Local variations in material and structural properties characterize murine thoracic aortic aneurysm mechanics

Abstract

We recently developed an approach to characterize local nonlinear, anisotropic mechanical properties of murine arteries by combining biaxial extension-distension testing, panoramic digital image correlation (pDIC), and an inverse method based on the principle of virtual power. This experimental-computational approach was illustrated for the normal murine abdominal aorta assuming uniform wall thickness. Here, however, we extend our prior approach by adding an optical coherence tomography (OCT) imaging system that permits local reconstructions of wall thickness. This multi-modality approach is then used to characterize spatial variations of material and structural properties in ascending thoracic aortic aneurysms (aTAA) from two genetically modified mouse models (fibrillin-1 and fibulin-4 deficient) and to compare them with those from angiotensin-II infused apolipoprotein-E deficient and wild-type control aortas. Local values of stored elastic energy and biaxial material stiffness, computed from spatial distributions of the bestfit material parameters, varied significantly with circumferential position (inner vs. outer curvature, ventral vs. dorsal sides) across genotypes and treatments. Importantly, these data reveal an inverse relationship between material stiffness and wall thickness that underlies a general linear relationship between stiffness and wall stress across aTAAs. OCT images also revealed sites of advanced medial degeneration, which were captured by the inverse material characterization. Quantification of histological data further provided high resolution local correlations amongst multiple mechanical metrics and wall microstructure. This is the first time that such structural defects and local properties have been characterized mechanically, which can better inform computational models of aortopathy that seek to predict where dissection or rupture may initiate.

Numerical knockouts–In silico assessment of factors predisposing to thoracic aortic aneurysms

“…These predicted changes are consistent with measured changes in the non-aneurysmal descending thoracic aorta in Fbn1 mgR/mgR mice, which have compromised elastic fiber integrity [ 32 ], though there was no attempt here to refine the model parameters to fit any particular data set. That the maximal changes co-localized with the region of maximal dilatation is also consistent with experimental (passive) measurements [ 43 ].…”

“…Finally, many biomechanical metrics provide important insight into the state of aortic health or disease, including biaxial (circumferential and axial) wall stretch, stress, and material stiffness as well as elastic energy storage. Of these, elastic energy storage is a key indicator of mechanical functionality [ 41 , 42 ] while the value of circumferential material stiffness appears to be a particularly important indicator of aneurysmal propensity or presence [ 32 , 43 ]. Neither quantity can be measured directly; they are best computed from an appropriate nonlinear constitutive model of the aortic wall, modeled here with a 3-D finite element geometry.…”

A Probabilistic and Anisotropic Failure Metric for Ascending Thoracic Aortic Aneurysm Risk Stratification

“…It is known that the hyperelastic and failure properties of aortic wall are regional dependent [18,66]. The wall thickness may also have spatial variations, and heterogeneity of wall thickness and material heterogeneity could be correlated [67]. In the FE simulations, a simplified case was considered, where the wall thickness was calculated from an averaged experimentally measured value, and the experimentally-derived hyperelastic behavior was used for the entire ATAA geometry.…”

On improving the accuracy of nonhomogeneous shear modulus identification in incompressible elasticity using the virtual fields method

“…We observed from both simulations and experiments that the proposed virtual fields performed much better in identifying the shear moduli of incompressible solids than the conventional virtual fields. This reveals that the conventional approach, though prevalent in solving parameter identification problems [20,[27][28][29], leads to errors in the identified shear modulus values. Conversely, the proposed virtual fields are capable of identifying shear moduli with very high precision for incompressible and nonhomogeneous solids.…”