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.
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July 2016
Research-Article
Novel Methodology for Characterizing Regional Variations in the Material Properties of Murine Aortas
Matthew R. Bersi,
Matthew R. Bersi
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
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Chiara Bellini,
Chiara Bellini
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
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Paolo Di Achille,
Paolo Di Achille
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
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Jay D. Humphrey,
Jay D. Humphrey
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
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Katia Genovese,
Katia Genovese
School of Engineering,
University of Basilicata,
Potenza 85100, Italy
University of Basilicata,
Potenza 85100, Italy
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Stéphane Avril
Stéphane Avril
INSERM, U1059,
Saint-Etienne 42000, France;
Saint-Etienne 42000, France;
Ecole Nationale Supérieure des
Mines de Saint-Etienne,
CIS-EMSE,
SAINBIOSE,
Saint-Etienne F-42023, France
Mines de Saint-Etienne,
CIS-EMSE,
SAINBIOSE,
Saint-Etienne F-42023, France
Search for other works by this author on:
Matthew R. Bersi
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
Chiara Bellini
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
Paolo Di Achille
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
Jay D. Humphrey
Department of Biomedical Engineering,
Yale University,
New Haven, CT 06520
Yale University,
New Haven, CT 06520
Katia Genovese
School of Engineering,
University of Basilicata,
Potenza 85100, Italy
University of Basilicata,
Potenza 85100, Italy
Stéphane Avril
INSERM, U1059,
Saint-Etienne 42000, France;
Saint-Etienne 42000, France;
Ecole Nationale Supérieure des
Mines de Saint-Etienne,
CIS-EMSE,
SAINBIOSE,
Saint-Etienne F-42023, France
Mines de Saint-Etienne,
CIS-EMSE,
SAINBIOSE,
Saint-Etienne F-42023, France
1Corresponding author.
Manuscript received October 14, 2015; final manuscript received May 10, 2016; published online June 7, 2016. Assoc. Editor: Jonathan Vande Geest.
J Biomech Eng. Jul 2016, 138(7): 071005 (15 pages)
Published Online: June 7, 2016
Article history
Received:
October 14, 2015
Revised:
May 10, 2016
Citation
Bersi, M. R., Bellini, C., Di Achille, P., Humphrey, J. D., Genovese, K., and Avril, S. (June 7, 2016). "Novel Methodology for Characterizing Regional Variations in the Material Properties of Murine Aortas." ASME. J Biomech Eng. July 2016; 138(7): 071005. https://doi.org/10.1115/1.4033674
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