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Damage Identification on Vertebral Bodies During Compressive Loading Using Digital Image Correlation

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Study Design. Ex vivo compression experiments on isolated cadaveric vertebrae. Objective. To qualitatively compare the fracture locations identified in video analysis with the locations of high compressive strain measured with… Click to show full abstract

Study Design. Ex vivo compression experiments on isolated cadaveric vertebrae. Objective. To qualitatively compare the fracture locations identified in video analysis with the locations of high compressive strain measured with digital image correlation (DIC) on vertebral bodies and to evaluate the timing of local damage to the cortical shell relative to the global yield force. Summary of Background Data. In previous ex vivo experiments, cortical bone fracture has been identified using various methods including acoustic emission sensors, strain gages, video analysis, or force signals. These methods are, however, limited in their ability to detect the location and timing of fracture. We propose use of DIC, a noncontact optical technique that measures surface displacement, to quantify variables related to damage. Methods. Isolated thoracolumbar human cadaveric vertebral bodies (nā€Š=ā€Š6) were tested in compression to failure at a quasi-static rate, and the force applied was measured using a load cell. The surface displacement and strain were measured using DIC. Video analysis was performed to identify fractures. Results. The location of fractures identified in the video corresponded well with the locations of high compressive strain on the bone. Before reaching the global yield force, more than 10% of the DIC measurements reached a minimum principal strain of 1.0%, a previously reported threshold for cortical bone damage. Conclusion. DIC measurements provide an objective measure that can be used to identify the location and timing of fractures during ex vivo vertebral experiments. This is important for understanding fracture mechanics and for validating vertebral computational models that incorporate failure. Level of Evidence: N /A

Keywords: vertebral bodies; fracture; digital image; damage; strain; image correlation

Journal Title: SPINE
Year Published: 2017

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