Title:

3D Surface Reconstruction of Quasi-Cylindrical Structures Using Panoramic Digital Image Correlation

Vascular disorders, such as aortic aneurysm and rupture, are dependent on the biomechanical properties of vasculature and supporting structures. Localized defects in the aortic wall have the potential to be catastrophic due to local changes in wall composition and structural integrity [1]. Understanding the localized impact of mechanical defects on vascular microstructures can promote improved diagnosis and prognosis of vascular disorders [2]. To investigate the effects of localized mechanical defects, novel systems capable of capturing local deformations in real time on ex-vivo tissue structures are required. To fulfill this need, a panoramic digital image correlation system (pDIC) was developed to capture the full-field (entire surface) geometry of quasi-cylindrical structures. The pDIC system has the advantage of imaging the entirety of a structure without the need for recalibration after each capture, making dynamic captures of vessel pressurization over time possible. Advancements in pDIC hardware and software workflows have enabled full-field, panoramic capture of quasi-cylindrical structures and reconstruction of surface geometry via image correlations using a static four-camera view. By using a tubular structure with known size and shape, such as a blunt hypodermic needle, this local biomechanical testing system and technique can be validated by first reconstructing the needle shape. Prior success of this reconstruction has established this test case as a reliable ground truth measurement. Future use and improvements on this novel mechanical testing system can improve our current understanding of vascular biomechanics and advance diagnosis of vascular conditions to reduce the impact of localized defects on catastrophic vascular failure. [1] Bersi MR, Bellini C, Di Achille P, Humphrey JD, Genovese K, Avril S. Novel Methodology for Characterizing Regional Variations in the Material Properties of Murine Aortas. J Biomech Eng. 2016 Jul 1;138(7):0710051–07100515. doi: 10.1115/1.4033674. PMID: 27210500; PMCID: PMC4914807. [2] Genovese K, Badel P, Cavinato C, Pierrat B, Bersi MR, Avril S, Humphrey JD. Multi-view digital image correlation systems for in vitro testing of arteries from mice to humans. Exp Mech. 2021 Nov;61(9):1455-1472. doi: 10.1007/s11340-021-00746-1. Epub 2021 Jul 16. PMID: 35370297; PMCID: PMC8972080.

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