Effects of wall stress on the dynamics of ventricular fibrillation: a simulation study using a dynamic mechanoelectric model of ventricular tissue

Preclinical short QT syndrome models: studying the phenotype and drug-screening

Cardiovascular diseases are the main cause of sudden cardiac death (SCD) in developed and developing countries. Inherited cardiac channelopathies are linked to 5-10% of SCDs, mainly in the young. Short QT syndrome (SQTS) is a rare inherited channelopathy, which leads to both atrial and ventricular tachyarrhythmias, syncope, and even SCD. International European Society of Cardiology guidelines include as diagnostic criteria: (i) QTc ≤ 340 ms on electrocardiogram, (ii) QTc ≤ 360 ms plus one of the follwing, an affected short QT syndrome pathogenic gene mutation, or family history of SQTS, or aborted cardiac arrest, or family history of cardiac arrest in the young. However, further evaluation of the QTc ranges seems to be required, which might be possible by assembling large short QT cohorts and considering genetic screening of the newly described pathogenic mutations. Since the mechanisms underlying the arrhythmogenesis of SQTS is unclear, optimal therapy for SQTS is still lacking. The disease is rare, unclear genotype-phenotype correlations exist in a bevy of cases and the absence of an international short QT registry limit studies on the pathophysiological mechanisms of arrhythmogenesis and therapy of SQTS. This leads to the necessity of experimental models or platforms for studying SQTS. Here, we focus on reviewing preclinical SQTS models and platforms such as animal models, heterologous expression systems, human-induced pluripotent stem cell-derived cardiomyocyte models and computer models as well as three-dimensional engineered heart tissues. We discuss their usefulness for SQTS studies to examine genotype-phenotype associations, uncover disease mechanisms and test drugs. These models might be helpful for providing novel insights into the exact pathophysiological mechanisms of this channelopathy and may offer opportunities to improve the diagnosis and treatment of patients with SQT syndrome.

Cardiac Mechano-Electric Coupling: Acute Effects of Mechanical Stimulation on Heart Rate and Rhythm

The heart is vital for biological function in almost all chordates, including humans. It beats continually throughout our life, supplying the body with oxygen and nutrients while removing waste products. If it stops, so does life. The heartbeat involves precise coordination of the activity of billions of individual cells, as well as their swift and well-coordinated adaption to changes in physiological demand. Much of the vital control of cardiac function occurs at the level of individual cardiac muscle cells, including acute beat-by-beat feedback from the local mechanical environment to electrical activity (as opposed to longer term changes in gene expression and functional or structural remodeling). This process is known as mechano-electric coupling (MEC). In the current review, we present evidence for, and implications of, MEC in health and disease in human; summarize our understanding of MEC effects gained from whole animal, organ, tissue, and cell studies; identify potential molecular mediators of MEC responses; and demonstrate the power of computational modeling in developing a more comprehensive understanding of ‟what makes the heart tick.ˮ.

In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling

INTRODUCTION

Genetic forms of the Short QT Syndrome (SQTS) arise due to cardiac ion channel mutations leading to accelerated ventricular repolarization, arrhythmias and sudden cardiac death. Results from experimental and simulation studies suggest that changes to refractoriness and tissue vulnerability produce a substrate favorable to re-entry. Potential electromechanical consequences of the SQTS are less well-understood. The aim of this study was to utilize electromechanically coupled human ventricle models to explore electromechanical consequences of the SQTS.

METHODS AND RESULTS

The Rice et al. mechanical model was coupled to the ten Tusscher et al. ventricular cell model. Previously validated K(+) channel formulations for SQT variants 1 and 3 were incorporated. Functional effects of the SQTS mutations on [Ca(2+)] i transients, sarcomere length shortening and contractile force at the single cell level were evaluated with and without the consideration of stretch-activated channel current (I sac). Without I sac, at a stimulation frequency of 1Hz, the SQTS mutations produced dramatic reductions in the amplitude of [Ca(2+)] i transients, sarcomere length shortening and contractile force. When I sac was incorporated, there was a considerable attenuation of the effects of SQTS-associated action potential shortening on Ca(2+) transients, sarcomere shortening and contractile force. Single cell models were then incorporated into 3D human ventricular tissue models. The timing of maximum deformation was delayed in the SQTS setting compared to control.

CONCLUSION

The incorporation of I sac appears to be an important consideration in modeling functional effects of SQT 1 and 3 mutations on cardiac electro-mechanical coupling. Whilst there is little evidence of profoundly impaired cardiac contractile function in SQTS patients, our 3D simulations correlate qualitatively with reported evidence for dissociation between ventricular repolarization and the end of mechanical systole.

A tissue-level electromechanical model of the left ventricle: application to the analysis of intraventricular pressure

The ventricular pressure profile is characteristic of the cardiac contraction progress and is useful to evaluate the cardiac performance. In this contribution, a tissue-level electromechanical model of the left ventricle is proposed, to assist the interpretation of left ventricular pressure waveforms. The left ventricle has been modeled as an ellipsoid composed of twelve mechano-hydraulic sub-systems. The asynchronous contraction of these twelve myocardial segments has been represented in order to reproduce a realistic pressure profiles. To take into account the different energy domains involved, the tissue-level scale and to facilitate the building of a modular model, multiple formalisms have been used: Bond Graph formalism for the mechano-hydraulic aspects and cellular automata for the electrical activation. An experimental protocol has been defined to acquire ventricular pressure signals from three pigs, with different afterload conditions. Evolutionary Algorithms have been used to identify the model parameters in order to minimize the error between experimental and simulated ventricular pressure signals. Simulation results show that the model is able to reproduce experimental ventricular pressure. In addition, electro-mechanical activation times have been determined in the identification process. For example, the maximum electrical activation time is reached, respectively, 96.5, 139.3 and 131.5 ms for the first, second, and third pigs. These preliminary results are encouraging for the application of the model on non-invasive data like ECG, arterial pressure or myocardial strain.

Global coupling in excitable media provides a simplified description of mechanoelectrical feedback in cardiac tissue

Cardiac mechanoelectric feedback can play an important role in different heart pathologies. In this paper, we show that mechanoelectric models which describe both the electric propagation and the mechanic contraction of cardiac tissue naturally lead to close systems of equations with global coupling among the variables. This point is exemplified using the Nash-Panfilov model, which reduces to a FitzHugh-Nagumo-type equation with global coupling in the linear elastic regime. We explain the appearance of self-oscillatory regimes in terms of the system nullclines and describe the different dynamical attractors. Finally, we study their basin of attraction in terms of the system size and the strength of the stretch-induced currents.