Multi-view digital image correlation systems for in vitro testing of arteries from mice to humans

用于体外检测小鼠至人类动脉的多视角数字图像相关系统

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Abstract

BACKGROUND: Digital image correlation (DIC) methods are increasingly used for non-contact optical assessment of geometry and deformation in soft tissue biomechanics, thus providing the full-field strain estimates needed for robust inverse material characterization. Despite the well-known flexibility and ease of use of DIC, issues related to spatial resolution and depth-of-field remain challenging in studies of quasi-cylindrical biological samples such as arteries. OBJECTIVE: After demonstrating that standard surrounding multi-view DIC systems are inappropriate for such usage, we submit that both the optical setup and the data analysis need to be specifically designed with respect to the size of the arterial sample of interest. Accordingly, we propose novel and optimized DIC systems for two distinct ranges of arterial diameters: less than 2.5 mm (murine arteries) and greater than 10 mm (human arteries). METHODS: We designed, set up, and validated a four-camera panoramic-DIC system for testing murine arteries and a multi-biprism DIC system for testing human arteries. Both systems enable dynamic 360-deg measurements with refraction correction over the entire surface of submerged samples in their native geometries. RESULTS: Illustrative results for 3D shape and full-surface deformation fields were obtained for a mouse infrarenal aorta and a latex cylinder of size similar to the human infrarenal aorta. CONCLUSION: Results demonstrated the feasibility and accuracy of both proposed methods in providing quantitative information on the regional behavior of arterial samples tested in vitro under physiologically relevant loading.

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