Numerical analysis of the hemodynamics of rat aorta based on magnetic resonance imaging and fluid–structure interaction

Abstract

Murine models have been widely used to investigate the mechanobiology of aortic atherosclerosis and dissections, which develop preferably at different anatomic locations of aorta. Based MRI and finite element analysis with fluid–structure interaction, we numerically investigated factors that may affect the blood flow and structural mechanics of rat aorta. The results indicated that aortic root motion greatly increases time‐averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), displacement of the aorta, and enhances helical flow pattern but has limited influence on effective stress, which is highly modulated by blood pressure. Moreover, the influence of the motion component on these indicators is different with axial motion more obvious than planar motion. Surrounding fixation of the intercostal arteries and the branch vessels on aortic arch would reduce the influence of aortic root motion. The compliance of the aorta has different influences at different regions, leading to decrease in TAWSS and helical flow, increase in OSI, RRT at the aortic arch, but has reversed effects on the branch vessels. When compared with the steady flow, the pulsatile blood flow would obviously increase the WSS, the displacement, and the effective stress in most regions. In conclusion, to accurately quantify the blood flow and structural mechanics of rat aorta, the motion of the aortic root, the compliance of aortic wall, and the pulsation of blood flow should be considered. However, when only focusing on the effective stress in rat aorta, the motion of the aortic root may be neglected.

Fluid–structure interaction study for biomechanics and risk factors in Stanford type A aortic dissection

“…To investigate the WSS exerted on the arterial wall during a pulsation cycle, the TAWSS is evaluated using the instantaneous WSS vector and the period of a cardiac cycle. In this computational model, the WSS ( τ w ) and TAWSS are given by: where u is the velocity of the blood flow, and T is the cardiac period 3,33,95 . Figure 9 shows the distribution contour of WSS at late systole ( t = 0.20 s) where the WSS reaches the maximum, and the maximum value is found in the entry of the false lumen.…”

“…In this computational model, the WSS (τ w ) and TAWSS are given by: where u is the velocity of the blood flow, and T is the cardiac period. 3,33,95 Figure 9 shows the distribution contour of WSS at late systole (t = 0.20 s) where the WSS reaches the maximum, and the maximum value is found in the entry of the false lumen. The maximal WSS can be bound near the false lumen entry (Plane 1) with a significantly higher value than other parts of the artery, excluding the maximum value of WSS on the side branches.…”

The Influence of Minor Aortic Branches in Patient-Specific Flow Simulations of Type-B Aortic Dissection

“…37 To date, minor branches have virtually always been neglected in simulations of the aorta due to limitations in medical image resolution, computational power, and a lack of available research on appropriate boundary conditions. Segmental arteries have been included as structural supports in aortic fluid-structure interaction (FSI) studies 13,19 but without haemodynamic assessment. The inferior mesenteric artery (IMA) and a selection of FL-branching intercostal arteries were recently included in a TBAD simulation.…”

Biomedical Approach of Nanotechnology and Biological Risks: A Mini-Review

“…Biomedical engineering combines principles from engineering, biological sciences, and medicine to develop technological solutions in healthcare. With various applications in medical imaging, diagnostic systems, rehabilitation, and more [1][2][3], scientific research has been driving the interest in optimizing advanced medical devices, personalizing medicine, integrating health data, and innovative therapies. For this, a clear intersection with nanotechnology is observed.…”