Although cement-within-cement revision arthroplasty minimizes the complications associated with removal of secure PMMA, failure at the interfacial region between new and old cement mantles remains a theoretical concern. This article assesses the variability in shear properties of bilaminar cement mantles related to duration of postcure and the use of antibiotic cements. Bilaminar cement mantles were 15% to 20% weaker than uniform mantles (P < .001) and demonstrated variability in shear strength related to duration of postcure of the freshly applied cement (P < .001). The use of Antibiotic Simplex did not significantly influence interfacial cement adhesion (P = .52). Interfacial adhesion by mechanisms other than mechanical interlock plays a significant role in the bond formed between new and old PMMA cements, with an important contribution by diffusion-based molecular interdigitation. In the presence of a secure cement-bone interface, we recommend cement-within-cement revision techniques in suitable patients.

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We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python packages. We find that trainable segmentation offers better accuracy than global or local thresholding methods and requires as few as 100 user-labelled pixels to produce an accurate segmentation. Trainable segmentation presents a balance of accuracy and training time between global/local thresholding and neural networks, when used on transmission electron microscope images of nanoparticles. We also quantitatively investigate the effectiveness of the components of trainable segmentation, its filter kernels and classifiers, in order to demonstrate the use cases for the different filter kernels in ParticleSpy and the most accurate classifiers for different data types. A set of filter kernels is identified that are effective in distinguishing particles from background but that retain dissimilar features. In terms of classifiers, we find that different classifiers perform optimally for different image contrast; specifically, a random forest classifier performs best for high-contrast ADF images, but that QDA and Gaussian Naïve Bayes classifiers perform better for low-contrast TEM images.

The mechanical properties of the short glass fibre reinforced (SGFR) epoxy resin used as the cortical bone analogue in the third-generation Sawbones femurs were investigated for use within orthopaedic benchtop tests. Tensile and four-point bending tests were used to assess the material properties of the SGFR epoxy at both room (22 'C) and body temperatures (37 degrees C). The 20 standardized specimens used for the materials testing were machined from third-generation Sawbones femurs. The flexural properties of the specimens were determined using ASTM D6272-02 and the tensile properties were obtained using ASTM D638-02. The mean (and standard deviation, or SD) values of the modulus of elasticity in four-point bending for room and body temperature specimens of 7.8 (0.64) GPa and 2.8 (0.66) GPa respectively were significantly different (P < 0.001). The mean (and SD) values of the modulus of elasticity in tension for the room and body temperature specimens of 9.4 (0.8) GPa and 5.4 (1.3) GPa respectively were also significantly different (P = 0.02). The modulus of elasticity of SGFR epoxy is highly temperature dependent. A reduction in the modulus of elasticity of up to 63 per cent was observed when increasing the temperature of the specimens from room to body temperature. SGFR epoxy Sawbones do not accurately represent the material properties of bone at body temperature.

The effect of cyclic loading on the torsional stiffness of a polished double-tapered femoral stem was investigated in vitro. Initial torsional stability was compared with torsional stability after cyclic loading. Stems were removed from the cement mantle and reinserted without the use of additional cement. Torsional stability was measured after reinsertion and after further cyclic loading. Subsidence of the stem was observed. No difference in torsional stiffness was observed during loading. No difference between the stiffness before extraction and after reinsertion was observed. Torsional stiffness of an Exeter stem does not decrease after axial subsidence under cyclic loading. Stability is retained after reinsertion into the original cement mantle. Debonding of the Exeter stem is not associated with rotational instability of the implant.