Esther Pueyo

Characterization of QT interval adaptation to RR interval changes and its use as a risk-stratifier of arrhythmic mortality in amiodarone-treated survivors of acute myocardial infarction

A new method is proposed to evaluate the dynamics of QT interval adaptation in response to heart rate (HR) changes. The method considers weighted averages of RR intervals (R~R~) preceding each cardiac beat to express RR interval history accounting for the influence on repolarization duration. A global optimization algorithm is used to determine the weight distribution leading to the lowest regression residual when curve fitting the [QT, R~R~] data using a patient- specific regression model. From the optimum weight distribution, a memory lag L/sub 90/ is estimated, expressing the delay in the QT adaptation to HR changes. On average, RR intervals of the past 150 beats (approximately 2.5 min) are required to model the QT response accurately. From a clinical point of view, the interval of the initial tens of seconds to one minute seems to be most important in the majority of cases. A measure of the optimum regression residual (r/sub opt/) has been calculated, discriminating between post-myocardial infarction patients at high and low risk of arrhythmic death while on treatment with amiodarone. A similar discrimination has been achieved with a variable expressing the character of QT lag behind the RR interval dynamics.

Impact of ionic current variability on human ventricular cellular electrophysiology

Abnormalities in repolarization and its rate dependence are known to be related to increased proarrhythmic risk. A number of repolarization-related electrophysiological properties are commonly used as preclinical biomarkers of arrhythmic risk. However, the variability and complexity of repolarization mechanisms make the use of cellular biomarkers to predict arrhythmic risk preclinically challenging. Our goal is to investigate the role of ionic current properties and their variability in modulating cellular biomarkers of arrhythmic risk to improve risk stratification and identification in humans. A systematic investigation into the sensitivity of the main preclinical biomarkers of arrhythmic risk to changes in ionic current conductances and kinetics was performed using computer simulations. Four stimulation protocols were applied to the ten Tusscher and Panfilov human ventricular model to quantify the impact of +/-15 and +/-30% variations in key model parameters on action potential (AP) properties, Ca(2+) and Na(+) dynamics, and their rate dependence. Simulations show that, in humans, AP duration is moderately sensitive to changes in all repolarization current conductances and in L-type Ca(2+) current (I(CaL)) and slow component of the delayed rectifier current (I(Ks)) inactivation kinetics. AP triangulation, however, is strongly dependent only on inward rectifier K(+) current (I(K1)) and delayed rectifier current (I(Kr)) conductances. Furthermore, AP rate dependence (i.e., AP duration rate adaptation and restitution properties) and intracellular Ca(2+) and Na(+) levels are highly sensitive to both I(CaL) and Na(+)/K(+) pump current (I(NaK)) properties. This study provides quantitative insights into the sensitivity of preclinical biomarkers of arrhythmic risk to variations in ionic current properties in humans. The results show the importance of sensitivity analysis as a powerful method for the in-depth validation of mathematical models in cardiac electrophysiology.

QRS Slopes for Detection and Characterization of Myocardial Ischemia

In this study, the upward (IUS) and downward (IDS) slopes of the QRS complex are proposed as indices for quantifying ischemia-induced electrocardiogram (ECG) changes. Using ECG recordings acquired before and during percutaneous transluminal coronary angioplasty (PTCA), it is found that the QRS slopes are considerably less steep during artery occlusion, in particular for IDS. With respect to ischemia detection, the slope indices outperform the often used high-frequency index (defined as the root mean square (rms) of the bandpass-filtered QRS signal for the frequency band 150-250 Hz) as the mean relative factors of change are much larger for IUS and IDS than for the high-frequency index (6.9 and 7.3 versus 3.7). The superior performance of the slope indices is equally valid when other frequency bands of the high-frequency index are investigated (the optimum one is found to be 125-175 Hz). Employing a simulation model in which the slopes of a template QRS are altered by different techniques, it is found that the slope changes observed during PTCA are mostly due to a widening of the QRS complex or a decrease of its amplitudes, but not a reduction of its high-frequency content or a combination of this and the previous effects. It is concluded that QRS slope information can be used as an adjunct to the conventional ST segment analysis in the monitoring of myocardial ischemia.

Comprehensive T wave Morphology Assessment in a Randomized Clinical Study of Dofetilide, Quinidine, Ranolazine, and Verapamil

Background Congenital long QT syndrome type 2 (abnormal hERG potassium channel) patients can develop flat, asymmetric, and notched T waves. Similar observations have been made with a limited number of hERG‐blocking drugs. However, it is not known how additional calcium or late sodium block, that can decrease torsade risk, affects T wave morphology. Methods and Results Twenty‐two healthy subjects received a single dose of a pure hERG blocker (dofetilide) and 3 drugs that also block calcium or sodium (quinidine, ranolazine, and verapamil) as part of a 5‐period, placebo‐controlled cross‐over trial. At pre‐dose and 15 time‐points post‐dose, ECGs and plasma drug concentration were assessed. Patch clamp experiments were performed to assess block of hERG, calcium (L‐type) and late sodium currents for each drug. Pure hERG block (dofetilide) and strong hERG block with lesser calcium and late sodium block (quinidine) caused substantial T wave morphology changes (P<0.001). Strong late sodium current and hERG block (ranolazine) still caused T wave morphology changes (P<0.01). Strong calcium and hERG block (verapamil) did not cause T wave morphology changes. At equivalent QTc prolongation, multichannel blockers (quinidine and ranolazine) caused equal or greater T wave morphology changes compared with pure hERG block (dofetilide). Conclusions T wave morphology changes are directly related to amount of hERG block; however, with quinidine and ranolazine, multichannel block did not prevent T wave morphology changes. A combined approach of assessing multiple ion channels, along with ECG intervals and T wave morphology may provide the greatest insight into drug‐ion channel interactions and torsade de pointes risk. Clinical Trial Registration URL: http://clinicaltrials.gov/ Unique identifier: NCT01873950.

Mechanisms of ventricular rate adaptation as a predictor of arrhythmic risk

Protracted QT interval (QTI) adaptation to abrupt heart rate (HR) changes has been identified as a clinical arrhythmic risk marker. This study investigates the ionic mechanisms of QTI rate adaptation and its relationship to arrhythmic risk. Computer simulations and experimental recordings in human and canine ventricular tissue were used to investigate the ionic basis of QTI and action potential duration (APD) to abrupt changes in HR with a protocol commonly used in clinical studies. The time for 90% QTI adaptation is 3.5 min in simulations, in agreement with experimental and clinical data in humans. APD adaptation follows similar dynamics, being faster in mid-myocardial cells (2.5 min) than in endocardial and epicardial cells (3.5 min). Both QTI and APD adapt in two phases following an abrupt HR change: a fast initial phase with time constant < 30 s, mainly related to L-type calcium and slow-delayed rectifier potassium current, and a second slow phase of >2 min driven by intracellular sodium concentration ([Na(+)](i)) dynamics. Alterations in [Na(+)](i) dynamics due to Na(+)/K(+) pump current inhibition result in protracted rate adaptation and are associated with increased proarrhythmic risk, as indicated by action potential triangulation and faster L-type calcium current recovery from inactivation, leading to the formation of early afterdepolarizations. In conclusion, this study suggests that protracted QTI adaptation could be an indicator of altered [Na(+)](i) dynamics following Na(+)/K(+) pump inhibition as it occurs in patients with ischemia or heart failure. An increased risk of cardiac arrhythmias in patients with protracted rate adaptation may be due to an increased risk of early after-depolarization formation.

QT variability and HRV interactions in ECG: quantification and reliability

In this paper, a dynamic linear approach was used over QT and RR series measured by an automatic delineator, to explore the interactions between QT interval variability (QTV) and heart rate variability (HRV). A low-order linear autoregressive model allowed to separate and quantify the QTV fractions correlated and not correlated with HRV, estimating their power spectral density measures. Simulated series and artificial ECG signals were used to assess the performance of the methods, considering a respiratory-like electrical axis rotation effect and noise contamination with a signal-to-noise ratio (SNR) from 30 to 10 dB. The errors found in the estimation of the QTV fraction related to HRV showed a nonrelevant performance decrease from automatic delineation. The joint performance of delineation plus variability analysis achieved less than 20% error in over 75% of cases for records presenting SNRs higher than 15 dB and QT standard deviation higher than 10 ms. The methods were also applied to real ECG records from healthy subjects where it was found a relevant QTV fraction not correlated with HRV (over 40% in 19 out of 23 segments analyzed), indicating that an important part of QTV is not linearly driven by HRV and may contain complementary information.

Inter-subject variability in human atrial action potential in sinus rhythm versus chronic atrial fibrillation

Aims Human atrial electrophysiology exhibits high inter-subject variability in both sinus rhythm (SR) and chronic atrial fibrillation (cAF) patients. Variability is however rarely investigated in experimental and theoretical electrophysiological studies, thus hampering the understanding of its underlying causes but also its implications in explaining differences in the response to disease and treatment. In our study, we aim at investigating the ability of populations of human atrial cell models to capture the inter-subject variability in action potential (AP) recorded in 363 patients both under SR and cAF conditions. Methods and Results Human AP recordings in atrial trabeculae (n = 469) from SR and cAF patients were used to calibrate populations of computational SR and cAF atrial AP models. Three populations of over 2000 sampled models were generated, based on three different human atrial AP models. Experimental calibration selected populations of AP models yielding AP with morphology and duration in range with experimental recordings. Populations using the three original models can mimic variability in experimental AP in both SR and cAF, with median conductance values in SR for most ionic currents deviating less than 30% from their original peak values. All cAF populations show similar variations in GK1, GKur and Gto, consistent with AF-related remodeling as reported in experiments. In all SR and cAF model populations, inter-subject variability in IK1 and INaK underlies variability in APD90, variability in IKur, ICaL and INaK modulates variability in APD50 and combined variability in Ito and IKur determines variability in APD20. The large variability in human atrial AP triangulation is mostly determined by IK1 and either INaK or INaCa depending on the model. Conclusion Experimentally-calibrated human atrial AP models populations mimic AP variability in SR and cAF patient recordings, and identify potential ionic determinants of inter-subject variability in human atrial AP duration and morphology in SR versus cAF.

The Na+/K+ pump is an important modulator of refractoriness and rotor dynamics in human atrial tissue.

Pharmacological treatment of atrial fibrillation (AF) exhibits limited efficacy. Further developments require a comprehensive characterization of ionic modulators of electrophysiology in human atria. Our aim is to systematically investigate the relative importance of ionic properties in modulating excitability, refractoriness, and rotor dynamics in human atria before and after AF-related electrical remodeling (AFER). Computer simulations of single cell and tissue atrial electrophysiology were conducted using two human atrial action potential (AP) models. Changes in AP, refractory period (RP), conduction velocity (CV), and rotor dynamics caused by alterations in key properties of all atrial ionic currents were characterized before and after AFER. Results show that the investigated human atrial electrophysiological properties are primarily modulated by maximal value of Na(+)/K(+) pump current (G(NaK)) as well as conductances of inward rectifier potassium current (G(K1)) and fast inward sodium current (G(Na)). G(NaK) plays a fundamental role through both electrogenic and homeostatic modulation of AP duration (APD), APD restitution, RP, and reentrant dominant frequency (DF). G(K1) controls DF through modulation of AP, APD restitution, RP, and CV. G(Na) is key in determining DF through alteration of CV and RP, particularly in AFER. Changes in ionic currents have qualitatively similar effects in control and AFER, but effects are smaller in AFER. The systematic analysis conducted in this study unravels the important role of the Na(+)/K(+) pump current in determining human atrial electrophysiology.

Quantification of Restitution Dispersion From the Dynamic Changes of the

Action potential duration restitution (APDR) curves present spatial variations due to the electrophysiological heterogeneities present in the heart. Enhanced spatial APDR dispersion in ventricle has been suggested as an arrhythmic risk marker. In this study, we propose a method to noninvasively quantify dispersion of APDR slopes at tissue level by making only use of the surface electrocardiogram (ECG). The proposed estimate accounts for rate normalized differences in the steady-state T-wave peak to T-wave end interval (Tpe). A methodology is developed for its computation, which includes compensation for the Tpe memory lag after heart-rate (HR) changes. The capability of the proposed estimate to reflect APDR dispersion is assessed using a combination of ECG signal processing, and computational modeling and simulation. Specifically, ECG recordings of control subjects undergoing a tilt test trial are used to measure that estimate, while its capability to provide a quantification of APDR dispersion at tissue level is assessed by using a 2-D ventricular tissue simulation. From this simulation, APDR dispersion, denoted as ΔαSIM, is calculated, and pseudo-ECGs are derived. Estimates of APDR dispersion measured from the pseudo-ECGs show to correlate with ΔαSIM, being the mean relative error below 5%. A comparison of the ECG estimates obtained from tilt test recordings and the ΔαSIM values measured in silico simulations at tissue level show that differences between them are below 20%, which is within physiological variability limits. Our results provide evidence that the proposed estimate is a noninvasive measurement of APDR dispersion in ventricle. Additional results from this study confirm that Tpe adapts to HR changes much faster than the QT interval.

T

In this paper, we illustrate how advanced computational modelling and simulation can be used to investigate drug-induced effects on cardiac electrophysiology and on specific biomarkers of pro-arrhythmic risk. To do so, we first perform a thorough literature review of proposed arrhythmic risk biomarkers from the ionic to the electrocardiogram levels. The review highlights the variety of proposed biomarkers, the complexity of the mechanisms of drug-induced pro-arrhythmia and the existence of significant animal species differences in drug-induced effects on cardiac electrophysiology. Predicting drug-induced pro-arrhythmic risk solely using experiments is challenging both preclinically and clinically, as attested by the rise in the cost of releasing new compounds to the market. Computational modelling and simulation has significantly contributed to the understanding of cardiac electrophysiology and arrhythmias over the last 40 years. In the second part of this paper, we illustrate how state-of-the-art open source computational modelling and simulation tools can be used to simulate multi-scale effects of drug-induced ion channel block in ventricular electrophysiology at the cellular, tissue and whole ventricular levels for different animal species. We believe that the use of computational modelling and simulation in combination with experimental techniques could be a powerful tool for the assessment of drug safety pharmacology.