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Full-field strain mapping of healthy and pathological mouse aortas using stereo digital image correlation
Journal article   Open access   Peer reviewed

Full-field strain mapping of healthy and pathological mouse aortas using stereo digital image correlation

Brooks A. Lane, Ricardo J. Cardoza, Susan M. Lessner, Narendra R. Vyavahare, Michael A. Sutton and John F. Eberth
Journal of the mechanical behavior of biomedical materials, v 141, 105745
01 May 2023
PMID: 36893686
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC10081968/pdf/nihms-1881328.pdfView
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Abstract

Arterial biomechanics DIC Mouse aortopathy Stereo imaging Strain map
The murine aorta is a complex, heterogeneous structure that undergoes large and sometimes asymmetrical deformations under loading. For analytical convenience, mechanical behavior is predominantly described using global quantities that fail to capture critical local information essential to elucidating aortopathic processes. Here, in our methodological study, we used stereo digital image correlation (StereoDIC) to measure the strain profiles of speckle-patterned healthy and elastase-infused, pathological mouse aortas submerged in a temperature-controlled liquid medium. Our unique device rotates two 15-degree stereo-angle cameras that gather sequential digital images while simultaneously performing conventional biaxial pressure-diameter and force-length testing. A StereoDIC Variable Ray Origin (VRO) camera system model is employed to correct for high-magnification image refraction through hydrating physiological media. The resultant Green-Lagrange surface strain tensor was quantified at different blood vessel inflation pressures, axial extension ratios, and after aneurysm-initiating elastase exposure. Quantified results capture large, heterogeneous, inflation-related, circumferential strains that are drastically reduced in elastase-infused tissues. Shear strains, however, were very small on the tissue’s surface. Spatially averaged StereoDIC-based strains were generally more detailed than those determined using conventional edge detection techniques.

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Collaboration types
Domestic collaboration
Web of Science research areas
Engineering, Biomedical
Materials Science, Biomaterials
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