Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation

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Abstract

In-silico fluid simulations of the left atria (LA) in atrial fibrillation (AF) patients can help to describe and relate patient-specific morphologies and complex flow haemodynamics with the pathophysiological mechanisms behind thrombus formation. Even in AF patients, LA wall motion plays a non-negligible role in LA function and blood flow patterns. However, obtaining 4D LA wall dynamics from patient-specific data is not an easy task due to current image resolution limitations. Therefore, several approaches have been proposed in the literature to include left atrial wall motion in fluid simulations, being necessary to benchmark them in relation to their estimations on thrombogenic risk. In this work, we present results obtained with computational fluid dynamic simulations of LA geometries from a control and an AF patient with different left atrial wall motion approaches: 1) assuming rigid walls; 2) with a passive movement of the mitral valve annulus plane from a dynamic mesh approach based on springs (DM-SB); and 3) imposing LA wall deformation extracted from dynamic computed tomography (DM-dCT) images. Different strategies for the inlet/outlet boundary conditions were also tested. The DM-dCT approach was the one providing simulation results closer to velocity curves extracted from the reference echocardiographic data, whereas the rigid wall strategy over-estimated the risk of thrombus formation.

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Albors, C., Mill, J., Kjeldsberg, H. A., Viladés Medel, D., Olivares, A. L., Valen-Sendstad, K., & Camara, O. (2022). Sensitivity Analysis of Left Atrial Wall Modeling Approaches and Inlet/Outlet Boundary Conditions in Fluid Simulations to Predict Thrombus Formation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13593 LNCS, pp. 179–189). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-23443-9_17

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