Computational modelling of monocyte deposition in abdominal aortic aneurysms
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Abdominal aortic aneurysm (AAA) disease involves a dilation of the aorta below the renal arteries. If the aneurysm becomes sufficiently dilated and tissue strength is less than vascular pressure, rupture of the aorta occurs entailing a high mortality rate. Despite improvements in surgical technique, the mortality rate for emergency repair remains high and so an accurate predictor of rupture risk is required. Inflammation and the associated recruitment of monocytes into the aortic wall are critical in the pathology of AAA disease, stimulating the degradation and remodeling of the vessel wall. Areas with high concentrations of macrophages may experience an increase in tissue degradation and therefore an increased risk of rupture. Determining the magnitude and distribution of monocyte recruitment can help us understand the pathology of AAA disease and add spatial accuracy to the existing rupture risk prediction models. In this study finite element computational fluid dynamics simulations of AAA haemodynamics are seeded with monocytes to elucidate patterns of cell deposition and probability of recruitment. Haemodynamics are first simulated in simplified AAA geometries of varying diameters with a patient averaged flow waveform inlet boundary condition. This allows a comparison with previous experimental investigations as well as determining trends in monocyte adhesion with aneurysm progression. Previous experimental investigations show a transition to turbulent flow occurring during the deceleration phase of the cardiac cycle. There has thus far been no investigation into the accuracy of turbulence models in simulating AAA haemodynamics and so simulations are compared using RNG κ − ε, κ − ω and LES turbulence models. The RNG κ − ε model is insufficient to model secondary flows in AAA and LES models are sensitive to inlet turbulence intensity. The probability of monocyte adhesion and recruitment depends on cell residence time and local wall shear stress. A near wall particle residence time (NWPRT)model is created incorporating a wall shear stress-limiter based on in vitro experimental data. Simulated haemodynamics show qualitative agreement with experimental results. Peaks of maximum NWPRT move downstream in successively larger geometries, correlating with vortex behaviour. Average NWPRT rises sharply in models above a critical maximum diameter. These techniques are then applied to patient-specific AAAs. Geometries are created from CT slices and velocity boundary conditions taken from Phase Contrast-MRI (PC-MRI) data for 3 patients. There is no gold standard for inlet boundary conditions and so simulations using 3 velocity components, 1 velocity component and parabolic flow profiles at the inlet are compared with each other and with PC-MRI data at the AAA midsection. The general trends in flow and wall shear stress are similar between simulations with 3 and 1 components of inlet velocity despite differences in the nature and complexity of secondary flow. Applying parabolic velocity profiles, however, can cause significant deviations in haemodynamics. Axial velocities show average to good correlation with PC-MRI data though the lower magnitude radial velocities produce high levels of noise in the raw data making comparisons difficult. Patient specific NWPRT models show monocyte infiltration is most likely at or around the iliac bifurcation.
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