Mathematical modeling and simulation of ventricular activation sequences: implications for cardiac resynchronization therapy

A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution

Computational modeling of electrophysiological properties of the rabbit heart is a commonly used way to enhance and/or complement findings from classic lab work on single cell or tissue levels. Yet, thus far, there was no possibility to extend the scope to include the resulting body surface potentials as a way of validation or to investigate the effect of certain pathologies. Based on CT imaging, we developed the first openly available computational geometrical model not only of the whole heart but also the complete torso of the rabbit. Additionally, we fabricated a 32-lead ECG-vest to record body surface potential signals of the aforementioned rabbit. Based on the developed geometrical model and the measured signals, we then optimized the activation sequence of the ventricles, recreating the functionality of the Purkinje network, and we investigated different apico-basal and transmural gradients in action potential duration. Optimization of the activation sequence resulted in an average root mean square error between measured and simulated signal of 0.074 mV/ms for all leads. The best-fit T-Wave, compared to measured data (0.038 mV/ms), resulted from incorporating an action potential duration gradient from base to apex with a respective shortening of 20 ms and a transmural gradient with a shortening of 15 ms from endocardium to epicardium. By making our model and measured data openly available, we hope to give other researchers the opportunity to verify their research, as well as to create the possibility to investigate the impact of electrophysiological alterations on body surface signals for translational research.

Implantable Cardioverter-Defibrillators With Versus Without Resynchronization Therapy in Patients With a QRS Duration >180 ms

BACKGROUND

More than 20% of Medicare beneficiaries receiving cardiac resynchronization therapy defibrillators (CRT-D) have a very wide (≥180 ms) QRS complex duration (QRSD). Outcomes of CRT-D in these patients are not well-established because they have been underrepresented in clinical trials.

OBJECTIVES

This study examined outcomes in patients with CRT-D in a very wide QRSD with left bundle branch block (LBBB) versus those without LBBB.

METHODS

Medicare patients from the Implantable Cardioverter Defibrillator Registry (January 1, 2005, through April 30, 2006) with a CRT-D and confirmed Class I or IIa indications for CRT-D were matched to implantable cardioverter-defibrillator (ICD) patients without CRT despite having Class I or IIa indications for CRT. Mortality and heart failure hospitalizations longer than 4 years with CRT-D versus standard ICDs based on a QRSD and morphology were analyzed.

RESULTS

We analyzed 24,960 patients. Among those with LBBB, patients with a QRSD ≥180 ms had a greater adjusted survival benefit with CRT-D versus standard ICD (hazard ration [HR] for death: 0.65; 95% confidence interval [CI]: 0.59 to 0.72) compared with those having a QRSD 120 to 149 ms (HR: 0.85; 95% CI: 0.80 to 0.92) and 150 to 179 ms (HR: 0.87; 95% CI: 0.81 to 0.93). CRT-D versus ICD was associated with an improvement in survival in those with LBBB and a QRSD ≥180 ms (adjusted HR for death: 0.78; 95% CI: 0.68 to 0.91), but not in those with LBBB and a QRSD 150 to 179 ms (adjusted HR for death: 1.06; 95% CI: 0.95 to 1.19).

CONCLUSIONS

Improvements in both survival and heart failure hospitalizations with CRT-D were greatest in patients with a QRSD ≥180 ms with or without LBBB, whereas patients with a QRSD 150 to 179 ms without LBBB had no improvement in survival with CRT-D, and those with a QRSD 150 to 179 ms and LBBB had only a modest improvement.

Implementation of Contraction to Electrophysiological Ventricular Myocyte Models, and Their Quantitative Characterization via Post-Extrasystolic Potentiation

Heart failure (HF) affects over 5 million Americans and is characterized by impairment of cellular cardiac contractile function resulting in reduced ejection fraction in patients. Electrical stimulation such as cardiac resynchronization therapy (CRT) and cardiac contractility modulation (CCM) have shown some success in treating patients with HF. Computer simulations have the potential to help improve such therapy (e.g. suggest optimal lead placement) as well as provide insight into the underlying mechanisms which could be beneficial. However, these myocyte models require a quantitatively accurate excitation-contraction coupling such that the electrical and contraction predictions are correct. While currently there are close to a hundred models describing the detailed electrophysiology of cardiac cells, the majority of cell models do not include the equations to reproduce contractile force or they have been added ad hoc. Here we present a systematic methodology to couple first generation contraction models into electrophysiological models via intracellular calcium and then compare the resulting model predictions to experimental data. This is done by using a post-extrasystolic pacing protocol, which captures essential dynamics of contractile forces. We found that modeling the dynamic intracellular calcium buffers is necessary in order to reproduce the experimental data. Furthermore, we demonstrate that in models the mechanism of the post-extrasystolic potentiation is highly dependent on the calcium released from the Sarcoplasmic Reticulum. Overall this study provides new insights into both specific and general determinants of cellular contractile force and provides a framework for incorporating contraction into electrophysiological models, both of which will be necessary to develop reliable simulations to optimize electrical therapies for HF.

Patient-specific modelling of cardiac electrophysiology in heart-failure patients

Aims

Left-ventricular (LV) conduction disturbances are common in heart-failure patients and a left bundle-branch block (LBBB) electrocardiogram (ECG) type is often seen. The precise cause of this pattern is uncertain and is probably variable between patients, ranging from proximal interruption of the left bundle branch to diffuse distal conduction disease in the working myocardium. Using realistic numerical simulation methods and patient-tailored model anatomies, we investigated different hypotheses to explain the observed activation order on the LV endocardium, electrogram morphologies, and ECG features in two patients with heart failure and LBBB ECG.

Methods and results

Ventricular electrical activity was simulated using reaction–diffusion models with patient-specific anatomies. From the simulated action potentials, ECGs and cardiac electrograms were computed by solving the bidomain equation. Model parameters such as earliest activation sites, tissue conductivity, and densities of ionic currents were tuned to reproduce the measured signals. Electrocardiogram morphology and activation order could be matched simultaneously. Local electrograms matched well at some sites, but overall the measured waveforms had deeper S-waves than the simulated waveforms.

Conclusion

Tuning a reaction–diffusion model of the human heart to reproduce measured ECGs and electrograms is feasible and may provide insights in individual disease characteristics that cannot be obtained by other means.

Imaging of Ventricular Fibrillation and Defibrillation: The Virtual Electrode Hypothesis

Ventricular fibrillation is the major underlying cause of sudden cardiac death. Understanding the complex activation patterns that give rise to ventricular fibrillation requires high resolution mapping of localized activation. The use of multi-electrode mapping unraveled re-entrant activation patterns that underlie ventricular fibrillation. However, optical mapping contributed critically to understanding the mechanism of defibrillation, where multi-electrode recordings could not measure activation patterns during and immediately after a shock. In addition, optical mapping visualizes the virtual electrodes that are generated during stimulation and defibrillation pulses, which contributed to the formulation of the virtual electrode hypothesis. The generation of virtual electrode induced phase singularities during defibrillation is arrhythmogenic and may lead to the induction of fibrillation subsequent to defibrillation. Defibrillating with low energy may circumvent this problem. Therefore, the current challenge is to use the knowledge provided by optical mapping to develop a low energy approach of defibrillation, which may lead to more successful defibrillation.

Fibroblast-myocyte electrotonic coupling: does it occur in native cardiac tissue?

Heterocellular electrotonic coupling between cardiac myocytes and non-excitable connective tissue cells has been a long-established and well-researched fact in vitro. Whether or not such coupling exists in vivo has been a matter of considerable debate. This paper reviews the development of experimental insight and conceptual views on this topic, describes evidence in favour of and against the presence of such coupling in native myocardium, and identifies directions for further study needed to resolve the riddle, perhaps less so in terms of principal presence which has been demonstrated, but undoubtedly in terms of extent, regulation, patho-physiological context, and actual relevance of cardiac myocyte–non-myocyte coupling in vivo. This article is part of a Special Issue entitled "Myocyte-Fibroblast Signalling in Myocardium."

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Electrical coupling of cardiomyocytes and fibroblasts is well-established in vitro

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Whether such hetero-cellular coupling exists in vivo has been a matter of debate

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We review the development of experimental and conceptual insight into the topic

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Conclusion 1: hetero-cellular coupling in heart tissue has been shown in principle

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Conclusion 2: extent, regulation, context, and relevance remain to be established

In silico study of the haemodynamic effects induced by mechanical ventilation and biventricular pacemaker

In silico modeling of the cardiovascular system (CVS) can help both in understanding pharmacological or pathophysiological process and in providing information which could not be obtained by means of traditional clinical research methods due to practical or ethical reasons. In this work the numerical CVS was used to study the effect of interaction between mechanical ventilation and biventricular pacemaker by haemodynamic and energetic point of view. Starting from literature data on patients with intra and/or inter-ventricular activation time delay and treated using biventricular pacemaker, we used in silico simulator to analyse the effects induced by mechanical ventilatory assistance (MVA). After reproducing baseline and CRT conditions, the MVA was simulated changing the mean intrathoracic pressure value. Results show that simultaneous application of CRT and MVA yields a reduction of cardiac output, left ventricular end-diastolic and end-systolic volume when positive mean intrathoracic pressure is applied. In the same conditions, when MVA is applied, left ventricular ejection fraction, mean left (right) atrial and pulmonary arterial pressure increase.

Modeling cardiac electromechanics and mechanoelectrical coupling in dyssynchronous and failing hearts: insight from adaptive computer models

Computer models have become more and more a research tool to obtain mechanistic insight in the effects of dyssynchrony and heart failure. Increasing computational power in combination with increasing amounts of experimental and clinical data enables the development of mathematical models that describe electrical and mechanical behavior of the heart. By combining models based on data at the molecular and cellular level with models that describe organ function, so-called multi-scale models are created that describe heart function at different length and time scales. In this review, we describe basic modules that can be identified in multi-scale models of cardiac electromechanics. These modules simulate ionic membrane currents, calcium handling, excitation-contraction coupling, action potential propagation, and cardiac mechanics and hemodynamics. In addition, we discuss adaptive modeling approaches that aim to address long-term effects of diseases and therapy on growth, changes in fiber orientation, ionic membrane currents, and calcium handling. Finally, we discuss the first developments in patient-specific modeling. While current models still have shortcomings, well-chosen applications show promising results on some ultimate goals: understanding mechanisms of dyssynchronous heart failure and tuning pacing strategy to a particular patient, even before starting the therapy.