Bone Damage Evolution Around Integrated Metal Screws Using X-Ray Tomography — in situ Pullout and Digital Volume Correlation

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Abstract

Better understanding of the local deformation of the bone network around metallic implants subjected to loading is of importance to assess the mechanical resistance of the bone-implant interface and limit implant failure. In this study, four titanium screws were osseointegrated into rat tibiae for 4 weeks and screw pullout was conducted in situ under x-ray microtomography, recording macroscopic mechanical behavior and full tomographies at multiple load steps before failure. Images were analyzed using Digital Volume Correlation (DVC) to access internal displacement and deformation fields during loading. A repeatable failure pattern was observed, where a ∼300–500 μm-thick envelope of bone detached from the trabecular structure. Fracture initiated close to the screw tip and propagated along the implant surface, at a distance of around 500 μm. Thus, the fracture pattern appeared to be influenced by the microstructure of the bone formed closely around the threads, which confirmed that the model is relevant for evaluating the effect of pharmacological treatments affecting local bone formation. Moreover, cracks at the tibial plateau were identified by DVC analysis of the tomographic images acquired during loading. Moderate strains were first distributed in the trabecular bone, which localized into higher strains regions with subsequent loading, revealing crack-formation not evident in the tomographic images. The in situ loading methodology followed by DVC is shown to be a powerful tool to study internal deformation and fracture behavior of the newly formed bone close to an implant when subjected to loading. A better understanding of the interface failure may help improve the outcome of surgical implants.

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Le Cann, S., Tudisco, E., Tägil, M., Hall, S. A., & Isaksson, H. (2020). Bone Damage Evolution Around Integrated Metal Screws Using X-Ray Tomography — in situ Pullout and Digital Volume Correlation. Frontiers in Bioengineering and Biotechnology, 8. https://doi.org/10.3389/fbioe.2020.00934

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