Effects of Persistent Atrial Fibrillation-Induced Electrical Remodeling on Atrial Electro-Mechanics - Insights from a 3D Model of the Human Atria

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

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.

Human atrial fibrillation and genetic defects in transient outward currents: mechanistic insights from multi-scale computational models

Previous studies have linked dysfunctional I_to arising from mutations to KCND3-encoded Kv4.3 and KCND2-encoded Kv4.2 to atrial fibrillation. Using computational models, this study aimed to investigate the mechanisms underlying pro-arrhythmic effects of the gain-of-function Kv4.3 (T361S, A545P) and Kv4.2 (S447R) mutations. Wild-type and mutant I_to formulations were developed from and validated against experimental data and incorporated into the Colman et al. model of human atrial cells. Single-cell models were incorporated into one- (1D) and two-dimensional (2D) models of atrial tissue, and a three-dimensional (3D) realistic model of the human atria. The three gain-of-function mutations had similar, albeit quantitatively different, effects: shortening of the action potential duration; lowering the plateau membrane potential, abbreviating the effective refractory period (ERP) and the wavelength (WL) of atrial excitation at the tissue level. Restitution curves for the WL, the ERP and the conduction velocity were leftward shifted, facilitating the conduction of atrial excitation waves at high excitation rates. The mutations also increased lifespan and stationarity of re-entry in both 2D and 3D simulations, which further highlighted a mutation-induced increase in spatial dispersion of repolarization. Collectively, these changes account for pro-arrhythmic effects of these Kv4.3 and Kv4.2 mutations in facilitating AF. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'.

Cellular heterogeneity and repolarisation across the atria: an in silico study

Mechanisms of atrial fibrillation and the susceptibility to reentries can be impacted by the repolarization across the atria. Studies into atrial fibrillation ignore cell-to-cell heterogeneity due to electrotonic coupling. Recent studies show that cellular variability may have a larger impact on electrophysiological behaviour than assumed. This paper aims to determine the impact of cellular heterogeneity on the repolarization phase across the AF remodelled atria. Using a population of models approach, 10 anatomically identical atrial models were created to include cellular heterogeneity. Atrial models were compared with an equivalent homogenous model. Activation, APD90, and repolarization maps were used to compare models. The impact of electrotonic coupling in the tissue was determined through a comparison of RMP, APD20, APD50, APD90, and triangulation between regional atrial tissue and the single cell populations. After calibration, cellular heterogeneity does not impact atrial depolarization. Repolarization patterns were significantly impacted by cellular heterogeneity, with the APD90 across the LA increasing due to heterogeneity and the reverse occurring in the RA. Electrotonic coupling caused a reduction in variability across all biomarkers but did not fully remove variability. Electrotonic coupling resulted in an increase in APD20 and APD50, and reduced triangulation compared to isolated cell populations. Heterogeneity also caused a reduction in triangulation compared with regionally homogeneous atria.

A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives)

Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.

A Comparison of Regional Classification Strategies Implemented for the Population Based Approach to Modelling Atrial Fibrillation

(1) Background: in silico models are increasingly relied upon to study the mechanisms of atrial fibrillation. Due to the complexity associated with atrial models, cellular variability is often ignored. Recent studies have shown that cellular variability may have a larger impact on electrophysiological behaviour than previously expected. This paper compares two methods for AF remodelling using regional populations. (2) Methods: using 200,000 action potentials, experimental data was used to calibrate healthy atrial regional populations with two cellular models. AF remodelling was applied by directly adjusting maximum channel conductances. AF remodelling was also applied through adjusting biomarkers. The methods were compared upon replication of experimental data. (3) Results: compared to the percentage method, the biomarker approach resulted in smaller changes. RMP, APD20, APD50, and APD90 were changed in the percentage method by up to 11%, 500%, 50%, and 60%, respectively. In the biomarker approach, RMP, APD20, APD50, and APD90 were changed by up to 4.5%, 132%, 50%, and 35%, respectively. (4) Conclusion: applying AF remodelling through biomarker-based clustering resulted in channel conductance changes that were consistent with experimental data, while maintaining the highly non-linear relationships between channel conductances and biomarkers. Directly changing conductances in the healthy regional populations impacted the non-linear relationships and resulted in non-physiological APD20 and APD50 values.

Stroke due to Left Atrial Appendage Thrombus after Pulmonary Vein Isolation despite Novel Oral Anticoagulant: A Case Report

In patients with atrial fibrillation, catheter ablation is suggested to reduce the mortality rate and is thus frequently performed. However, peri- and postprocedural thromboembolic complications as well as high recurrence rates of atrial fibrillation limit its advantages and require concomitant anticoagulation. With the advent of novel oral anticoagulants (NOACs), fixed dosing without routine laboratory monitoring became feasible. Nevertheless, several factors are associated with either an overdose or an insufficient drug activity of NOACs. We report on a patient with atrial fibrillation undergoing catheter ablation and cardioversion suffering from ischemic stroke despite being under oral anticoagulation. It turned out that the drug activity of the NOACs used was repeatedly insufficient in spite of regular intake and adequate dosing. In sum, drug activity controls should be taken into consideration in patients with thrombotic events despite oral anticoagulation with NOACs.

The impact of wall thickness and curvature on wall stress in patient-specific electromechanical models of the left atrium

The left atrium (LA) has a complex anatomy with heterogeneous wall thickness and curvature. The anatomy plays an important role in determining local wall stress; however, the relative contribution of wall thickness and curvature in determining wall stress in the LA is unknown. We have developed electromechanical finite element (FE) models of the LA using patient-specific anatomical FE meshes with rule-based myofiber directions. The models of the LA were passively inflated to 10mmHg followed by simulation of the contraction phase of the atrial cardiac cycle. The FE models predicted maximum LA volumes of 156.5 mL, 99.3 mL and 83.4 mL and ejection fractions of 36.9%, 32.0% and 25.2%. The median wall thickness in the 3 cases was calculated as [Formula: see text] mm, [Formula: see text] mm, and [Formula: see text] mm. The median curvature was determined as [Formula: see text] [Formula: see text], [Formula: see text], and [Formula: see text]. Following passive inflation, the correlation of wall stress with the inverse of wall thickness and curvature was 0.55-0.62 and 0.20-0.25, respectively. At peak contraction, the correlation of wall stress with the inverse of wall thickness and curvature was 0.38-0.44 and 0.16-0.34, respectively. In the LA, the 1st principal Cauchy stress is more dependent on wall thickness than curvature during passive inflation and both correlations decrease during active contraction. This emphasizes the importance of including the heterogeneous wall thickness in electromechanical FE simulations of the LA. Overall, simulation results and sensitivity analyses show that in complex atrial anatomy it is unlikely that a simple anatomical-based law can be used to estimate local wall stress, demonstrating the importance of FE analyses.

Correlation between serum homocysteine, Galectin-3 concentration and atrial structural remodeling in atrial fibrillation patients

Objective To investigate the correlation between serum homocysteine (Hcy), Galectin-3 concentration and atrial structural remodeling in atrial fibrillation (AF) patients.

Methods Twenty-five patients with persistent atrial fibrillation (PeAF), 24 patients with paroxysmal atrial fibrillation (PaAF) and 23 healthy controls were included in the present work. All subjects received an echocardiography examination. Serum concentration of Hcy and Galectin-3 were also examined by Enzyme Linked Immunosorbent Assay (ELISA).

Results Echocardiography examination demonstrated that there were significant differences for LAD (p=0.002), LVEF (p=0.005) and LVAI (p=0.0001) between the control, PaAF and PeAF groups. However, LVSD and LVDD were not significantly different between the three groups (pall>0.05). There was a significant positive correlation between LAVI and serum Hcy level in both PaAF (rpearson=0.49, p=0.016) and PeAF (rpearson=0.51, p=0.009) groups. The correlation between LAVI and serum Galectin-3 concentration was also statistically significant for PaAF (rpearson=0.54, p=0.006) and PeAF (rpearson=0.60, p=0.001) groups. Using serum Hcy as reference, diagnostic sensitivity and specificity were calculated as 72.00 (95%CI: 50.61-87.93) and 62.50 (95%CI: 40.59-81.20), respectively, with an AUC of 0.68 for PaAF and PeAF. For serum Galectin-3, the sensitivity and specificity values were 64.00 (95%CI:42.52-82.03) and 66.67 (95%CI:44.68-84.37), respectively, with an AUC of 0.68.

Conclusion: Serum Hcy and Galectin-3 were elevated in AF patients and thus may be potential markers of atrial structural remodeling. However, the diagnostic efficacy of PeAF from PaAF was limited by low AUC values.

PITX2 upregulation increases the risk of chronic atrial fibrillation in a dose-dependent manner by modulating IKs and ICaL -insights from human atrial modelling

Background

Functional analysis has shown that the paired-like homeodomain transcription factor 2 (PITX2) overexpression associated with atrial fibrillation (AF) leads to the slow delayed rectifier K⁺ current (I_Ks) increase and the L-type Ca²⁺ current (I_CaL) reduction observed in isolated right atrial myocytes from chronic AF (CAF) patients. Through multiscale computational models, this study aimed to investigate the functional impact of the PITX2 overexpression on atrial electrical activity.

Methods

The well-known Courtemanche-Ramirez-Nattel (CRN) model of human atrial action potentials (APs) was updated to incorporate experimental data on alterations in I_Ks and I_CaL due to the PITX2 overexpression. These cell models for sinus rhythm (SR) and CAF were then incorporated into homogeneous multicellular one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) tissue models. The proarrhythmic effects of the PITX2 overexpression were quantified with ion current profiles, AP morphology, AP duration (APD) restitution, conduction velocity restitution (CVR), wavelength (WL), vulnerable window (VW) for unidirectional conduction block, and minimal substrate size required to induce re-entry. Dynamic behaviors of spiral waves were characterized by measuring lifespan (LS), tip patterns and dominant frequencies.

Results

The I_Ks increase and the I_CaL decrease arising from the PITX2 overexpression abbreviated APD and flattened APD restitution (APDR) curves in single cells. It reduced WL and increased CV at high excitation rates at the 1D tissue level. Although it had no effects on VW for initiating spiral waves, it decreased the minimal substrate size necessary to sustain re-entry. It also stabilized and accelerated spiral waves in 2D and 3D tissue models.

Conclusions

Electrical remodeling (I_Ks and I_CaL) due to the PITX2 overexpression increases susceptibility to AF due to increased tissue vulnerability, abbreviated APD, shortened WL and altered CV, which, in combination, facilitate initiation and maintenance of spiral waves.

Analysis of a coupled fluid-structure interaction model of the left atrium and mitral valve

We present a coupled left atrium-mitral valve model based on computed tomography scans with fibre-reinforced hyperelastic materials. Fluid-structure interaction is realised by using an immersed boundary-finite element framework. Effects of pathological conditions, eg, mitral valve regurgitation and atrial fibrillation, and geometric and structural variations, namely, uniform vs non-uniform atrial wall thickness and rule-based vs atlas-based fibre architectures, on the system are investigated. We show that in the case of atrial fibrillation, pulmonary venous flow reversal at late diastole disappears, and the filling waves at the left atrial appendage orifice during systole have reduced magnitude. In the case of mitral regurgitation, a higher atrial pressure and disturbed flows are seen, especially during systole, when a large regurgitant jet can be found with the suppressed pulmonary venous flow. We also show that both the rule-based and atlas-based fibre defining methods lead to similar flow fields and atrial wall deformations. However, the changes in wall thickness from non-uniform to uniform tend to underestimate the atrial deformation. Using a uniform but thickened wall also lowers the overall strain level. The flow velocity within the left atrial appendage, which is important in terms of appendage thrombosis, increases with the thickness of the left atrial wall. Energy analysis shows that the kinetic and dissipation energies of the flow within the left atrium are altered differently by atrial fibrillation and mitral valve regurgitation, providing a useful indication of the atrial performance in pathological situations.

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.

Atrial contractility and fibrotic biomarkers are associated with atrial fibrillation after elective coronary artery bypass grafting

OBJECTIVE

New-onset postoperative atrial fibrillation is common after cardiac surgery. Less has been reported about the relationship among fibrosis, inflammation, calcium-induced left atrial and right atrial contractile forces, and postoperative atrial fibrillation. We sought to identify predictors of postoperative atrial fibrillation.

METHODS

From August 2016 to February 2018, we evaluated 229 patients who had preoperative sinus rhythm before elective primary coronary artery bypass grafting. Of 229 patients, 191 maintained sinus rhythm postoperatively, whereas 38 patients developed atrial fibrillation. Preoperative tissue inhibitor of metalloproteinase-1, pentraxin-3, matrix metallopeptidase-9, galectin-3, high-sensitivity C-reactive protein, growth differentiation factor 15, and transforming growth factor-ß were measured. Clinical and echocardiographic findings (tricuspid annular plane systolic excursion for right heart function) and calcium-induced force measurements from left atrial and right atrial-derived skinned myocardial fibers were recorded.

RESULTS

Patients with atrial fibrillation were older (P = .001), had enlarged left atrial (P = .0001) and right atrial areas (P = .0001), and had decreased tricuspid annular plane systolic excursion (P = .001). Levels of matrix metallopeptidase-9 and pentraxin-3 were decreased (P < .05), whereas growth differentiation factor 15 was increased (P = .001). We detected lower left atrial force values at calcium-induced force measurements 5.5 (P < .05), 5.4 (P < .01), and 5.3 to 4.52 (P = .0001) and right atrial force values at calcium-induced force measurements 5.0 to 4.52 (P < .05) in patients with postoperative atrial fibrillation. Multivariable analysis showed that advanced age (P = .033), decreased left atrial force value at calcium-induced force measurement of 5.5 (P = .033), enlarged left atrial (P = .013) and right atrial (P = .081) areas, and reduced tricuspid annular plane systolic excursion (P = .010) independently predicted postoperative atrial fibrillation.

CONCLUSIONS

Advanced age, decreased left atrial force value at calcium-induced force measurement of 5.5, enlarged left atrial and right atrial areas, and reduced tricuspid annular plane systolic excursion were identified as independent predictors for postoperative atrial fibrillation.

Personalized computational modeling of left atrial geometry and transmural myofiber architecture

Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by complete absence of coordinated atrial contraction and is associated with an increased morbidity and mortality. Personalized computational modeling provides a novel framework for integrating and interpreting the role of atrial electrophysiology (EP) including the underlying anatomy and microstructure in the development and sustenance of AF. Coronary computed tomography angiography data were segmented using a statistics-based approach and the smoothed voxel representations were discretized into high-resolution tetrahedral finite element (FE) meshes. To estimate the complex left atrial myofiber architecture, individual fiber fields were generated according to morphological data on the endo- and epicardial surfaces based on local solutions of Laplace’s equation and transmurally interpolated to tetrahedral elements. The influence of variable transmural microstructures was quantified through EP simulations on 3 patients using 5 different fiber interpolation functions. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity tetrahedral FE meshes. The novel algorithm for automated incorporation of the left atrial fiber architecture provided a realistic estimate of the atrial microstructure and was able to qualitatively capture all important fiber bundles. Consistent maximum local activation times were predicted in EP simulations using individual transmural fiber interpolation functions for each patient suggesting a negligible effect of the transmural myofiber architecture on EP. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts accounting for detailed anatomy and microstructure and facilitates simulations of atrial EP.

Low-dose green tea intake reduces incidence of atrial fibrillation in a Chinese population

The aim of the present study was to assessthe association between green tea intake and incidence of atrial fibrillation (AF) in a Chinese population. A total of 801 (mean age: 62 years; 56% male) subjects were enrolled: 401 AF patients and 400 controls. All subjects completed a questionnaire and the associations between their green tea drinking habits and incidence of AF were assessed using the odds ratio (OR) and binary logistic regression. After multivariate adjustment, green tea intake presented as a protective factor against the incidence of AF (OR: 0.349, 95% CI: 0.253-0.483, P < 0.001). The green tea protection showed downward trend with increasing green tea intake (P for the trend= 0.001). Low frequency, low concentration, short-term tea consumption was classified as low-dose green tea intake. Green tea intake decreased the incidence of both paroxysmal AF (OR: 0.307, 95% CI: 0.216-0.436, P < 0.001) and persistent AF (OR: 0.355, 95% CI: 0.261-0.482, P < 0.001) and may be associated with a decreased incidence of AF. This study suggests that low-dose green tea intake strongly protects against AF.

Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation.

Usefulness of the Atrial Emptying Fraction to Predict Maintenance of Sinus Rhythm After Direct Current Cardioversion for Atrial Fibrillation

Atrial volumes indexed to body surface area (AVI) are robust predictors of nonvalvular atrial fibrillation (AF) recurrence after direct current cardioversion (DCCV). The incremental value of atrial emptying fraction (EmF) compared with atrial volumes as a predictor for recurrent AF after DCCV has not been evaluated. We sought to compare the predictive ability of baseline left atrial (LA) EmF, right atrial (RA) EmF, LAVI, and RAVI for post-DCCV AF recurrence at 6 months. The first 95 patients enrolled in the AF Clinic Registry with adequate echocardiogram imaging constituted the study cohort. Each patient underwent echocardiogram within 6 months before cardioversion. Maximal LAVI and RAVI, LA EmF, and RA EmF were performed offline using 4-chamber single-plane Simpson's method, averaged over 5 cycles. The mean age of the study cohort was 64 ± 12 years, and 67% were men. Only 28 patients (29%) who underwent DCCV remained in sinus rhythm at 6 months of follow-up. The remaining, 67 (71%) had reverted to AF or underwent ablation during the 6 months of follow-up. The overall performance for prediction of AF recurrence was greatest for RA EmF, area under the receiver operator characteristic curve (AUC): RA EmF 0.92, LA EmF 0.89, RAVI 0.76, and LAVI 0.63. RA and LA EmF AUCs were significantly higher than for LAVI or RAVI (max p = 0.02). In conclusion, although RAVI and LAVI are strong predictors of AF recurrence after DCCV, RA and LA EmF outperformed in this cohort.

Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with increased risk of cerebrovascular stroke, and with several other pathologies, including heart failure. Current therapies for AF are targeted at reducing risk of stroke (anticoagulation) and tachycardia-induced cardiomyopathy (rate or rhythm control). Rate control, typically achieved by atrioventricular nodal blocking drugs, is often insufficient to alleviate symptoms. Rhythm control approaches include antiarrhythmic drugs, electrical cardioversion, and ablation strategies. Here, we offer several examples of how computational modeling can provide a quantitative framework for integrating multiscale data to: (a) gain insight into multiscale mechanisms of AF; (b) identify and test pharmacological and electrical therapy and interventions; and (c) support clinical decisions. We review how modeling approaches have evolved and contributed to the research pipeline and preclinical development and discuss future directions and challenges in the field.