Computational fluid dynamics simulations based on MRI reconstructions of the human aorto-iliac bifurcation accurately predicted flow patterns and demonstrated major differences in wall shear stress.
Combining MRI and computational fluid dynamics provides a noninvasive approach to evaluate local geometries and wall shear stress as risk factors for arterial disease.
Magnetic resonance imaging and computational fluid dynamics (CFD) have been used in combination to simulate flow patterns at the human aorto-iliac bifurcation. Vascular anatomy was reconstructed from stacked two-dimensional (2D) time-of-flight images, and revealed asymmetric, nonplanar geometry with curvature in the abdominal aorta and right iliac artery. The left iliac artery was straight and exhibited a smaller take off angle than the right iliac artery. The anatomical reconstruction was used to generate a computational mesh and obtain CFD predictions of flow and wall shear stress (WSS) within the region of interest. The dynamic boundary conditions necessary were specified by 2D cine phase contrast measurements of velocity profiles in each component vessel. Predicted flow patterns were in good quantitative agreement with experiment and demonstrated major differences in WSS distributions between the iliac arteries. This noninvasive approach has considerable potential to evaluate local geometries and WSS as risk factors for arterial disease in individual subjects.
Long et al. (Sat,) conducted a other in Arterial disease risk. Magnetic resonance imaging and computational fluid dynamics (CFD) vs. Experimental measurements was evaluated on Flow patterns and wall shear stress (WSS) distributions. Computational fluid dynamics simulations based on MRI reconstructions of the human aorto-iliac bifurcation accurately predicted flow patterns and demonstrated major differences in wall shear stress.