Abstract
Mouse models of atherosclerosis have become effective resources to study atherogenesis, including the relationship between hemodynamics and lesion development. Computational methods aid the prediction of the in vivo hemodynamic environment in the mouse vasculature, but careful selection of inflow and outflow boundary conditions (BCs) is warranted to promote model accuracy. Herein, we investigated the impact of animal-specific versus reduced/idealized flow boundary conditions on predicted blood flow patterns in the mouse thoracic aorta. Blood velocities were measured in the aortic root, arch branch vessel, and descending aorta in ApoE−/− mice using phase-contrast MRI. Computational geometries were derived from micro-CT imaging and combinations of high-fidelity or reduced/idealized MR-derived BCs were applied to predict the bulk flow field and hemodynamic metrics (e.g., wall shear stress, WSS; cross-flow index, CFI). Results demonstrate that pressure-free outlet BCs significantly overestimate outlet flow rates as compared to measured values. When compared to models that incorporate 3-component inlet velocity data [\(\mathop{v}\limits^{\rightharpoonup} \left( {v_{r} ,v_{\theta } ,v_{z} } \right)\)] and time-varying outlet mass flow splits [\(Q\left( t \right)\)] (i.e., high-fidelity model), neglecting in-plane inlet velocity components (i.e., \(\mathop{v}\limits^{\rightharpoonup} (v_{z}\))) leads to errors in WSS and CFI values ranging from 10 to 30% across the model domain whereas the application of a steady outlet mass flow splits results in negligible differences in these hemodynamics metrics. This investigation highlights that 3-component inlet velocity data and at least steady mass flow splits are required for accurate predictions of flow patterns in the mouse thoracic aorta.
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Notes
Although a pressure gauge was not in-line during perfusion of the animals, due to possibility of equipment damage with the contrast agent, benchtop testing using an identical setup with tubing that had a diameter equivalent to the mouse aorta and high downstream resistance indicated the perfusion pressure was ~150 mmHg.
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Acknowledgments
MRI scans were performed at the University of Utah Preclinical Imaging Facility supported by NIH Grant S10 RR023017. Seg3D is an Open Source software project that is supported by the National Institute of General Medical Sciences of the National Institutes of Health under Grant Number P41 GM103545.
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Smith, K.A., Merchant, S.S., Hsu, E.W. et al. Effect of Subject-Specific, Spatially Reduced, and Idealized Boundary Conditions on the Predicted Hemodynamic Environment in the Murine Aorta. Ann Biomed Eng 49, 3255–3266 (2021). https://doi.org/10.1007/s10439-021-02851-7
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DOI: https://doi.org/10.1007/s10439-021-02851-7