Effects of Geometric Modelling and Blood Rheology in Patient-Specific Arterial Blood Flow Simulations with Speed-Accuracy Trade-Off Analysis

TL;DR

The paper investigates how reducing the geometric complexity of a patient-specific descending aorta affects 3D pulsatile blood flow simulations, comparing Newtonian, Carreau–Yasuda, and Apostolidis–Beris viscosity models. By constructing three geometry levels (Level 1: CT-derived, Level 2: area-preserving slice-based, Level 3: smooth tapered tube) and applying realistic boundary conditions with extended inlets/outlets, the study quantifies changes in velocity profiles, WSS, TAWSS, OSI, and flow topology using the $Q$-criterion. Correlation analyses show Level 2 largely preserves Level 1 features for non-Newtonian models, while Level 3 increasingly blurs local details; non-Newtonian rheology is more robust to geometric simplification than Newtonian predictions. A speed-accuracy trade-off is demonstrated: Level 2 yields ~4x faster computations with substantial retention of key hemodynamic patterns, whereas Level 3 provides further speed at the expense of losing recirculation zones and localized stress variations. The results offer practical guidance for rapid yet credible patient-specific CFD in large arteries, enabling faster clinical decision support and treatment planning, while highlighting the value of non-Newtonian models for irregular geometries.

Abstract

This study investigates the effects of geometric model reduction on blood flow simulations in the patient-specific descending aorta, followed by speed-accuracy trade-off analysis using 3D simulations. We demonstrate how wall shear stresses (WSS) can be reliably estimated for such realistic arteries using significantly faster simulations of highly idealized equivalent geometries, for any blood rheology model. CFD simulations (3D) are performed at two levels of geometry reduction employing realistic pulsatile inflow and pressure outlet boundary conditions and utilizing both Newtonian and non-Newtonian blood rheology models, including the one developed recently by Apostolidis and Beris. The first level of reduction does not retain effects due to local asymmetry but can approximate various flow parameters and patterns, while showing a significant computational speedup. However, further simplification to an idealized smooth geometry loses all information about the vortex structures and flow circulation. The non-Newtonian models retain more accuracy than the Newtonian models in geometry reductions, as quantified by correlations defined in this study. The idealized smooth geometry, combined with area correction, yields WSS estimates that closely approximate those of the actual artery. This study is expected to be applicable in geometric reductions (and speed enhancements) for more complex patient-specific 3D simulations while maintaining accuracy.

Figures (16)

• Figure 1: Level of geometrical aspects is shown, in (i) Level 1 of descending aorta extracted from CT-scan data, (ii) Slice-based geometry of descending aorta (Level 1 is divided into 25 slices for the construction of Level 2). (iii) Level 3 geometry based on the inlet and outlet diameter of Level 1 geometry. (iv) Cross-sectional area variation over the normalized z-axis for each level of simplification of the descending aorta.
• Figure 2: Pulsatile velocity waveform incorporated at the inlet of the artery, along with the pulsatile pressure waveform at the outlet of the descending aorta. mills1970 .
• Figure 4: (a) Oscillatory velocity inlet profile. (b) symmetric bifurcation geometry used by Nagargoje et al. nagargoje2021pulsatile
• Figure 5: (a) Mesh independence test is performed for Levels 1-3 of the descending aorta. The average velocity at the outlet is presented as a function of the inverse of the mesh element size. Here, $e$ is the mesh element size, and a higher inverse element size indicates a finer mesh. (b) The $z$-velocity component (w) is plotted at time instants $t_{1}, t_{2},$ and $t_{3}$ at the bifurcation of the geometry and matched against comparable results of Nagargoje et al. nagargoje2021pulsatile
• Figure 6: Axial velocity component shown for the three different viscosity models in (a) Level 1, (b) Level 2, and (c) Level 3 geometries.