期刊
ENGINEERING WITH COMPUTERS
卷 38, 期 5, 页码 4005-4022出版社
SPRINGER
DOI: 10.1007/s00366-022-01735-1
关键词
Murine model; Thoracic aorta; Fluid-structure interaction; Ultrasound; Computational fluid dynamics; Arterial wall deformation
Modeling fluid-structure interactions in cardiovascular systems plays a crucial role in obtaining realistic computational models. However, determining the appropriate boundary conditions is challenging due to a lack of information on the contact between the arterial wall and surrounding tissue. This study presents a method to calibrate external tissue support parameters using 4D ultrasound data, and demonstrates that the same tissue support parameter estimates can be used for modeling healthy and diseased states of the vessel.
Modeling of fluid-structure interactions (FSIs) between the deformable arterial wall and blood flow is necessary to obtain physiologically realistic computational models of cardiovascular systems. However, lack of information on the nature of contact between the outer vessel wall and surrounding tissue presents challenges in prescribing appropriate structural boundary conditions. Imaging techniques used to visualize wall deformation in vivo may be useful for estimating simulation parameters that capture the effects of both vascular composition and surrounding tissue support on the vessel wall displacement. Here, we present a method to calibrate external tissue support parameters in FSI simulations against four-dimensional ultrasound (4DUS) of the murine thoracic aortae. We collected ultrasound, blood pressure, and histological data from several mice infused with angiotensin II (n = 4) and created a representative model of healthy and diseased (at 28 days post-angiotensin II infusion) murine aortae. We ran pulsatile FSI simulations after accounting for increased arterial wall stiffness with varying levels of tissue support, which demonstrated non-trivial variation in not only structural quantities, such as vessel wall deformation, but also hemodynamic quantities, such as wall shear stress across simulations. Furthermore, we compared simulation results with in vivo 4DUS imaging data and observed that the suitable range of the tissue support spring parameter was identical for both healthy and diseased states. This indicated that the same tissue support parameter estimates could be used for modeling the healthy and diseased states of the vessel, provided that changes in arterial wall stiffness had been considered. We anticipate this technique and the tissue support estimates reported herein will help inform computational models of blood flow and vasculature that incorporate the influence of external tissue. [GRAPHICS] .
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