Mechano-electric finite element model of the left atrium

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Personalized biomechanical insights in atrial fibrillation: opportunities & challenges

INTRODUCTION

Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke.

AREAS COVERED

In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care.

EXPERT OPINION

Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.

Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology

Mechanoelectric feedback (MEF) in the heart operates through several mechanisms which serve to regulate cardiac function. Stretch activated channels (SACs) in the myocyte membrane open in response to cell lengthening, while tension generation depends on stretch, shortening velocity, and calcium concentration. How all of these mechanisms interact and their effect on cardiac output is still not fully understood. We sought to gauge the acute importance of the different MEF mechanisms on heart function. An electromechanical computer model of a dog heart was constructed, using a biventricular geometry of 500K tetrahedral elements. To describe cellular behavior, we used a detailed ionic model to which a SAC model and an active tension model, dependent on stretch and shortening velocity and with calcium sensitivity, were added. Ventricular inflow and outflow were connected to the CircAdapt model of cardiovascular circulation. Pressure-volume loops and activation times were used for model validation. Simulations showed that SACs did not affect acute mechanical response, although if their trigger level was decreased sufficiently, they could cause premature excitations. The stretch dependence of tension had a modest effect in reducing the maximum stretch, and stroke volume, while shortening velocity had a much bigger effect on both. MEF served to reduce the heterogeneity in stretch while increasing tension heterogeneity. In the context of left bundle branch block, a decreased SAC trigger level could restore cardiac output by reducing the maximal stretch when compared to cardiac resynchronization therapy. MEF is an important aspect of cardiac function and could potentially mitigate activation problems.

Normative healthy reference values for global and segmental 3D principal and geometry dependent strain from cine cardiac magnetic resonance imaging

3-Dimensional (3D) myocardial deformation analysis (3D-MDA) enables novel descriptions of geometry-independent principal strain (PS). Applied to routine 2D cine cardiovascular magnetic resonance (CMR), this provides unique measures of myocardial biomechanics for disease diagnosis and prognostication. However, healthy reference values remain undefined. This study describes age- and sex-stratified reference values from CMR-based 3D-MDA, including 3D PS. One hundred healthy volunteers were prospectively recruited following institutional ethics approval and underwent CMR imaging. 3D-MDA was performed using validated software. Age- and sex-stratified global and segmental strain measures were derived for conventional geometry-dependent [circumferential (CS), longitudinal (LS), and radial (RS)] and geometry-independent [minimum (minPS) and maximum principal (maxPS)] directions of deformation. Layer-specific contraction angle interactions were determined using local minPS vectors. The average age was 43 ± 15 years and 55% were women. Strain measures were higher in women versus men. 3D PS-based assessment of maximum tissue shortening (minPS) and maximum tissue thickening (maxPS) were greater than corresponding geometry-dependent markers of LS and RS, consistent with improved representation of local tissue deformations. Global maxPS amplitude best discriminated both age and sex. Segmental analyses showed greater strain amplitudes in apical segments. Transmural PS contraction angles were higher in females and showed a heterogeneous distribution across segments. In this study we provided age and sex-based reference values for 3D strain from CMR imaging, demonstrating improved capacity for 3D PS to document maximal local tissue deformations and to discriminate age and sex phenotypes. Novel markers of layer-specific strain angles from 3D PS were also described.

A survey of pathways for mechano-electric coupling in the atria

Mechano-electric coupling (MEC) in atrial tissue has received sparse investigation to date, despite the well-known association between chronic atrial dilation and atrial fibrillation (AF). Of note, no fewer than six different mechanisms pertaining to stretch-activated channels, cellular capacitance and geometric effects have been identified in the literature as potential players. In this mini review, we briefly survey each of these pathways to MEC. We then perform computational simulations using single cell and tissue models in presence of various stretch regimes and MEC pathways. This allows us to assess the relative significance of each pathway in determining action potential duration, conduction velocity and rotor stability. For chronic atrial stretch, we find that stretch-induced alterations in membrane capacitance decrease conduction velocity and increase action potential duration, in agreement with experimental findings. In the presence of time-dependent passive atrial stretch, stretch-activated channels play the largest role, leading to after-depolarizations and rotor hypermeandering. These findings suggest that physiological atrial stretches, such as passive stretch during the atrial reservoir phase, may play an important part in the mechanisms of atrial arrhythmogenesis.

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Passive strains caused by ventricular contraction need to be considered when incorporating mechano-electro feedback in atrial electrophysiology models.

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In chronic stretch, stretch-induced capacitance changes dominate.

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Chronic stretch leads to an increase in action potential duration and a reduction in conduction velocity, consistent with experimental studies.

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In the presence of passive stretch, stretch-activated channels can induce delayed after-depolarisations and lead to rotor hypermeandering.

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Mechano-electro feedback is thus likely to have implications for the genesis and maintenance of atrial arrhythmias.

Mechanoelectrical feedback in pulmonary vein arrhythmogenesis: Clinical challenges and therapeutic opportunities

Mechanoelectrical feedback is an important factor in the pathophysiology of atrial fibrillation (AF). Ectopic electrical activity originating from pulmonary vein (PV) myocardial sleeves has been found to trigger and maintain paroxysmal AF. Dilated PVs by high stretching force may activate mechanoelectrical feedback, which induces calcium overload and produces afterdepolarization. These results, in turn, increase PV arrhythmogenesis and contribute to initiation of AF. Paracrine factors, effectors of the renin-angiotensin system, membranous channels, or cytoskeleton of PV myocytes may modulate PV arrhythmogenesis directly through mechanoelectrical feedback or indirectly through endocardial/myocardial cross-talk. The purpose of this review is to present laboratory and translational relevance of mechanoelectrical feedback in PV arrhythmogenesis. Targeting mechanoelectrical feedback in PV arrhythmogenesis may shed light on potential opportunities and clinical concerns of AF treatment.

Understanding AF Mechanisms Through Computational Modelling and Simulations

AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.