Novel Methodology for Characterizing Regional Variations in the Material Properties of Murine Aortas

Abstract

Many vascular disorders, including aortic aneurysms and dissections, are characterized by localized changes in wall composition and structure. Notwithstanding the importance of histopathologic changes that occur at the microstructural level, macroscopic manifestations ultimately dictate the mechanical functionality and structural integrity of the aortic wall. Understanding structure-function relationships locally is thus critical for gaining increased insight into conditions that render a vessel susceptible to disease or failure. Given the scarcity of human data, mouse models are increasingly useful in this regard. In this paper, we present a novel inverse characterization of regional, nonlinear, anisotropic properties of the murine aorta. Full-field biaxial data are collected using a panoramic-digital image correlation (p-DIC) system. An inverse method, based on the principle of virtual power (PVP), is used to estimate values of material parameters regionally for a microstructurally motivated constitutive relation. We validate our experimental-computational approach by comparing results to those from standard biaxial testing. The results for the nondiseased suprarenal abdominal aorta from apolipoprotein-E null mice reveal material heterogeneities, with significant differences between dorsal and ventral as well as between proximal and distal locations, which may arise in part due to differential perivascular support and localized branches. Overall results were validated for both a membrane and a thick-wall model that delineated medial and adventitial properties. Whereas full-field characterization can be useful in the study of normal arteries, we submit that it will be particularly useful for studying complex lesions such as aneurysms, which can now be pursued with confidence given the present validation.

Computational predictions of damage propagation preceding dissection of ascending thoracic aortic aneurysms

“…In the current work, we used a genetic algorithm that ensures a global minimum. It was shown to be less sensitive to the mutual influence between and coefficients of exponential strain energy density functions …”

“…Nevertheless, it is also shown that these thickness variations are less important in aneurysms than in healthy aortas . The effect of possible regional variations in the thickness and in the material properties would obviously affect the local values of deposition stretches that we have to assign to elastin, as shown in another paper where the regional variations of a CMT‐based model were reconstructed on mice aortas …”

“…It is noteworthy that those can take different values when fibers are under compression or tension denoted by t and c in Equations 6 and 7. 48…”

Smoothly varying in‐plane stiffness heterogeneity evaluated under uniaxial tensile stress

“…Reduction in size of the VSG reduces resolution (decreases signal to noise) and reduces confidence in strain measurement. VFM is well suited to identify stiffness in homogeneous non-linear materials, [15][16][17][18] but identification in locally non-linear materials requires strain measurements at the limits of current technology.…”

Correlation of Wall Microstructure and Heterogeneous Distributions of Strain in Evolving Murine Abdominal Aortic Aneurysms

“…Namely, the local 2D deformation gradient tensor was estimated from the position vectors of two sides of each triangular domain in the reference and deformed configuration, ultimately allowing the calculation of the 2D Green strain tensor. Further details on the pDIC system, calibration, and analysis can be found elsewhere [2–4,7–8]. …”