Capturing regional variation in aortic mechanics: dual-estimation method for material parameter identification and biological correlation

Abstract The aorta shows significant regional variation in geometry and composition. This complexity makes numerical modeling challenging, as it requires identifying material parameters. Typically, the Holzapfel-Gasser-Ogden model is used. However, it suffers from nonuniqueness and sensitivity to outliers, which can obscure biological variation. In addition, standard compressible formulations with a volumetric-isochoric split fail to couple volumetric and anisotropic responses. To address these issues, a regularized dual-estimation framework was introduced. This framework combines a global baseline estimator with local refinement while maintaining structural material continuity. Furthermore, it uses a Modified Anisotropic model to improve the representation of compressibility physics. For validation, the approach included uniaxial extension and protein quantification from Wistar rats. The results show that the proximal ascending/aortic-arch segment is most compliant at low stretch, whereas the abdominal aorta stiffens earlier and becomes fiber-dominated at lower stretch levels. Notably, these trends align directionally with regional composition. However, the fitted stress components are model-based descriptors rather than direct measurements of individual constituents.