Osteosynthesis aims to maintain fracture reduction until bone healing occurs, which is not achieved in case of mechanical fixation failure. One form of failure is plastic plate bending due to overloading, occurring in up to 17% of midshaft fracture cases and often necessitating reoperation. This study aimed to replicate in-vivo conditions in a cadaveric experiment and to validate a finite element (FE) simulation to predict plastic plate bending. Six cadaveric bones were used to replicate an established ovine tibial osteotomy model with locking plates in-vitro with two implant materials (titanium, steel) and three fracture gap sizes (30, 60, 80 mm). The constructs were tested monotonically until plastic plate deformation under axial compression. Specimen-specific FE models were created from CT images. Implant material properties were determined using uniaxial tensile testing of dog bone shaped samples. The experimental tests were replicated in the simulations. Stiffness, yield, and maximum loads were compared between the experiment and FE models. Implant material properties (Young's modulus and yield stress) for steel and titanium were 184 GPa and 875 MPa, and 105 GPa and 761 MPa, respectively. Yield and maximum loads of constructs ranged between 469–491 N and 652–683 N, and 759–995 N and 1252–1600 N for steel and titanium fixations, respectively. FE models accurately and quantitatively correctly predicted experimental results for stiffness (R2=0.96), yield (R2=0.97), and ultimate load (R2=0.97). FE simulations accurately predicted plastic plate bending in osteosynthesis constructs. Construct behavior was predominantly driven by the implant itself, highlighting the importance of modelling correct material properties of metal. The validated FE models could predict subject-specific load bearing capacity of osteosyntheses in vivo in preclinical or clinical studies. Acknowledgements: This study was supported by the AO Foundation via the AOTRAUMA Network (Grant No.: AR2021_03)

Anterior approach total hip arthroplasty (AA-THA) has a steep learning curve, with higher complication rates in initial cases. Proper surgical case selection during the learning curve can reduce early risk. This study aims to identify patient and radiographic factors associated with AA-THA difficulty using Machine Learning (ML). Consecutive primary AA-THA patients from two centres, operated by two expert surgeons, were enrolled (excluding patients with prior hip surgery and first 100 cases per surgeon). K- means prototype clustering – an unsupervised ML algorithm – was used with two variables - operative duration and surgical complications within 6 weeks - to cluster operations into difficult or standard groups. Radiographic measurements (neck shaft angle, offset, LCEA, inter-teardrop distance, Tonnis grade) were measured by two independent observers. These factors, alongside patient factors (BMI, age, sex, laterality) were employed in a multivariate logistic regression analysis and used for k-means clustering. Significant continuous variables were investigated for predictive accuracy using Receiver Operator Characteristics (ROC). Out of 328 THAs analyzed, 130 (40%) were classified as difficult and 198 (60%) as standard. Difficult group had a mean operative time of 106mins (range 99–116) with 2 complications, while standard group had a mean operative time of 77mins (range 69–86) with 0 complications. Decreasing inter-teardrop distance (odds ratio [OR] 0.97, 95% confidence interval [CI] 0.95–0.99, p = 0.03) and right-sided operations (OR 1.73, 95% CI 1.10–2.72, p = 0.02) were associated with operative difficulty. However, ROC analysis showed poor predictive accuracy for these factors alone, with area under the curve of 0.56. Inter-observer reliability was reported as excellent (ICC >0.7). Right-sided hips (for right-hand dominant surgeons) and decreasing inter-teardrop distance were associated with case difficulty in AA-THA. These data could guide case selection during the learning phase. A larger dataset with more complications may reveal further factors

Abstract. Objectives. Identifying risk factors for inferior outcomes after anterior cruciate ligament reconstruction (ACLR) is important for prognosis and patient information. This study aimed to ascertain if BMI, pre-operative scores, demographic data and concomitant injuries in patients undergoing ACLR affected patient-reported functional outcomes. Methods. A prospective review collected data from a single surgeon series of 278 patients who underwent arthroscopic ACLR. BMI, age, gender, graft choice, pre-op Lysholm score, meniscal and chondral injuries were recorded. The Lysholm score, hop test and KT1000 were used to measure post-op functional outcome at one year. Multiple regression analysis was used to determine factors that predicted Lysholm scores at one year. Results. The mean age was 29 years, with 58 female and 220 male patients. The mean pre-op Lysholm score was 53.8. One hunded and seventy-nine patients had meniscal injuries, of which 81 were medial, 60 lateral, and 38 bilateral. Eighteen patients also had chondral injury and 106 patients had no other associated injury. Age, gender, graft type and presence of meniscal or chondral injuries did not affect one-year post-operative Lysholm scores. A BMI greater than 30, physio compliance and preoperative Lysholm scores helped predict one-year post-operative Lysholm scores (p=0.02). Pearson's correlation found a direct link between BMI and post-operative Lysholm (p=0.03). Conclusions. BMI, physio compliance and pre-operative Lysholm scores are the most significant determinants of short-term functional outcome after ACLR. However, the effects of associated injuries may be apparent in the long-term as degenerative changes set in or the continued detriment resulting from the concomitant injury affect outcome. 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

Multiple biochemical biomarkers have been previously investigated for the diagnosis, prognosis and response to treatment of articular cartilage damage, including osteoarthritis (OA). Synovial fluid (SF) biomarker measurement is a potential method to predict treatment response and effectiveness. However, the significance of different biomarkers and their correlation to clinical outcomes remains unclear. This systematic review evaluated current SF biomarkers used in investigation of cartilage degeneration or regeneration in the knee joint and correlated these biomarkers with clinical outcomes following cartilage repair or regeneration interventions. PubMed, Institute of Science Index, Scopus, Cochrane Central Register of Controlled Trials, and Embase databases were searched. Studies evaluating SF biomarkers and clinical outcomes following cartilage repair intervention were included. Two researchers independently performed data extraction and QUADAS-2 analysis. Biomarker inclusion, change following intervention and correlation with clinical outcome was compared. 9 studies were included. Study heterogeneity precluded meta-analysis. There was significant variation in sampling and analysis. 33 biomarkers were evaluated in addition to microRNA and catabolic/anabolic ratios. Five studies reported on correlation of biomarkers with six biomarkers significantly correlated with clinical outcomes following intervention. However, correlation was only demonstrated in isolated studies. This review demonstrates significant difficulties in drawing conclusions regarding the importance of SF biomarkers based on the available literature. Improved standardisation for collection and analysis of SF samples is required. Future publications should also focus on clinical outcome scores and seek to correlate biomarkers with progression to further understand the significance of identified markers in a clinical context

Proximal humerus fractures are the third most common fragility fractures with treatment remaining challenging. Mechanical fixation failure rates of locked plating range up to 35%, with 80% of them being related to the screws perforating the glenohumeral joint. Secondary screw perforation is a complex and not yet fully understood process. Biomechanical testing and finite element (FE) analysis are expected to help understand the importance of various risk factors. Validated FE simulations could be used to predict perforation risk. This study aimed to (1) develop an experimental model for single screw perforation in the humeral head and (2) evaluate and compare the ability of bone density measures and FE simulations to predict the experimental findings. Screw perforation was investigated experimentally via quasi-static ramped compression testing of 20 cuboidal bone specimens at 1 mm/min. They were harvested from four fresh-frozen human cadaveric proximal humeri of elderly donors (aged 85 ± 5 years, f/m: 2/2), surrounded with cylindrical embedding and implanted with a single 3.5 mm locking screw (DePuy Synthes, Switzerland) centrally. Specimen-specific linear µFE (ParOSol, ETH Zurich) and nonlinear explicit µFE (Abaqus, SIMULIA, USA) models were generated at 38 µm and 76 µm voxel sizes, respectively, from pre- and post-implantation micro-Computed Tomography (µCT) images (vivaCT40, Scanco Medical, Switzerland). Bone volume (BV) around the screw and in front of the screw tip, and tip-to-joint distance (TJD) were evaluated on the µCT images. The µFE models and BV were used to predict the experimental force at the initial screw loosening and the maximum force until perforation. Initial screw loosening, indicated by the first peak of the load-displacement curve, occurred at a load of 64.7 ± 69.8 N (range: 10.2 – 298.8 N) and was best predicted by the linear µFE (R. 2. = 0.90), followed by BV around the screw (R. 2. = 0.87). Maximum load was 207.6 ± 107.7 N (range: 90.1 – 507.6 N) and the nonlinear µFE provided the best prediction (R. 2. = 0.93), followed by BV in front of the screw tip (R. 2. = 0.89). Further, the nonlinear µFE could better predict screw displacement at maximum force (R. 2. = 0.77) than TJD (R. 2. = 0.70). The predictions of non-linear µFE were quantitatively correct. Our results indicate that while density-based measures strongly correlate with screw perforation force, the predictions by the nonlinear explicit µFE models were even better and, most importantly, quantitatively correct. These models have high potential to be utilized for simulation of more realistic fixations involving multiple screws under various loading cases. Towards clinical applications, future studies should investigate if explicit FE models based on clinically available CT images could provide similar prediction accuracies

Background. Although there are predictive equations that estimate the total fat mass obtained from multiple-site ultrasound (US) measurements, the predictive equation of total fat mass has not been investigated solely from abdominal subcutaneous fat thickness. Therefore, the aims of this study were; (1) to develop regression-based prediction equations based on abdominal subcutaneous fat thickness for predicting fat mass in young- and middle-aged adults, and (2) to investigate the validity of these equations to be developed. Methods. The study was approved by the Local Research Ethics Committee (Decision number: GO 19/788). Twenty-seven males (30.3 ± 8.7 years) and eighteen females (32.4 ± 9.5 years) were randomly divided into two groups as the model prediction group (19 males and 12 females) and the validation group (8 males and 6 females). Total body fat mass was determined by dual-energy X-ray absorptiometry (DXA). Abdominal subcutaneous fat thickness was measured by US. The predictive equations for total fat mass from US were determined as fat thickness (in mm) × standing height (in m). Statistical analyses were performed using R version 4.0.0. The association between the total fat mass and the abdominal subcutaneous fat thickness was interpreted using the Pearson test. The linear regression analysis was used to predict equations for total body fat mass from the abdominal subcutaneous fat thickness acquired by US. Then these predictive equations were applied to the validation group. The paired t-test was used to examine the difference between the measured and the predicted fat masses, and Lin's concordance correlation coefficient (CCC) was used as a further measure of agreement. Results. There was a significant positive moderate correlation between the total fat mass and the abdominal subcutaneous fat thickness × height in the model prediction group of males (r = 0.588, p = 0.008), whereas significant positive very strong correlation was observed in the model prediction group of females (r = 0.896, p < 0.001). Predictive equations for DXA-measured total body fat mass from abdominal subcutaneous fat thickness using US were as follows: for males “Fat mass-DXA = 0.276 × (Fat thickness-US × Height) + 17.221” (R. 2. = 0.35, SEE = 3.6, p = 0.008); for females “Fat mass-DXA = 0.694 x (Fat thickness-US × Height) + 7.085” (R. 2. = 0.80, SEE = 2.8, p < 0.001). When fat mass prediction equations were applied to the validation groups, measured- and estimated-total fat masses in males and females were found similar (p = 0.9, p = 0.5, respectively). A good level of agreement between measurements in males and females was attained (CCC = 0.84, CCC = 0.76, respectively). Conclusion. We developed and validated prediction equations that are convenient for determining total fat masses in young- and middle-aged adults using abdominal subcutaneous fat thickness obtained from the US. The abdominal subcutaneous fat thickness obtained from a single region by US might provide a noninvasive quick and easy evaluation not only in clinical settings but also on the field

Objectives. Intramedullary fixation is considered the most stable treatment for pertrochanteric fractures of the proximal femur and cut-out is one of the most frequent mechanical complications. In order to determine the role of clinical variables and radiological parameters in predicting the risk of this complication, we analysed the data pertaining to a group of patients recruited over the course of six years. Methods. A total of 571 patients were included in this study, which analysed the incidence of cut-out in relation to several clinical variables: age; gender; the AO Foundation and Orthopaedic Trauma Association classification system (AO/OTA); type of nail; cervical-diaphyseal angle; surgical wait times; anti-osteoporotic medication; complete post-operative weight bearing; and radiological parameters (namely the lag-screw position with respect to the femoral head, the Cleveland system, the tip-apex distance (TAD), and the calcar-referenced tip-apex distance (CalTAD)). Results. The incidence of cut-out across the sample was 5.6%, with a higher incidence in female patients. A significantly higher risk of this complication was correlated with lag-screw tip positioning in the upper part of the femoral head in the anteroposterior radiological view, posterior in the latero-lateral radiological view, and in the Cleveland peripheral zones. The tip-apex distance and the calcar-referenced tip-apex distance were found to be highly significant predictors of the risk of cut-out at cut-offs of 30.7 mm and 37.3 mm, respectively, but the former appeared more reliable than the latter in predicting the occurrence of this complication. Conclusion. The tip-apex distance remains the most accurate predictor of cut-out, which is significantly greater above a cut-off of 30.7 mm. Cite this article: G. Caruso, M. Bonomo, G. Valpiani, G. Salvatori, A. Gildone, V. Lorusso, L. Massari. A six-year retrospective analysis of cut-out risk predictors in cephalomedullary nailing for pertrochanteric fractures: Can the tip-apex distance (TAD) still be considered the best parameter?. Bone Joint Res 2017;6:481–488. DOI: 10.1302/2046-3758.68.BJR-2016-0299.R1

Pre-operative 3D glenoid planning improves component placement in terms of version, inclination, offset and orientation. Version and inclination measurements require the position of the inferior angle. As a consequence, current planning tools require a 3D model of the full scapula to accurately determine the glenoid parameters. Statistical shape models (SSMs) can be used to reconstruct the missing anatomy of bones. Therefore, the objective of this study is to develop and validate an SSM for the reconstruction of the inferior scapula, hereby reducing the irradiation exposure for patients. The training dataset for the statistical shape consisted of 110 CT images from patients without observable scapulae pathologies as judged by an experienced shoulder surgeon. 3D scapulae models were constructed from the segmented images. An open-source non-rigid B-spline-based registration algorithm was used to obtain point-to-point correspondences between the models. A statistical shape model was then constructed from the dataset using principal component analysis. Leave-one-out cross-validation was performed to evaluate the accuracy of the predicted glenoid parameters from virtual partial scans. Five types of virtual partial scans were created on each of the training set models, where an increasing amount of scapular body was removed to mimic a partial CT scan. The statistical shape model was reconstructed using the leave-one-out method, so the corresponding training set model is no longer incorporated in the shape model. Reconstruction was performed using a Monte Carlo Markov chain algorithm, random walk proposals included both shape and pose parameters, the closest fitting proposal was selected for the virtual reconstruction. Automatic 3D measurements were performed on both the training and reconstructed 3D models, including glenoid version, inclination, glenoid centre point position and glenoid offset. In terms of inclination and version we found a mean absolute difference between the complete model and the different virtual partial scan models of 0.5° (SD 0.4°). The maximum difference between models was 3° for inclination and 2° for version. For offset and centre point position the mean absolute difference was 0 mm with an absolute maximum of 1 mm. The magnitude of the mean and maximum differences for all anatomic measurements between the partial scan and complete models is smaller than the current surgical accuracy. Considering these findings, we believe a SSM based reconstruction technique can be used to accurately reconstruct the glenoid parameters from partial CT scans

Worldwide, osteoporosis, causes more than 8.9 million fractures annually, resulting in an osteoporotic fracture every 3 seconds, where 1 in every 3 women and 1 in every 5 men aged over 50 will experience osteoporotic fractures at least once in their lifetime. Vertebral fractures, estimated at 1.4 million/year are among the most common fractures, posing enormous health and socioeconomic challenges to the individual and society at large. Considering that the great majority of individuals at high risk (up to 80%), who have already had at least one osteoporotic fracture, are neither identified nor treated, prediction of the risk factors for vertebral fractures can be of great value for prevention/early diagnosis. Recent studies show that finite element analysis of computed tomography (CT) scans provides noninvasive means to assess fracture risk and has the potential to be clinically implemented upon proper validation. The objective of this study was to develop a voxel-based finite element model using quantitative computed tomography (QCT) images in conjunction with in-vitro experiments to evaluate the strength of the vertebral bodies and predict the fracture risk criteria. A total of 10 vertebrae were dissected from juvenile sheep lumbar spines. The attached soft tissues and posterior elements and facet joints were completely removed, and the upper and lower vertebral bodies were polished using glass paper to provide smooth surfaces. The specimens were wrapped in phosphate buffer saline (PBS) soaked gauze, sealed in plastic bags, and stored in a refrigerator at −22°C. QCT scans of the specimens were captured using a bone density calibration phantom (QRM Co., Moehrendorf, Germany) with three 18 mm cylindrical inserts, providing 0, 100 and 200 mg HA/ccm, respectively. All the specimens, preserved hydrated in PBS solution, were mechanically tested at room temperature using a mechanical testing apparatus (Zwick/Roell, Ulm-Germany). The QCT images were then used to reconstruct the voxel-based FE model employing a custom-developed heterogeneous material mapping code. Five different equations for the correlation of the density and the elastic modulus were used to validate the efficiency of the FE model as compared to the in-vitro experiments. The results of the voxel-based FE models matched well with the in-vitro experiments, with an average error of 11.38 (±4.09)% based on the power law equation. A failure criterion was embedded in the FE models and the initiation of fracture was successfully predicted for all specimens. Further, typical kyphoplasty treatment was simulated in the 5 models to evaluate the application of the validated algorithm in the estimation of the failure patterns. Our novel voxel-based FE model can be used in future studies to predict the outcome of different types of therapeutic modalities/surgeries and estimate fracture risk including postoperative fractures

Summary Statement. The constraint behavior of total knee arthroplasty (TKA) prosthesis usually has to be physically tested. This study presents a computer simulation model using finite element analysis (FEA) and demonstrates its effectiveness in predicting the femorotibial constraint behavior of TKA implants. Introduction. TKA prostheses are semi-constrained artificial joints. A well-functioning TKA prosthesis should be designed with a good balance between stability and mobility, meaning the femorotibial constraint of the artificial joint cannot be excessive or too lax. To assess the constraint behavior of a TKA prosthesis, physical testing is usually required, and an industrial test standard has been developed for this purpose. Benefiting from technological advancement, computer simulation has become increasingly useful in many industries, including medical device research and development. FEA has been extensively used in stress analysis and structural evaluation of various orthopaedic implants. This study presented an FEA-based simulation to evaluate the femorotibial constraint behavior of TKA prosthesis, and demonstrated the effectiveness of the method by validating it through physical testing. Methods. A Cruciate Retaining (CR) TKA prosthesis design (Optetrak Logic CR, size 3, Exactech, FL, USA) was used in this study. The prosthesis system consists of a femoral component, a tibial insert, and a tibial baseplate. CAD models of the implants assembled at 0° of flexion were used for the simulation. Finite element models were generated using 10-node tetrahedral elements, with all materials considered linear elastic. Boundary conditions were set up according to the ASTM F1223 standard. The tibial baseplate was fixed distally. A constant compressive force (710 N) was applied on the femoral component. Nonlinear Surface-Surface-Contact was defined at the femorotibial articulating surfaces as well as between the tibial insert and tibial baseplate. A coefficient of friction of 0.2 determined from the physical test was input into the simulation. The femoral component was driven under a displacement-controlled scheme to slide along the anterior-posterior (AP) direction on the tibial insert. At each time step, constraint force occurring at the articulating surface was derived from the reaction force at the distal fixation of the tibial baseplate. The force-displacement curve was plotted by combining the results of all time steps to characterize the constraint behavior of the prosthesis. A nonlinear FEA solver (NX Nastran SOL601, Siemens, TX, USA) was used to solve the simulation. In addition, five samples of the prostheses were physically tested per ASTM F1223. Simulation results were compared to the physical testing. Results. The simulation successfully captured the movement of contact location and pressure along the movement of the femoral component. The force-displacement curve predicted by the simulation exhibited a very close hysteresis loop profile as the results of physical testing. Using the curve slope from 0 to 5 mm to characterise the constraint in the most relevant displacement range, the simulation predicted 45.7 N/mm anteriorly and 36.4 N/mm posteriorly, which are less than 10% different from the physical testing results (46.4 N/mm anteriorly and 39.6 N/mm posteriorly). Discussion/Conclusion. This study demonstrated that the simulation was able to closely predict the femorotibial constraint behavior of the TKA prosthesis under ASTM F1223 testing. The simulation results resembled the physical test results not only in the general profile of the curve but also in the magnitude of slope values. The increased difference at the far anterior region could be related to the fact that no material nonlinearity was considered in the current simulation, a factor that could be improved in future studies. A validated simulation method could be very useful in TKA prosthesis design. Since no physical prototypes are required, design evaluation and optimization can be achieved in a much easier and faster manner

A principle of Total Knee Arthroplasty (TKA) is to achieve a neutral standing coronal alignment of the limb (Hip Knee Ankle (HKA) angle) to reduce risks of implant loosening, reduce polyethylene wear, and optimise patella tracking. Several long-term studies have questioned this because the relationship between alignment and implant survivorship is weaker than previously reported. We hypothesize standing HKA poorly predicts implant failure because it does not predict dynamic HKA, dynamic adduction moment, and loading of the knee during gait. Therefore, the aim of our study is to assess the relationship between the standing (or static) and the dynamic (gait activity) HKAs. We performed a prospective study on a cohort of 35 patients (35 knees) who were treated with a posterior-stabilized TKA for primary osteoarthritis between November 2012 and January 2013. Three months after surgery each patient had a standardized digital full-leg coronal radiographs and was classified as neutrally aligned TKA (17 patients), varus aligned (9 patients), and valgus aligned (4 patients). Patients then performed a gait analysis for level walking and dynamic HKA and adduction moment during the stance phase of gait were measured. We found standing HKA having a moderate correlation with the peak dynamic varus (r=0.318, p=0.001) and the mean and peak adduction moments (r=0.31 and r=-0.352 respectively). In contrast we did not find a significant correlation between standing HKA and the mean dynamic coronal alignment (r=0.14, p=0.449). No significant differences were found for dynamic frontal parameters (dynamic HKA and adduction moment) between patients defined as neutrally aligned or varus aligned. In our practice, the standing HKA after TKA was of little value to predict dynamic behaviour of the limb during gait. These results may explain why standing coronal alignment after TKA may have limited influence on long term implant fixation and wear

Summary Statement. A coupled finite element - analytical model is presented to predict and to elucidate a clinical healing scenario where bone regenerates in a critical-sized femoral defect, bounded by periosteum or a periosteum substitute implant and stabilised via an intramedullary nail. Introduction. Bone regeneration and maintenance processes are intrinsically linked to mechanical environment. However, the cellular and subcellular mechanisms of mechanically-modulated bone (re-) generation are not fully understood. Recent studies with periosteum osteoprogenitor cells exhibit their mechanosensitivity in vitro and in situ. In addtion, while a variety of growth factors are implicated in bone healing processes, bone morphogenetic protein-2 (BMP-2) is recognised to be involved in all stages of bone regeneration. Furthermore, periosteal injuries heal predominantly via endochondral ossification mechanisms. With this background in mind, the current study aims to understand the role of mechanical environment on BMP-2 production and periosteally-mediated bone regeneration. The one-stage bone transport model [1] provides a clinically relevant experimental platform on which to model the mechanobiological process of periosteum-mediated bone regeneration in a critical-sized defect. Here we develop a model framework to study the cellular-, extracellular- and mechanically-modulated process of defect infilling, governed by the mechanically-modulated production of BMP-2 by osteoprogenitor cells located in the periosteum. Methods. Material properties of the healing callus and periosteum contribute to the strain stimulus sensed by osteoprogenitor cells therein. Using a mechanical finite element model, periosteal surface strains are first predicted as a function of callus properties. Strains are then input to a mechanistic mathematical model, where mechanical regulation of BMP-2 production mediates rates of cellular proliferation, differentiation and extracellular matrix (ECM) production, to predict healing outcomes. A parametric approach enables the spatial and temporal prediction of tissue regeneration via endochondral ossification. Predictions are compared with experimental, micro-computed tomographic and histologic, measures of cartilage and mineralised bone tissue regenerates. Model Predictions in Light of Experimental Case Studies: A validated baseline model predicts defect healing via cellular egression, extracellular matrix production and endochondral ossification, using parameters optimised to mimic experimental outcome measures at initial and final stages of healing. To elucidate which predictive model paramenters result in the intrinsic differences in experimental outcomes between defects bounded by either periosteum in situ or a periosteum substitute implant, model parameters are then varied by orders of magnitude to determine which factors exert dominant influence on achievement of experimentally relevant ECM area outcomes. Considering the complete set of parameters relevant to healing, the rate of osteoprogenitor to osteoblast differentiation, as well as rates of chondrocyte and osteoblast proliferation must be reduced and ECM production by chondrocytes must be increased from baseline, to achieve healing outcomes analogous to those observed in experiments. Discussion/Conclusion. The novel model framework presented here integrates a mechanistic feedback system, based on the mechanosensitivity of periosteal osteoprogenitor cells, which allows for modeling and prediction of tissue regeneration on multiple length and time scales

The ability to predict load-bearing capacity during the consolidation phase in distraction osteogenesis by non-invasive means would represent a significant advance in the management of patients undergoing such treatment. Measurements of stiffness have been suggested as a promising tool for this purpose. Although the multidimensional characteristics of bone loading in compression, bending and torsion are apparent, most previous experiments have analysed only the relationship between maximum load-bearing capacity and a single type of stiffness. We have studied how compressive, bending and torsional stiffness are related to the torsional load-bearing capacity of healing callus using a common set of samples of bone regenerate from 26 sheep treated by tibial distraction osteogenesis. Our findings showed that measurements of torsional, bending and compressive stiffness were all suitable as predictors of the load-bearing capacity of healing callus. Measurements of torsional stiffness performed slightly better than those of compressive and bending stiffness

When performing total hip replacements in patients with hip dysplasia, acetabular augmentation may be required to prevent early component failure. Preoperative radiographic templating may help estimate acetabularcomponent coverage but has not previously been shown to predict the need for augmentation. We developed a simple method to estimate the percentage of acetabular component coverage from pre-operative radiographs (True: False cup ratio). We aimed to evaluate whether this couldpredict the need foracetabular augmentation at primary total hip replacement for patients with dysplastic hips. We reviewed all patients with hip dysplasia who underwent a primary total hip replacement from 2005–2012. Classification of hip dysplasia (Crowe), centre edge angle (CEA), Sharp and Tonnis angles were determined on pre-operative radiographs for each patient. Templating was performed on anteroposteriorand lateral view hip radiographs to determine the likely percentage of acetabular component coverage using the True: False cup ratio. Patients requiring acetabular augmentation at time of primary total hip arthroplasty were noted. 128 cases were reviewed, 31 (24%) required acetabularaugmentation. Comparison between augmented and non-augmented cases revealed no difference in the mean CEA (p = 0.19), Sharp angles (p = 0.76) or Tonnis angles (p = 0.32). A lower True Cup: False Cup ratio was observed in the augmented groupcompared to the non-augmented group(median = 0.68 vs 0.88, p < 0.01). Preoperative templating can help predict which dysplastic hips are likely to require acetabular augmentation at primary total hip replacement

Introduction

The ankle cartilage has an important function in walking movements, mainly in sports; for active young people, between 20 and 30 years old, the incidence of osteochondral lesions is more frequent. They are also more frequent in men, affecting around 21,000 patients per year in USA with 6.5% of ankle injuries generating osteochondral lesions. The lesion is a result of ankle sprain and is most frequently found in the medial location, in 53% of cases.

The main objective of this work was to develop an experimental and finite element models to study the effect of the ankle osteochondral lesion on the cartilage behavior.

Abstract

INTRODUCTION. Loss of joint function is only exploited in osteoarthritis (OA) once severe impairment is apparent. Animal models allow for lesion induction and serial OA progression measures. We recently described an adjustable non-surgical loading model for generating focal cartilage lesions in only the lateral femur joint compartment, in which regimes can be adjusted so that these either do or do not progress spontaneously. Herein, we use ventral plane videographic treadmill gait analysis to determine whether gait changes can be used to discriminate between stable and spontaneously progressing lesions, induced by these two loading regimes. METHODS. Animals encountered normal conditions, except during loading (9N, 40 cycles, 0.1 Hz, 10 sec/ cycle) which was applied to right knees in two groups (n=8) of 8-week-old male CBA mice: i) loaded once; ii) loaded 3 times/week for 2 weeks. Gait (including: brake, propel, stance, stride, stride length, stride frequency, steps and paw area) was assessed 3 times/week for 2 weeks in each mouse using a DigigaitTM treadmill. Thereafter, mice received 5mg/kg carprofen for analgesia and gait analysis repeated on 3 further alternate days. RESULTS. The two loading regimes produced virtually identical gait modifications with delayed onset (apparent on day 3) which remained unchanged for 2 weeks; mice loaded once only showed modified contralateral limb use, but those loaded multiply exhibited additional ipsilateral front limb modifications; no changes in gait were observed in loaded limbs. Intriguingly, the two regimes produced distinct responses to analgesia. Load-induced gait changes were completely rescued by carprofen in mice loaded only once, whilst those in mice loaded repetitively persisted. CONCLUSION. Our findings reveal specific and reproducible, compensatory changes in contralateral, non-loaded limb gait induced by any joint loading which produces focal articular lesions, and modified ipsilateral front limb use only when progressing lesions are induced by repetitive loading. We find that pain relief completely alleviates all gait modifications associated with stable lesions induced by single loading, but not those induced by repetitive loading. Differing responses in mice with stable and progressive articular cartilage load-induced lesions suggests that gait behaviour in a mechanical loading model of OA may predict joint degeneration

Substance P is readily detected in the synovial fluid of the knee in which it acts as a powerful inflammatory agent in response to injury and disease. It may be an objective predictor of pain after knee replacement surgery. The level of substance P was measured in the synovial fluid in both knees of 114 patients having unilateral and in 86 patients having bilateral total knee replacement for osteoarthritis. All had severe pain in the knee to be replaced and joint destruction. Substance P was elevated in 73% of replaced knees but not in normal or asymptomatic knees. Good or excellent pain relief was achieved in 97% of patients with an elevated preoperative level of substance P and in 61% of those with a normal preoperative level (p < 0.05 compared with preoperative values)

The operative treatment of fractures of the proximal humerus can be complicated by poor bone quality. Our aim was to evaluate a new method which allows prediction of the bone quality of the proximal humerus from radiographs. Anteroposterior radiographs were taken of 19 human cadaver humeri. The cortical thickness was measured at two levels of the proximal humeral diaphysis. The bone mineral density (BMD) was determined for the humeral head (HH), the surgical neck (SN), the greater tuberosity (GT) and lesser tuberosity (LT) using dual-energy x-ray absorptiometry. The mean cortical thickness was 4.4 ± 1.0 mm. Specimens aged 70 years or less had a significantly higher cortical thickness than those aged over 70 years. A significant positive correlation was found between cortical thickness and the BMD for each region of interest. The cortical thickness of the proximal diaphysis is a reliable predictor of the bone quality of the proximal humerus

Background

Understanding vertebral fracture is important in order to reduce fracture risk. Previous studies have used FE to investigate mechanical behaviour, typically using a linear material response. This study aimed to establish a novel model that could represent the plastic behaviour leading to fracture.