Computational rabbit models to investigate the initiation, perpetuation, and termination of ventricular arrhythmia

Fibroblast growth factor homologous factors: canonical and non-canonical mechanisms of action

Since their discovery nearly 30 years ago, fibroblast growth factor homologous factors (FHFs) are now known to control the functionality of excitable tissues through a range of mechanisms. Nervous and cardiac system dysfunctions are caused by loss- or gain-of-function mutations in FHF genes. The best understood 'canonical' targets for FHF action are voltage-gated sodium channels, and recent studies have expanded the repertoire of ways that FHFs modulate sodium channel gating. Additional 'non-canonical' functions of FHFs in excitable and non-excitable cells, including cancer cells, have been reported over the past dozen years. This review summarizes and evaluates reported canonical and non-canonical FHF functions.

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.

Low-energy, single-pulse surface stimulation defibrillates large mammalian ventricles

BACKGROUND

Strong electric shocks are the gold standard for ventricular defibrillation but are associated with pain and tissue damage. We hypothesized that targeting the excitable gap (EG) of reentry with low-energy surface stimulation is a less damaging and painless alternative for ventricular defibrillation.

OBJECTIVE

The purpose of this study was to determine the conditions under which low-energy surface stimulation defibrillates large mammalian ventricles.

METHODS

Low-energy surface stimulation was delivered with five electrodes that were 7 cm long and placed 1-2 cm apart on the endocardial and epicardial surfaces of perfused pig left ventricle (LV). Rapid pacing (>4 Hz) was used to induce reentry from a single electrode. A 2 ms defibrillation pulse ≤0.5 A was delivered from all electrodes with a varied time delay from the end of the induction protocol (0.1-5 seconds). Optical mapping was performed and arrhythmia dynamics analyzed. For mechanistic insight, simulations of the VF induction and defibrillation protocols were performed in silico with an LV model emulating the experimental conditions and electrodes placed 0.25-2 cm apart.

RESULTS

In living LV, reentry was induced with varying complexity and dominant frequencies ranging between 3.5 to 6.2 Hz over 8 seconds postinitiation. Low-energy defibrillation was achieved with energy <60 mJ and electrode separations up to 2 cm for less complex arrhythmia. In simulations, defibrillation consistently occurred when stimulation captured >75% of the EG, which blocked reentry <2.9 mm in front of the leading reentrant wavefront.

CONCLUSION

Defibrillation with low-energy, single-pulse surface stimulation is feasible with energies below the human pain threshold (100 mJ). Optimal defibrillation occurs when arrhythmia complexity is minimal and electrodes capture >75% of the EG.

A comprehensive, multiscale framework for evaluation of arrhythmias arising from cell therapy in the whole post-myocardial infarcted heart

Direct remuscularization approaches to cell-based heart repair seek to restore ventricular contractility following myocardial infarction (MI) by introducing new cardiomyocytes (CMs) to replace lost or injured ones. However, despite promising improvements in cardiac function, high incidences of ventricular arrhythmias have been observed in animal models of MI injected with pluripotent stem cell-derived cardiomyocytes (PSC-CMs). The mechanisms of arrhythmogenesis remain unclear. Here, we present a comprehensive framework for computational modeling of direct remuscularization approaches to cell therapy. Our multiscale 3D whole-heart modeling framework integrates realistic representations of cell delivery and transdifferentiation therapy modalities as well as representation of spatial distributions of engrafted cells, enabling simulation of clinical therapy and the prediction of emergent electrophysiological behavior and arrhythmogenensis. We employ this framework to explore how varying parameters of cell delivery and transdifferentiation could result in three mechanisms of arrhythmogenesis: focal ectopy, heart block, and reentry.

Analysis of heterogeneous cardiac pacemaker tissue models and traveling wave dynamics

The sinoatrial-node (SAN) is a complex heterogeneous tissue that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how this tissue remains stable is lacking. Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker tissue models. In this study, we adapt a recent model of pacemaker cells (Severi et al., 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells, in particular "center" and "peripheral" cells with distinct intrinsic frequencies and action potential morphology. Large-scale simulations of the SAN tissue, represented by a heterogeneous tissue structure of pacemaker cells, exhibit a rich repertoire of behaviors, including complete synchrony, traveling waves of activity originating from periphery to center, and transient traveling waves originating from the center. We use phase reduction methods that do not require fully simulating the large-scale model to capture these observations. Moreover, the phase reduced models accurately predict key properties of the tissue electrical dynamics, including wave frequencies when synchronization occurs, and wave propagation direction in a variety of tissue models. With the reduced phase models, we analyze the relationship between cell distributions and coupling strengths and the resulting transient dynamics. Further, the reduced phase model predicts parameter regimes of irregular electrical dynamics. Thus, we demonstrate that phase reduced oscillator models applied to realistic pacemaker tissue is a useful tool for investigating the spatial-temporal dynamics of cardiac pacemaker activity.

Automatic estimation of Purkinje-Myocardial junction hot-spots from noisy endocardial samples: A simulation study

The reconstruction of the ventricular cardiac conduction system (CCS) from patient-specific data is a challenging problem. High-resolution imaging techniques have allowed only the segmentation of proximal sections of the CCS from images acquired ex vivo. In this paper, we present an algorithm to estimate the location of a set of Purkinje-myocardial junctions (PMJs) from electro-anatomical maps, as those acquired during radio-frequency ablation procedures. The method requires a mesh representing the myocardium with local activation time measurements on a subset of nodes. We calculate the backwards propagation of the electrical signal from the measurement points to all the points in the mesh to define a set of candidate PMJs that is iteratively refined. The algorithm has been tested on several Purkinje network configurations, with simulated activation maps, subject to different error amplitudes. The results show that the method is able to build a set of PMJs that explain the observed activation map for different synthetic CCS configurations. In the tests, the average error in the predicted activation time is below the amplitude of the error applied to the data.

Effect of ventricular myocardium characteristics on the defibrillation threshold

Myocardium characteristics differ markedly among individuals and play an important role in defibrillation threshold. The accuracy of simulation models used in most published studies are still have room to be improved and most of them only discussed the effect of myocardial anisotropy on defibrillation threshold. In our manuscript, a rabbit ventricular finite-element (FE) volume conductor model with high precision was constructed. Ventricular myocardium characteristics include cardiomyocyte coupling and the degree of myocardial anisotropy, which are represented as the value and the ratio of anisotropic conductivity, respectively. Quantitative analysis was performed simultaneously in terms of cardiomyocyte coupling and the degree of myocardial anisotropy. Based on this, the combined effects of these two factors were further discussed. The electric field distributions of shocks and the defibrillation thresholds under different myocardial characteristics were simulated on this model. The simulation results revealed that as the degree of myocardial anisotropy increases, defibrillation threshold increases, and cardiomyocyte decoupling (decrease in electrical conductivity) can considerably increase the defibrillation threshold.

Cardiac ischemia-insights from computational models

BACKGROUND

Complementary to clinical and experimental studies, computational cardiac modeling serves to obtain a comprehensive understanding of the cardiovascular system in order to analyze dysfunction, evaluate existing, and develop novel treatment strategies.

OBJECTIVES

We describe the basics of multiscale computational modeling of cardiac electrophysiology from the molecular ion channel to the whole body scale. By modeling cardiac ischemia, we illustrate how in silico experiments can contribute to our understanding of how the pathophysiological mechanisms translate into changes observed in diagnostic tools such as the electrocardiogram (ECG).

MATERIALS AND METHODS

Quantitative in silico modeling spans a wide range of scales from ion channel biophysics to ECG signals. For each of the scales, a set of mathematical equations describes electrophysiology in relation to the other scales. Integration of ischemia-induced changes is performed on the ion channel, single-cell, and tissue level. This approach allows us to study how effects simulated at molecular scales translate to changes in the ECG.

RESULTS

Ischemia induces action potential shortening and conduction slowing. Hence, ischemic myocardium has distinct and significant effects on propagation and repolarization of excitation, depending on the intramural extent of the ischemic region. For transmural and subendocardial ischemic regions, ST segment elevation and depression, respectively, were observed, whereas intermediate ischemic regions were found to be electrically silent (NSTEMI).

CONCLUSIONS

In silico modeling contributes quantitative and mechanistic insight into fundamental ischemia-related arrhythmogenic mechanisms. In addition, computational modeling can help to translate experimental findings at the (sub-)cellular level to the organ and body context (e. g., ECG), thereby providing a thorough understanding of this routinely used diagnostic tool that may translate into optimized applications.

Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia

Computational modelling, combined with experimental investigations, is a powerful method for investigating complex cardiac electrophysiological behaviour. The use of rabbit-specific models, due to the similarities of cardiac electrophysiology in this species with human, is especially prevalent. In this paper, we first briefly review rabbit-specific computational modelling of ventricular cell electrophysiology, multi-cellular simulations including cellular heterogeneity, and acute ischemia. This mini-review is followed by an original computational investigation of variability in the electrophysiological response of two experimentally-calibrated populations of rabbit-specific ventricular myocyte action potential models to acute ischemia. We performed a systematic exploration of the response of the model populations to varying degrees of ischemia and individual ischemic parameters, to investigate their individual and combined effects on action potential duration and refractoriness. This revealed complex interactions between model population variability and ischemic factors, which combined to enhance variability during ischemia. This represents an important step towards an improved understanding of the role that physiological variability may play in electrophysiological alterations during acute ischemia.

Rabbit models as tools for preclinical cardiac electrophysiological safety testing: Importance of repolarization reserve

It is essential to more reliably assess the pro-arrhythmic liability of compounds in development. Current guidelines for pre-clinical and clinical testing of drug candidates advocate the use of healthy animals/tissues and healthy individuals and focus on the test compound's ability to block the hERG current and prolong cardiac ventricular repolarization. Also, pre-clinical safety tests utilize several species commonly used in cardiac electrophysiological studies. In this review, important species differences in cardiac ventricular repolarizing ion currents are considered, followed by the discussion on electrical remodeling associated with chronic cardiovascular diseases that leads to altered ion channel and transporter expression and densities in pathological settings. We argue that the choice of species strongly influences experimental outcome and extrapolation of results to human clinical settings. We suggest that based on cardiac cellular electrophysiology, the rabbit is a useful species for pharmacological pro-arrhythmic investigations. In addition to healthy animals and tissues, the use of animal models (e.g. those with impaired repolarization reserve) is suggested that more closely resemble subsets of patients exhibiting increased vulnerability towards the development of ventricular arrhythmias and sudden cardiac death.