Abstract. Objectives. This study aids the control of remodelling and strain response in bone; providing a quantified map of apparent modulus and strength in the proximal tibia in 3 anatomically relevant directions in terms of apparent density and factor groups. Methods. 7 fresh-frozen cadaveric specimens were quantified computed tomography (qCT) scanned, segmented and packed with 3 layers of 9mm side length cubic cores aligned to anatomical mechanical axes. Cores were removed with printed custom cutting and their densities found from qCT. Cores (n = 195) were quasi-statically compression tested. Modulus was estimated from a load cycle hysteresis loop, between 40% and 20% of yield stress. Sequential testing order in 3 orthogonal directions was randomised. Group differences were identified via an analysis of variance for the factors density, age, gender, testing order, subchondral depth, condyle and sub-meniscal location. Regression models were fit for significant factor sub-groups, predicting properties from density. Results. Axial modulus was 1.5 times greater than the two transverse directions (p<0.001), between which no difference was found. For all test directions, differences were quantified for density and modulus across all subchondral depths (p<0.001). 60% of transverse modulus variation was explained by density within subgroups for each subchondral depth. Medial axial modulus was 1.3 times greater than the lateral side (p = 0.011). Lateral axial modulus halved over a 25mm depth whilst remaining constant for the medial side. Density explained 75% of variation when grouped by subchondral depth and condyle. Yield strength was well predicted across all test directions, with density explaining 81% of axial strength variation and no differences over subchondral depth. Conclusions. The quantification of bone multiaxial modulus based on condyle and subchondral depth has been shown for the first time in a clinically viable protocol using conventional CT. Accounting for spatial variation improves upon literature property prediction models. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Good lag screw holding power in trabecular bone of the femoral head is a requisite to achieve stability in the management of proximal femoral fractures. It has been demonstrated that insertion torque and pullout strength of lag screw are linearly correlated. Therefore, insertion torque measurement could be a method to estimate the achieved screw purchase. Manual perception is not reliable [1], but the use of an instrumented screwdriver would make the procedure feasible. The aim of this study was to assess the accuracy achievable using the insertion torque as predictor of lag screw purchase. Four different screw designs (two cannulated and two solid-core screws) were investigated in this study. Each screw was inserted into a block of trabecular bone tissue following a standardised procedure designed to maximise the experimental repeatability. The blocks of trabecular tissue were extracted from human as well as bovine femora to increase the range of bone mineral density. The prediction accuracy was evaluated by plotting pullout strength versus insertion torque, performing a linear regression analysis and calculating the difference (as percentage) between predicted and measured values. Insertion torque showed a strong linear correlation (coefficient of determination R. 2. : 0.95–0.99) with the pullout strength of lag screw. However the prediction error in pullout strength estimation was greater than 40% for small values of insertion torque, decreasing down to 15% when the lag screw was driven into good quality bone tissue. Measuring insertion torque can supply quantitative information about the achieved lag screw purchase. Since screw design and insertion procedure have been shown to affect both the insertion torque and the pullout strength [2], the prediction model must be screw-specific and determined, closely simulating the clinical procedure defined by the screw manufacturer. However, the surgeon must be aware that, even under highly repeatable experimental conditions, the prediction error was found to be high when small insertion torque was measured, i.e. when the screw was driven in low quality bone tissue. Therefore, insertion torque is not reliable in evaluating lag screw purchase in the management of proximal femur fracture of osteoporotic patients

Objectives

Electronic forms of data collection have gained interest in recent years. In orthopaedics, little is known about patient preference regarding pen-and-paper or electronic questionnaires. We aimed to determine whether patients undergoing total hip (THR) or total knee replacement (TKR) prefer pen-and-paper or electronic questionnaires and to identify variables that predict preference for electronic questionnaires.