A simple model of the right atrium of the human heart with the sinoatrial and atrioventricular nodes included

The virtual sinoatrial node: What did computational models tell us about cardiac pacemaking?

Since its discovery, the sinoatrial node (SAN) has represented a fascinating and complex matter of research. Despite over a century of discoveries, a full comprehension of pacemaking has still to be achieved. Experiments often produced conflicting evidence that was used either in support or against alternative theories, originating intense debates. In this context, mathematical descriptions of the phenomena underlying the heartbeat have grown in importance in the last decades since they helped in gaining insights where experimental evaluation could not reach. This review presents the most updated SAN computational models and discusses their contribution to our understanding of cardiac pacemaking. Electrophysiological, structural and pathological aspects - as well as the autonomic control over the SAN - are taken into consideration to reach a holistic view of SAN activity.

Model Systems for Addressing Mechanism of Arrhythmogenesis in Cardiac Repair

PURPOSE OF REVIEW

Cardiac cell-based therapy represents a promising approach for cardiac repair. However, one of the main challenges is cardiac arrhythmias associated with stem cell transplantation. The current review summarizes the recent progress in model systems for addressing mechanisms of arrhythmogenesis in cardiac repair.

RECENT FINDINGS

Animal models have been extensively developed for mechanistic studies of cardiac arrhythmogenesis. Advances in human induced pluripotent stem cells (hiPSCs), patient-specific disease models, tissue engineering, and gene editing have greatly enhanced our ability to probe the mechanistic bases of cardiac arrhythmias. Additionally, recent development in multiscale computational studies and machine learning provides yet another powerful tool to quantitatively decipher the mechanisms of cardiac arrhythmias. Advancing efforts towards the integrations of experimental and computational studies are critical to gain insights into novel mitigation strategies for cardiac arrhythmias in cell-based therapy.

Calibration of ionic and cellular cardiac electrophysiology models

Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.

Rotors Detected by Phase Analysis of Filtered, Epicardial Atrial Fibrillation Electrograms Colocalize With Regions of Conduction Block

BACKGROUND

Several recent studies suggest rotors detected by phase mapping may act as main drivers of persistent atrial fibrillation. However, the electrophysiological nature of detected rotors remains unclear. We performed a direct, 1:1 comparison between phase and activation time mapping in high-density, epicardial, direct-contact mapping files of human atrial fibrillation.

METHODS

Thirty-eight unipolar electrogram files of 10 s duration were recorded in patients with atrial fibrillation (n=20 patients) using a 16×16 electrode array placed on the epicardial surface of the left atrial posterior wall or the right atrial free wall. Phase maps and isochrone wave maps were constructed for all recordings. For each detected phase singularity (PS) with a lifespan of >1 cycle length, the corresponding conduction pattern was investigated in the isochrone wave maps.

RESULTS

When using sinusoidal recomposition and Hilbert Transform, 138 PSs were detected. One hundred and four out of 138 PSs were detected within 1 electrode distance (1.5 mm) from a line of conduction block between nonrotating wavefronts detected by activation mapping. Far fewer rotating wavefronts were detected when rotating activity was identified based on wave mapping (18 out of 8219 detected waves). Fourteen out of these 18 cases were detected as PSs in phase mapping. Phase analysis of filtered electrograms produced by simulated wavefronts separated by conduction block also identified PSs on the line of conduction block.

CONCLUSIONS

PSs identified by phase analysis of filtered epicardial electrograms colocalize with conduction block lines identified by activation mapping. Detection of PSs using phase analysis has a low specificity for identifying rotating wavefronts during human atrial fibrillation using activation mapping.

Heart Rhythm Insights Into Structural Remodeling in Atrial Tissue: Timed Automata Approach

The heart rhythm of a person following heart transplantation (HTX) is assumed to display an intrinsic cardiac rhythm because it is significantly less influenced by the autonomic nervous system-the main source of heart rate variability in healthy people. Therefore, such a rhythm provides evidence for arrhythmogenic processes developing, usually silently, in the cardiac tissue. A model is proposed to simulate alterations in the cardiac tissue and to observe the effects of these changes on the resulting heart rhythm. The hybrid automata framework used makes it possible to represent reliably and simulate efficiently both the electrophysiology of a cardiac cell and the tissue organization. The curve fitting method used in the design of the hybrid automaton cycle follows the well-recognized physiological phases of the atrial myocyte membrane excitation. Moreover, knowledge of the complex architecture of the right atrium, the ability of the almost free design of intercellular connections makes the automata approach the only one possible. Two particular aspects are investigated: impairment of the impulse transmission between cells and structural changes in intercellular connections. The first aspect models the observed fatigue of cells due to specific cardiac tissue diseases. The second aspect simulates the increase in collagen deposition with aging. Finally, heart rhythms arising from the model are validated with the sinus heart rhythms recorded in HTX patients. The modulation in the impairment of the impulse transmission between cells reveals qualitatively the abnormally high heart rate variability observed in patients living long after HTX.

Computational assessment of the functional role of sinoatrial node exit pathways in the human heart

AIM

The human right atrium and sinoatrial node (SAN) anatomy is complex. Optical mapping experiments suggest that the SAN is functionally insulated from atrial tissue except at discrete SAN-atrial electrical junctions called SAN exit pathways, SEPs. Additionally, histological imaging suggests the presence of a secondary pacemaker close to the SAN. We hypothesise that a) an insulating border-SEP anatomical configuration is related to SAN arrhythmia; and b) a secondary pacemaker, the paranodal area, is an alternate pacemaker but accentuates tachycardia. A 3D electro-anatomical computational model was used to test these hypotheses.

METHODS

A detailed 3D human SAN electro-anatomical mathematical model was developed based on our previous anatomical reconstruction. Electrical activity was simulated using tissue specific variants of the Fenton-Karma action potential equations. Simulation experiments were designed to deploy this complex electro-anatomical system to assess the roles of border-SEPs and paranodal area by mimicking experimentally observed SAN arrhythmia. Robust and accurate numerical algorithms were implemented for solving the mono domain reaction-diffusion equation implicitly, calculating 3D filament traces, and computing dominant frequency among other quantitative measurements.

RESULTS

A centre to periphery gradient of increasing diffusion was sufficient to permit initiation of pacemaking at the centre of the 3D SAN. Re-entry within the SAN, micro re-entry, was possible by imposing significant SAN fibrosis in the presence of the insulating border. SEPs promoted the micro re-entry to generate more complex SAN-atrial tachycardia. Simulation of macro re-entry, i.e. re-entry around the SAN, was possible by inclusion of atrial fibrosis in the presence of the insulating border. The border shielded the SAN from atrial tachycardia. However, SAN micro-structure intercellular gap junctional coupling and the paranodal area contributed to prolonged atrial fibrillation. Finally, the micro-structure was found to be sufficient to explain shifts of leading pacemaker site location.

CONCLUSIONS

The simulations establish a relationship between anatomy and SAN electrical function. Microstructure, in the form of intercellular gap junction coupling, was found to regulate SAN function and arrhythmia.

Calcium dynamics in cardiac excitatory and non-excitatory cells and the role of gap junction

Calcium ions aid in the generation of action potential in myocytes and are responsible for the excitation-contraction coupling of heart. The heart muscle has specialized patches of cells, called excitatory cells (EC) such as the Sino-atrial node cells capable of auto-generation of action potential and cells which receive signals from the excitatory cells, called non-excitatory cells (NEC) such as cells of the ventricular and auricular walls. In order to understand cardiac calcium homeostasis, it is, therefore, important to study the calcium dynamics taking into account both types of cardiac cells. Here we have developed a model to capture the calcium dynamics in excitatory and non-excitatory cells taking into consideration the gap junction mediated calcium ion transfer from excitatory cell to non-excitatory cell. Our study revealed that the gap junctional coupling between excitatory and non-excitatory cells plays important role in the calcium dynamics. It is observed that any reduction in the functioning of gap junction may result in abnormal calcium oscillations in NEC, even when the calcium dynamics is normal in EC cell. Sensitivity of gap junction is observed to be independent of the pacing rate and hence a careful monitoring is required to maintain normal cardiomyocyte condition. It also highlights that sarcoplasmic reticulum may not be always able to control the amount of cytoplasmic calcium under the condition of calcium overload.

Mathematical model of the atrioventricular nodal double response tachycardia and double-fire pathology

A proposed model consisting of two coupled models (Hodgkin-Huxley and Yanagihara-Noma-Irisawa model) is considered as a description of the heart's action potential. System of ordinary differential equations is used to recreate pathological behaviour in the conducting heart's system such as double fire and the most common tachycardia: atrioventricular nodal reentrant tachycardia (AVNRT). Part of the population has an abnormal accessory pathways: fast and slow (Fujiki, 2008). These pathways in the atrioventricular node (AV node) are anatomical and functional contributions of supraventricular tachycardia. However, the appearance of two pathways in the AV node may be a contribution of arrhythmia, which is caused by coexistent conduction by two pathways (called double fire). The difference in the conduction time between these pathways is the most important factor. This is the reason to introduce three types of couplings and delay to our system in order to reproduce various types of the AVNRT. In our research, introducing the feedback loops and couplings entails the creation of waves which can correspond to the re-entry waves occurring in the AVNRT. Our main aim is to study solutions of the given equations and take into consideration the influence of feedback and delays which occur in these pathological modes. We also present stability analysis for both components, that is Hodgkin-Huxley and Yanagihara-Noma-Irisawa models, as well as for the final double-fire model.

Reentry and Ectopic Pacemakers Emerge in a Three-Dimensional Model for a Slab of Cardiac Tissue with Diffuse Microfibrosis near the Percolation Threshold

Arrhythmias in cardiac tissue are generally associated with irregular electrical wave propagation in the heart. Cardiac tissue is formed by a discrete cell network, which is often heterogeneous. Recently, it was shown in simulations of two-dimensional (2D) discrete models of cardiac tissue that a wave crossing a fibrotic, heterogeneous region may produce reentry and transient or persistent ectopic activity provided the fraction of conducting connections is just above the percolation threshold. Here, we investigate the occurrence of these phenomena in three-dimensions by simulations of a discrete model representing a thin slab of cardiac tissue. This is motivated (i) by the necessity to study the relevance and properties of the percolation-related mechanism for the emergence of microreentries in three dimensions and (ii) by the fact that atrial tissue is quite thin in comparison with ventricular tissue. Here, we simplify the model by neglecting details of tissue anatomy, e. g. geometries of atria or ventricles and the anisotropy in the conductivity. Hence, our modeling study is confined to the investigation of the effect of the tissue thickness as well as to the comparison of the dynamics of electrical excitation in a 2D layer with the one in a 3D slab. Our results indicate a strong and non-trivial effect of the thickness even for thin tissue slabs on the probability of microreentries and ectopic beat generation. The strong correlation of the occurrence of microreentry with the percolation threshold reported earlier in 2D layers persists in 3D slabs. Finally, a qualitative agreement of 3D simulated electrograms in the fibrotic region with the experimentally observed complex fractional atrial electrograms (CFAE) as well as strong difference between simulated electrograms in 2D and 3D were found for the cases where reentry and ectopic activity were triggered by the micro-fibrotic region.

Technical advances in studying cardiac electrophysiology - Role of rabbit models

Cardiovascular research has made a major contribution to an unprecedented 10 year increase in life expectancy during the last 50 years: most of this increase due to a decline in mortality from heart disease and stroke. The majority of the basic cardiovascular science discoveries, which have led to this impressive extension of human life, came from investigations conducted in various small and large animal models, ranging from mouse to pig. The small animal models are currently popular because they are amenable to genetic engineering and are relatively inexpensive. The large animal models are favored at the translational stage of the investigation, as they are anatomically and physiologically more proximal to humans, and can be implanted with various devices; however, they are expensive and less amenable to genetic manipulations. With the advent of CRISPR genetic engineering technology and the advances in implantable bioelectronics, the large animal models will continue to advance. The rabbit model is particularly poised to become one of the most popular among the animal models that recapitulate human heart diseases. Here we review an array of the rabbit models of atrial and ventricular arrhythmias, as well as a range of the imaging and device technologies enabling these investigations.

A Genetic Algorithm Optimization Method for Mapping Non-Conducting Atrial Regions: A Theoretical Feasibility Study

Atrial ablation has been recently utilized for curing atrial fibrillation. The success rate of empirical ablation is relatively low as often the exact locations of the arrhythmogenic sources remain elusive. Guided ablation has been proposed to improve ablation technique by providing guidance regarding the potential localization of the sources; yet to date no main technological solution has been widely adopted as an integral part of the ablation process. Here we propose a genetic algorithm optimization technique to map a major arrhythmogenic substance-non-conducting regions (NCRs). Excitation delays in a set of electrodes of known locations are measured following external tissue stimulation, and the spatial distribution of obstacles that is most likely to yield the measured delays is reconstructed. A forward problem module was solved to provide synthetic time delay measurements using a 2D human atrial model with known NCR distribution. An inverse genetic algorithm module was implemented to optimally reconstruct the locations of the now unknown obstacle distribution using the synthetic measurements. The performance of the algorithm was demonstrated for several distributions varying in NCR number and shape. The proposed algorithm was found robust to measurements with a signal-to-noise ratio of at least -20 dB, and for measuring electrodes separated by up to 3.2 mm. Our results support the feasibility of the proposed algorithm in mapping NCRs; nevertheless, further research is required prior to clinical implementation for incorporating more complex atrial tissue geometrical configurations as well as for testing the algorithm with experimental data.