Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Author:

Kjeldsberg Henrik A.1,Albors Carlos2,Mill Jordi2,Medel David Viladés3,Camara Oscar2,Sundnes Joakim1,Valen‐Sendstad Kristian1ORCID

Affiliation:

1. Department of Computational Physiology Simula Research Laboratory Oslo Norway

2. Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain

3. Cardiology Department Hospital Santa Creu i Sant Pau Barcelona Spain

Abstract

AbstractAtrial fibrillation (AF) poses a significant risk of stroke due to thrombus formation, which primarily occurs in the left atrial appendage (LAA). Medical image‐based computational fluid dynamics (CFD) simulations can provide valuable insight into patient‐specific hemodynamics and could potentially enhance personalized assessment of thrombus risk. However, the importance of accurately representing the left atrial (LA) wall dynamics has not been fully resolved. In this study, we compared four modeling scenarios; rigid walls, a generic wall motion based on a reference motion, a semi‐generic wall motion based on patient‐specific motion, and patient‐specific wall motion based on medical images. We considered a LA geometry acquired from 4D computed tomography during AF, systematically performed convergence tests to assess the numerical accuracy of our solution strategy, and quantified the differences between the four approaches. The results revealed that wall motion had no discernible impact on LA cavity hemodynamics, nor on the markers that indicate thrombus formation. However, the flow patterns within the LAA deviated significantly in the rigid model, indicating that the assumption of rigid walls may lead to errors in the estimated risk factors. In contrast, the generic, semi‐generic, and patient‐specific cases were qualitatively similar. The results highlight the crucial role of wall motion on hemodynamics and predictors of thrombus formation, and also demonstrate the potential of using a generic motion model as a surrogate for the more complex patient‐specific motion. While the present study considered a single case, the employed CFD framework is entirely open‐source and designed for adaptability, allowing for integration of additional models and generic motions.

Funder

Norges Forskningsråd

Horizon 2020 Framework Programme

Publisher

Wiley

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