Computational study of aortic hemodynamics for patients with an abnormal aortic valve: The importance of secondary flow at the ascending aorta inlet

Abstract

Blood flow in the aorta is helical, but most computational studies ignore the presence of secondary flow components at the ascending aorta (AAo) inlet. The aim of this study is to ascertain the importance of inlet boundary conditions (BCs) in computational analysis of flow patterns in the thoracic aorta based on patient-specific images, with a particular focus on patients with an abnormal aortic valve. Two cases were studied: one presenting a severe aortic valve stenosis and the other with a mechanical valve. For both aorta models, three inlet BCs were compared; these included the flat profile and 1D through-plane velocity and 3D phase-contrast magnetic resonance imaging derived velocity profiles, with the latter being used for benchmarking. Our results showed that peak and mean velocities at the proximal end of the ascending aorta were underestimated by up to 41% when the secondary flow components were neglected. The results for helical flow descriptors highlighted the strong influence of secondary velocities on the helical flow structure in the AAo. Differences in all wall shear stress (WSS)-derived indices were much more pronounced in the AAo and aortic arch (AA) than in the descending aorta (DAo). Overall, this study demonstrates that using 3D velocity profiles as inlet BC is essential for patient-specific analysis of hemodynamics and WSS in the AAo and AA in the presence of an abnormal aortic valve. However, predicted flow in the DAo is less sensitive to the secondary velocities imposed at the inlet; hence, the 1D through-plane profile could be a sufficient inlet BC for studies focusing on distal regions of the thoracic aorta.

4-D Flow MRI-Based Computational Analysis of Blood Flow in Patient-Specific Aortic Dissection

“…Briefly, the images were pre-processed using MATLAB to generate a series of files which could be read into Ansys EnSight, where the inlet cross-section was defined by positioning a cut-plane normal to the aortic wall in the ascending aorta. The normal velocity components were then extracted and further processed using our in-house MATLAB tool [21] which included image segmentation and centering; the latter was needed to compensate for in-plane movements of the aorta during the cardiac cycle. Velocity values were then interpolated in time, and mapped onto the 3D global coordinates of the model inlet.…”

“…For the inlet, these generally involve mapping a typical flow waveform onto flat [4,7,9] or parabolic [6] profiles. Previous studies [20,21] have shown that idealized velocity profiles are not suitable for studies focusing on the ascending aorta and aortic arch, but the descending aorta is less sensitive to the inlet velocity profile.…”

Numerical Investigation of the Effects of Prosthetic Aortic Valve Design on Aortic Hemodynamic Characteristics

“…Moreover, the laminar flow condition was assumed in this study due to the constriction of the solver. Although the laminar assumption has been widely used in the flow simulations in the aortic valve and aorta [42,52,80,85,86], its inaccurate estimation of flow parameters within the transitional and turbulent flow regime region should be noted in the individualized evaluations [87].…”

A bi-fidelity surrogate modeling approach for uncertainty propagation in three-dimensional hemodynamic simulations

“…Uncertainty quantification (UQ) and sensitivity analysis (SA) of cardiovascular modeling have been gaining increasing attention in the past decade. There are numerous literature on examining the influence of variations in inflow/outflow boundary conditions [6][7][8][9][10][11][12][13][14][15][16][17][18], segmented vascular geometry [19][20][21][22][23][24][25][26][27][28], and mechanical properties of blood flow or vessel walls [29][30][31][32][33] on the simulated hemodynamics. However, the majority of these works focused on investigating the sensitivity of the model to its input factors using ad hoc perturbation analysis but have yet to rigorously characterize and quantify the uncertainty distributions.…”