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Abstract:
Magnesium (Mg)-based implants are highly attractive for the orthopedic field and may replace titanium (Ti) as support for fracture healing. To determine the implant-bone-interaction in different bony regions, we implanted Mg-based alloy ZX00 (Mg < 0.5 Zn < 0.5 Ca, in wt%) and Ti-screws into the distal epiphysis and distal metaphysis of sheep tibiae. The implant degradation and osseointegration were assessed in vivo and ex vivo after 4, 6 and 12 weeks, using a combination of clinical computed tomography (cCT), medium-resolution micro CT (µCT) and high-resolution synchrotron radiation µCT (SRµCT). Implant volume loss, gas formation, and bone growth were evaluated for both implantation sites and each bone region independently. Additionally, histological analysis of bone growth was performed on embedded hard-tissue samples. We demonstrate that in all cases, the degradation rate of ZX00-implants ranges between 0.23-0.75 mm/year. The highest degradation rates were found in the epiphysis. Bone-to-implant-contact varied between the time points and bone types for both materials. Mostly, bone-volume-to-total-volume was higher around Ti-implants. However, we found an increased cortical thickness around the ZX00-screws when compared to the Ti-screws. Our results showed the suitability of ZX00-screws for implantation into the distal meta- and epiphysis

Keywords:
Biodegradable implants,Magnesium-based alloys,Computed tomography,Mg-Zn-Ca,Sheep,Histology

Abstract:
Highly accurate segmentation of large 3D volumes is a demanding task. Challenging applications like the segmentation of synchrotron radiation microtomograms (SRμCT) at high-resolution, which suffer from low contrast, high spatial variability and measurement artifacts, readily exceed the capacities of conventional segmentation methods, including the manual segmentation by human experts. The quantitative characterization of the osseointegration and spatio-temporal biodegradation process of bone implants requires reliable, and very precise segmentation. We investigated the scaling of 2D U-net for high resolution grayscale volumes by three crucial model hyper-parameters (i.e., the model width, depth, and input size). To leverage the 3D information of high-resolution SRμCT, common three axes prediction fusing is extended, investigating the effect of adding more than three axes prediction. In a systematic evaluation we compare the performance of scaling the U-net by intersection over union (IoU) and quantitative measurements of osseointegration and degradation parameters. Overall, we observe that a compound scaling of the U-net and multi-axes prediction fusing with soft voting yields the highest IoU for the class “degradation layer”. Finally, the quantitative analysis showed that the parameters calculated with model segmentation deviated less from the high quality results than those obtained by a semi-automatic segmentation method.