless) and 3.73 µV, respectively, were the ECG markers most strongly associated with SCD, while TS, dichotomized at 2.5 ms/RR, was the index most strongly related to PFD. When separating SCD victims from the rest of patients, the individual marker with best performance was Δα≥0.035, which, for a fixed specificity (Sp) of 90%, showed a sensitivity (Se) value of 10%, while the combination of Δα and IAA increased Se to 18%. For separation of PFD victims from the rest of patients, the best individual marker was TS ≤ 2.5 ms/RR, which, for Sp=90%, showed a Se of 26%, this value being lower than Se=34%, produced by the combination of Δα and TS. Furthermore, when performing SVM classification into the three reported groups, the optimal combination of risk markers led to a maximum Sp of 79% (Se=18%) for SCD and Sp of 81% (Se=14%) for PFD. CONCLUSIONS: The results shown in this work suggest that it is possible to efficiently discriminate SCD and PFD in a population of CHF patients using ECG-derived risk markers like Δα, TS and IAA.

Comparative evaluation of methodologies for T-wave alternans mapping in electrograms.

Electrograms (EGM) recorded from the surface of the myocardium are becoming more and more accessible. T-wave alternans (TWA) is associated with increased vulnerability to ventricular tachycardia/fibrillation and it occurs before the onset of ventricular arrhythmias. Thus, accurate methodologies for time-varying alternans estimation/detection in EGM are needed. In this paper, we perform a simulation study based on epicardial EGM recorded in vivo in humans to compare the accuracy of four methodologies: the spectral method (SM), modified moving average method, laplacian likelihood ratio method (LLR), and a novel method based on time-frequency distributions. A variety of effects are considered, which include the presence of wide band noise, respiration, and impulse artifacts. We found that 1) EGM-TWA can be detected accurately when the standard deviation of wide-band noise is equal or smaller than ten times the magnitude of EGM-TWA. 2) Respiration can be critical for EGM-TWA analysis, even at typical respiratory rates. 3) Impulse noise strongly reduces the accuracy of all methods, except LLR. 4) If depolarization time is used as a fiducial point, the localization of the T-wave is not critical for the accuracy of EGM-TWA detection. 5) According to this study, all methodologies provided accurate EGM-TWA detection/quantification in ideal conditions, while LLR was the most robust, providing better detection-rates in noisy conditions. Application on epicardial mapping of the in vivo human heart shows that EGM-TWA has heterogeneous spatio-temporal distribution.

Prognostic value of average T-wave alternans and QT variability for cardiac events in MADIT-II patients.

BACKGROUND: Identifying which patients might benefit the most from ICD therapy remains challenging. We hypothesize that increased T-wave alternans (TWA) and QT variability (QTV) provide complementary information for predicting appropriate ICD therapy in patients with previous myocardial infarction and reduced ejection fraction. METHODS: We analyzed 10-min resting ECGs from MADIT-II patients with baseline heart rate >80 beats/min. TWA indices IAA and IAA90 were computed with the multilead Laplacian Likelihood ratio method. QTV indices QTVN and QTVI were measured using a standard approach. Cox proportional hazard models were adjusted considering appropriate ICD therapy and sudden cardiac death (SCD) as endpoints. RESULTS: TWA and QTV were measured in 175 patients. Neither QTV nor TWA predicted SCD. Appropriate ICD therapy was predicted by combining IAA90 and QTVN after adjusting for relevant correlates. CONCLUSION: Increased TWA and QTV are independent predictors of appropriate ICD therapy in MADIT-II patients with elevated heart rate at baseline.

T wave alternans in experimental myocardial infarction: time course and predictive value for the assessment of myocardial damage.

BACKGROUND: T-wave alternans (TWA) is associated with prognosis after myocardial infarction (MI), however its link to the extent of ischemic injury has not been clarified. We analyzed the course of TWA and its relation to myocardial damage in experimental myocardial infarction. METHODS: In 21 pigs, infarction was induced by 40-minute long balloon inflation in LAD under continuous 12-lead ECG monitoring. TWA was assessed in a 32-beat sliding window, using periodic component analysis and the Laplacian Likelihood Ratio method. Myocardium at risk (MaR) and infarct size (IS) were evaluated by SPECT and magnetic resonance imaging respectively. RESULTS: TWA appeared at 7.2±4.5minutes of occlusion, reached its maximum at 12.7±6.3 and lasted until 26.5±9.2minutes. The maximal level of TWA was associated with both MaR (r=0.499, p=0.035) and IS (r=0.65, p=0.004). CONCLUSION: TWA magnitude is associated with both MaR and IS in experiment, which encourages further studies in clinical settings.

Robust classification of neonatal apnoea-related desaturations.

Respiratory signals monitored in the neonatal intensive care units are usually ignored due to the high prevalence of noise and false alarms (FA). Apneic events are generally therefore indicated by a pulse oximeter alarm reacting to the subsequent desaturation. However, the high FA rate in the photoplethysmogram may desensitize staff, reducing the reaction speed. The main reason for the high FA rates of critical care monitors is the unimodal analysis behaviour. In this work, we propose a multimodal analysis framework to reduce the FA rate in neonatal apnoea monitoring. Information about oxygen saturation, heart rate, respiratory rate and signal quality was extracted from electrocardiogram, impedance pneumogram and photoplethysmographic signals for a total of 20 features in the 5 min interval before a desaturation event. 1616 desaturation events from 27 neonatal admissions were annotated by two independent reviewers as true (physiologically relevant) or false (noise-related). Patients were divided into two independent groups for training and validation, and a support vector machine was trained to classify the events as true or false. The best classification performance was achieved on a combination of 13 features with sensitivity, specificity and accuracy of 100% in the training set, and a sensitivity of 86%, a specificity of 91% and an accuracy of 90% in the validation set.

Average T-wave alternans activity in ambulatory ECG records predicts sudden cardiac death in patients with chronic heart failure.

BACKGROUND: T-wave alternans (TWA) is a well-documented noninvasive electrocardiographic (ECG) method useful for identifying patients at risk for sudden cardiac death (SCD). OBJECTIVE: The purpose of this study was to evaluate whether the long-term average TWA activity on Holter monitoring provides prognostic information in patients with chronic heart failure. METHODS: Twenty-four-hour Holter ECGs from 650 ambulatory patients with mild-to-moderate chronic heart failure were analyzed in the study. Average TWA activity was measured by using a fully automated multilead technique, and 2 indices were proposed to quantify TWA: an index quantifying the average TWA activity in the whole recording (IAA), which was used to define a positive/negative TWA test, and an index quantifying the average TWA activity at heart rates between 80 and 90 beats/min (IAA(90)). RESULTS: Patients were divided into TWA positive (TWA+) and TWA negative (TWA-) groups by setting a cut point of 3.7 µV for IAA, corresponding to the 75th percentile of the distribution of IAA in the population. After a median follow-up of 48 months, the survival rate was significantly higher in the TWA- group for cardiac death and SCD (p = .017 and p = .001, respectively). Multivariate Cox proportional hazards analysis revealed that both TWA+ and IAA(90) were associated with SCD with hazard rates of 2.29 (p = .004) and 1.07 per µV (p = .046), respectively. CONCLUSION: The average TWA activity measured automatically from Holter ECGs predicted SCD in patients with mild-to-moderate chronic heart failure.

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.

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.

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.

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.

Pulse photopletismography amplitude decrease detector for sleep apnea evaluation in children.

A method for automatic detection of sleep apnea using pulse photopletismography signal (PPG) is proposed. This method is based on a detection of decreases on PPG amplitude fluctuations. The proposed detector is composed of three stages: pre-processing, envelope detection, based on root mean square series or Hilbert transform, and decision algorithm based on an adaptive threshold. The detector has been evaluated using simulated and real signals. Sensibility and positive predictive value of the detector where 76% and 73% for real signals. A clinical study to sleep apnea diagnosis in children based on this detector has been carried out. PPG attenuation events per hour ratio Eh has statistical significance (p < 0.05) to classify children as normal 13.5 ± 6.35 Eh(mean ± SD) or pathologic 21.1 ± 8.93 Eh.