On strain-based rupture criterion for ascending aortic aneurysm: The role of fiber waviness

We propose a new approach for constructing strain-based rupture criterion for ascending thoracic aortic aneurysm. The rupture metric is formulated using an effective strain, which is a measure of net strain that the collagen bundles experience after fiber uncrimping. The effective strain is a function of the total strain and the waviness properties of the collagen fibers. In the present work, the waviness properties are obtained from fitting biaxial response data to constitutive models that explicitly consider the collagen waviness and fiber recruitment. Inflation test data from 10 ascending thoracic aortic aneurysm specimens are analyzed. For each specimen, tension-strain data at ∼2300 material points are garnered. The effective strain fields in the configuration immediately before rupture are computed. It is found that the hotspots of the effective strain match the rupture sites very well in all 10 samples. More importantly, the values of effective strain at the hotsopts are closely clustered around 0.1, in contrast to a much wider distribution of the total strain. The study underscores the importance of considering the fiber recruitment in formulating strain-based rupture metric, and suggests that ϵ¯≈0.1, where ϵ¯ is the effective strain metric defined in this work, can be considered as a criterion for assessing the imminent rupture risk of ascending aortic aneurysms. STATEMENT OF SIGNIFICANCE: We advocate to use effective strain in ATAA rupture assessment. The effective strain is a measure of net strain in the collagen network after waviness uncrimping. We analyzed bulge inflation data of ATAA samples. It was found that, while the total strains at rupture varied from sample to sample, the effective strains were closely clustered around 0.1. And the hotspots of effective strain matched the rupture sites well. The work underlines the importance of considering collagen fiber waviness and recruitment when evaluating the rupture risk using strain, and suggests a new direction for developing sharper rupture metrics.