Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics.

Carlos Sánchez,Blanca Rodríguez,Esther Pueyo,Alfonso Bueno-Orovio

doi:10.3389/fbioe.2017.00029

Abstract

Atrial fibrillation (AF) usually manifests as reentrant circuits propagating through the whole atria creating chaotic activation patterns. Little is yet known about how differences in electrophysiological and ionic properties between patients modulate reentrant patterns in AF. The goal of this study is to quantify how variability in action potential duration (APD) at different stages of repolarization determines AF dynamics and their modulation by ionic block using a set of virtual whole-atria human models. Six human whole-atria models are constructed based on the same anatomical structure and fiber orientation, but with different electrophysiological phenotypes. Membrane kinetics for each whole-atria model are selected with distinct APD characteristics at 20, 50, and 90% repolarization, from an experimentally calibrated population of human atrial action potential models, including AF remodeling and acetylcholine parasympathetic effects. Our simulations show that in all whole-atria models, reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage, thus leading to higher dominant frequency (DF) and more organized activation in the left atrium than in the right atrium. Differences in APD in all phases of repolarization (not only APD90) yielded quantitative differences in fibrillation patterns with long APD associated with slower and more regular dynamics. Long APD50 and APD20 were associated with increased interatrial conduction block and interatrial differences in DF and organization index, creating reentry instability and self-termination in some cases. Specific inhibitions of IK1, INaK, or INa reduce DF and organization of the arrhythmia by enlarging wave meandering, reducing the number of secondary wavelets, and promoting interatrial block in all six virtual patients, especially for the phenotypes with short APD at 20, 50, and/or 90% repolarization. This suggests that therapies aiming at prolonging the early phase of repolarization might constitute effective antiarrhythmic strategies for the pharmacological management of AF. In summary, simulations report significant differences in atrial fibrillatory dynamics resulting from differences in APD at all phases of repolarization.

Highlights

Reentrant circuits are one of the main manifestations of the most commonly diagnosed arrhythmia in the human heart: atrial fibrillation (AF) (Fuster et al, 2011)
Each human whole-atria model was assigned a different action potential (AP) phenotype with human atrial membrane kinetics based on the Maleckar et al model (Maleckar et al, 2009), but with ionic conductances calibrated to account for Atrial fibrillation (AF) remodeling and intersubject variability in action potential duration (APD) using an experimentally calibrated population of human AP models as described in Sánchez et al (2014)
AF dynamics were modulated by differences in all three phases of repolarization, as shown in Figure 3 for the models with short vs long APD90, APD50, and APD20

Summary

Introduction

Reentrant circuits are one of the main manifestations of the most commonly diagnosed arrhythmia in the human heart: atrial fibrillation (AF) (Fuster et al, 2011). The frequency of tissue activation or the organization in atrial activation can be quantified from electrograms (EGMs) measured on the atrial surface Heterogeneity in these indices is considered putative of the complex spatiotemporal patterns that characterize AF, including multiple self-sustained rotors driving fibrillatory conduction (Berenfeld and Jalife, 2011; Atienza et al, 2015; Benharash et al, 2015), collision of the resulting wavefronts (Narayan et al, 2011), and disorganized local activation due to rotor meandering (Zlochiver et al, 2008; Berenfeld and Jalife, 2011). All these measurable indices (and AF characteristics) present significant variability between different patients, but the implications of this variability are not well understood (Habel et al, 2010; Britton et al, 2013; Sánchez et al, 2014; Kogawa et al, 2015; Muszkiewicz et al, 2016)

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