Abstract
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.
Highlights
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by uncoordinated atrial activation with consequent deterioration of mechanical function
The automated personalized modeling pipeline was exercised on 3 patient cases to demonstrate its ability to generate detailed finite element (FE) models including a qualitative representation of the left atrial fiber architecture
This artifact results from the coronary CT angiography (CTA) imaging acquisition, from the image reconstruction, in which the voxel image was generated over the course of typically 2 consecutive heart beats changing the intensity of the contrast agent as it was pumped through the circulatory system
Summary
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by uncoordinated atrial activation with consequent deterioration of mechanical function. Significant limitations of atrial in vivo imaging, due to its thinwalled phenotype, have motivated comprehensive anatomical and morphological ex vivo studies aiming to characterize the atrial fiber architecture qualitatively over the endo- and epicardial surfaces (Ho et al, 1999; 2002; Cabrera et al, 2008; Ho and SánchezQuintana, 2009). Additional ex vivo quantifications of the atrial fiber orientation include serial surface macroscopy (Zhao et al, 2012; 2013), micro-computed tomography (CT) (Varela et al, 2013; Zhao et al, 2015; Stephenson et al, 2017), diffusion tensor magnetic resonance imaging (MRI) (Pashakhanloo et al, 2016) and contrast-enhanced MRI (Zhao et al, 2017)
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