The treatment of paediatric supracondylar humeral fractures is likely one of the first procedures involving X-ray guided wire insertion that trainee orthopaedic surgeons will encounter. Pinning is a skill that requires high levels of anatomical knowledge, spatial awareness, and hand-eye coordination. We developed a simulation model using silicone soft-tissue and 3D-printed bones to allow development and practice of this skill at no additional risk to patients. For this model, we have focused on reusability and lowering raw-material costs without compromising fidelity. To achieve this, the initial bone model was extracted from open-source computed tomography scans and modified from adult to paediatric size. Muscle of appropriate robustness was then sculpted around the bones using 3D modelling software. A cutaneous layer was developed to mimic oedema using clay sculpturing on a plaster-casted paediatric forearm. These models were then used for 3D-printing and silicone casting respectively. The bone models were printed with settings to imitate cortical and cancellous densities and give high-fidelity tactile feedback upon drilling. Each humerus costs NZD $0.30 in material to print and can be used 1–3 times. Silicone casting of the soft-tissue layers imitates differing relative densities between muscle and oedematous cutaneous tissue, thereby increasing skill necessary to accurately palpate landmarks. Each soft-tissue sleeve cost NZD $70 in material costs to produce and can be used 20+ times. The resulting model is modular, reusable, and replaceable, with each component standardised and easily reproduced. It can be used to practice land-mark palpation and Kirschner wire pinning and is especially valuable in smaller centres which may not be able to afford traditional Saw Bones models. This low-cost model thereby improves equity while maintaining quality of simulation training

Introduction. Total knee arthroplasty (TKA) is a well proven surgical procedure. Squat and gait motions are common activities in daily life. However, squat motion is known as most dissatisfying motion in activities in daily life after total knee arthroplasty (TKA). Dissatisfaction after TKA might refer to muscle co-contraction between quadriceps and hamstrings. The purposed of this study was to develop squat and gait simulation model and analyses the contact mechanics and quadriceps and hamstring muscle stability. We hypothesized that squat model shows larger contact forces and lower hamstring to quadriceps force ratio than gait model. Materials and Methods. Squat motion and gait model were simulated in musculoskeletal simulation software (AnyBody Modeling System, AnyBody Technology, Denmark). Subject-specific bone models used in the simulation were reconstructed from CT images by Mimics (Materialize, Belgium). The lower extremity model was constructed with pelvis, femur, tibia, foot segments and total knee replacement components: femoral component, tibial insert, tibial tray, and patella component [Fig.1]. The muscle model was consisted of 160 muscle elements. The TKR components used in this study are PS-type LOSPA Primary Knee System (Corentec Co., Ltd, Republic of Korea). Force-dependent kinematics method was used in the simulation. The model was simulated to squat from 15° to 100° knee flexion, in 100 frames. Gait simulation model was based on motion capture and force-plate system. Motion capture and force-plate data were from grand challenge competition dataset. Results / Discussion. Patellofemoral contact forces ranged from 0.18 to 3.78 percent body weight (%BW) and from 0.00 to 1.36 %BW during squat motion and gait cycle, respectively. Patellofemoral contact forces calculated at 30°, 60°, and 90° flexion during squat motion were 0.53, 1.93, and 3.22 %BW, respectively. Wallace et al. also reported patellofemoral contact forces at 30°, 60°, and 90° flexion, which were 0.31, 1.33, 2.45 %BW during squat motion. Our results showed similar results from other studies, however the squat model overestimated the patellofemoral contact forces. Contact stiffness in the simulation model might affected the overestimated contact forces. Hamstring to quadriceps force ratio ranged from 0.32 to 1.88 for squat model, and from 0.00 to 2.54 for gait model. As our hypothesis, squat motion showed larger patellofemoral contact forces. Also, mean hamstring to quadriceps force ratio of squat model were about half than the mean hamstring to quadriceps force ratio of gait model. From the results, possibility exists that unbalanced force of quadriceps and hamstring can affect dissatisfaction after TKA while squat motion is the most dissatisfying motion after TKA. However, muscle stability is not the only factor that can affect dissatisfaction after TKA. In future study, more biomechanical parameters should be evaluated to find meaningful dissatisfying factor after TKA. Conclusion. In conclusion, TKA musculoskeletal models of squat and gait motion were constructed and patellofemoral contact force / hamstring to quadriceps force ratio were evaluated. Patellofemoral mechanics were validated by comparison of previous study. Additional studies are needed to find dissatisfying factor after TKA

Introduction. For the evaluation of new orthopaedic implants, cadaveric testing remains an attractive solution. However, prior to cadaveric testing, the performance of an implant can be evaluated using numerical simulations. These simulations can provide insight in the kinematics and contact forces associated with a specific implant design and/or positioning. Methods. Both a two and three dimensional simulation model have been created using the AnyBody Modelling System (AMS). In the two dimensional model, the knee joint is represented by a hinge. Similarly, the ankle and hip joint are represented by a hinge joint and a variable amplitude quadriceps force is applied to a rigid bar connected to the tibia (Figure 1a). In line with this simulation model, a hinge model was created that could be mounted in the UGent knee simulator to evaluate the performance of the simulated model. The hinge model thereby performs a cyclic motion under varying quadriceps load while recording the ankle reaction forces. In addition to the two dimensional model, a three dimensional model has been developed (Figure 1b). More specifically, a model is built of a sawbone leg holding a posterior stabilized single radius total knee implant. The physical sawbone model contains simplified medial and lateral collateral ligaments. In line with the boundary conditions of the UGent knee simulator, the simulated hip contains a single rotational degree of freedom and the ankle holds four degrees of freedom (three rotations, single translation). In the simulations, the knee is modelled using the force-dependent kinematics (FDK) method built in the AMS. This leaves the knee with six degrees of freedom that are controlled by the ligament tension in combination with the applied quadriceps load and shape of the implant. The physical sawbone model goes through five cycles in the UGent simulator using while recording the kinematics of the femur and tibia using a set of markers rigidly attached to the femur and tibia bone. The position of the implant with respect to the markers was evaluated by CT-scanning the sawbone model. Results and Discussion. In a first step, the reaction forces at the ankle in the 2D model were evaluated. The difference between the simulated and measured reaction force is limited and can be explained from a slight variation of the attachment point of the quadriceps load. For the 3D model, the kinematic patterns have been evaluated for both the simulation and physical model using Grood & Suntay definitions. The kinematic parameters display realistic trends, however, no exact match has been obtained for all parameters so far. The latter might be attributed to a number of simplifications in the simulation model as well as elastic deformation of the physical sawbone model. Conclusion. A three dimensional model of a knee implant in the UGent Knee Simulator has been developed. The simulated kinematic patterns appear realistic though no exact match with the measured patterns has been obtained. Future research will therefore focus on the development of a more realistic experimental and numerical model

For a proper rehabilitation of the knee following knee arthroplasty, a comprehensive understanding of bony and soft tissue structures and their effects on biomechanics of the individual patient is essential. Musculoskeletal models have the potential, however, to predict dynamic interactions of the knee joint and provide knowledge to the understanding of knee biomechanics. Our goal was to develop a generic musculoskeletal knee model which is adaptable to subject-specific situations and to use in-vivo kinematic measurements obtained under full-weight bearing condition in a previous Upright-MRI study of our group for a proper validation of the simulation results. The simulation model has been developed and adapted to subject-specific cases in the multi-body simulation software AnyBody. For the implementation of the knee model a reference model from the AnyBody Repository was adapted for the present issue. The standard hinge joint was replaced with a new complex knee joint with 6DoF. The 3D bone geometries were obtained from an optimized MRI scan and then post-processed in the mesh processing software MeshLab. A homogenous dilation of 3 mm was generated for each bone and used as articulating surfaces. The anatomical locations of viscoelastic ligaments and muscle attachments were determined based on literature data. Ligament parameters, such as elongation and slack length, were adjusted in a calibration study in two leg stance as reference position. For the subject-specific adaptation a general scaling law, taking segment length, mass and fat into account, was used for a global scaling. The scaling law was further modified to allow a detailed adaption of the knee region, e.g. align the subject-specific knee morphology (including ligament and muscle attachments) in the reference model. The boundary conditions were solely described by analytical methods since body motion (apart from the knee region) or force data were not recorded in the Upright-MRI study. Ground reaction forces have been predicted and a single leg deep knee bend was simulated by kinematic constraints, such as that the centre of mass is positioned above the ankle joint. The contact forces in the knee joint were computed using the force dependent kinematic algorithm. Finally, the simulation model was adapted to three subjects, a single leg deep knee bend was simulated, subject-specific kinematics were recorded and then compared to their corresponding in-vivo kinematic measurements data. We were able to simulate the whole group of subjects over the complete range of motion. The tibiofemoral kinematics of three subjects could be simulated showing the overall trend correctly, whereas absolute values partially differ. In conclusion, the presented simulation model is highly adaptable to an individual situation and seems to be suitable to approximate subject-specific knee kinematics without consideration of cartilage and menisci. The model enables sensitivity analyses regarding changes in patient specific knee kinematics following e.g. surgical interventions on bone or soft tissue as well as related to the design and placement of partial or total knee joint replacement. However, model optimisation, a higher case number, sensitivity analyses of selected parameters and a semi-automation of the workflow are parts of our ongoing work

Many recent knee prostheses are designed aiming to the physiological knee kinematics on tibiofemoral joint, which means the femoral rollback and medial pivot motion. However, there have been few studies how to design a patellar component. Since patella and tibia are connected by a patellar tendon, tibiofemoral and patellofemoral motion or contact forces might affect each other. In this study, we aimed to discuss the optimal design of patellar component and simulated the knee flexion using four types of patellar shape during deep knee flexion. Our simulation model calculates the position/orientation, contact points and contact forces by inputting knee flexion angle, muscle forces and external forces. It can be separated into patellofemoral and tibiofemoral joints. On each joint, calculations are performed using the condition of point contact and force/moment equilibrium. First, patellofemoral was calculated and output patellar tendon force, and tibiofemoral was calculated with patellar tendon force as external force. Then patellofemoral was calculated again, and the calculation was repeated until the position/orientation of tibia converged. We tried four types of patellar shape, circular dome, cylinder, plate and anatomical. Femoral and tibial surfaces are created from Scorpio NRG PS (Stryker Co.). Condition of knee flexion was passive, with constant muscle forces and varying external force acting on tibia. Knee flexion angle was from 80 to 150 degrees. As a result, the internal rotation of tibia varied much by using anatomical or plate patella than dome or cylinder shape. Although patellar contact force did not change much, tibial contact balances were better on dome and cylinder patella and the medial contact forces were larger than lateral on anatomical and plate patella. Thus, the results could be divided into two types, dome/cylinder and plate/anatomical. It might be caused by the variations of patellar rotation angle were large on anatomical and plate patella, though patellar tilt angles were similar in all the cases. We have already reported that the anatomical shape of patella would contact in good medial-lateral balance when tibia moved physiologically, therefore we have predicted the anatomical patella might facilitate the physiological tibiofemoral motion. However, the results were not as we predicted. Actually our previous and this study are not in the same condition; we used a posterior-stabilized type of prosthesis, and the post and cam mechanism could not make the femur roll back during deep knee flexion. It might be better to choose dome or cylinder patella to obtain the stability of tibiofemoral joint, and to choose anatomical or plate to the mobility

Introduction. Total knee replacement (TKR) is an established and effective surgical procedure in case of advanced osteoarthritis. However, the rate of satisfied patients amounts only to about 75 %. One common cause for unsatisfied patients is the anterior knee pain, which is partially caused by an increase in patellofemoral contact force and abnormal patellar kinematics. Since the malpositioning of the tibial and the femoral component affects the interplay in the patellofemoral joint and therefore contributes to anterior knee pain, we conducted a computational study on a cruciate-retaining (CR) TKR and analysed the effect of isolated femoral and tibial component malalignments on patellofemoral dynamics during a squat motion. Methods. To analyse different implant configurations, a musculoskeletal multibody model was implemented in the software Simpack V9.7 (Simpack AG, Gilching, Germany) from the SimTK data set (Fregly et al.). The musculoskeletal model comprised relevant ligaments with nonlinear force-strain relation according to Wismans and Hill-type muscles spanning the lower extremity. The experimental data were obtained from one male subject, who received an instrumented CR TKR. Muscle forces were calculated using a variant of the computed muscle control algorithm. To enable roll-glide kinematics, both tibio- and patellofemoral joint compartments were modelled with six degrees of freedom by implementing a polygon-contact-model representing the detailed implant surfaces. Tibiofemoral contact forces were predicted and validated using data from experimental squat trials (SimTK). The validated simulation model has been used as reference configuration corresponding to the optimal surgical technique. In the following, implant configurations, i.e. numerous combinations of relative femoral and tibial component alignment were analysed: malposition of the femoral/tibial component in mediolateral (±3 mm) and anterior-posterior (±3 mm) direction. Results. Mediolateral translation/malposition of the tibial component did not show high influence on the maximal patellofemoral contact force. Regarding the mediolateral translation of the femoral component, similar tendencies were observed. However, lateralisation of the femoral component (3 mm) clearly increased the lateral patella shift and medialisation of the tibial component (3 mm) led to a slightly increased lateral patella shift. Compared to the reference model, pronounced posterior translation of the tibial and femoral component resulted in a lower patellofemoral contact force, further increasing with higher anterior translation of the components. The translation of the tibial component showed smaller influence on the patellofemoral contact force than the translation of the femoral component. Discussion. In our present study, the mediolateral malposition of the femoral and tibial component showed no major impact on patellofemoral contact force and contribution to anterior knee pain in patients with CR TKR. However, the influence of implant component positioning in anterior-posterior direction on patellofemoral contact force is evident, especially for the femoral component. Our generated musculoskeletal model can contribute to computer-assisted preclinical testing of TKR and may support clinical decision-making in preoperative planning

Incidence of intraoperative fracture during cementless Total Hip Arthroplasty (THA) is increasing. This is attributed to factors such as an increase in revision procedures and the favour of cementless fixation. Intraoperative fractures often occur during the seating of cementless components. A surgical mallet and introducer are used to generate the large impaction forces necessary to seat the component, sometimes leading to excessive hoop strain in the bone. The mechanisms of bone strain during impaction are complex and occur over very short timeframes. For this reason experimental and simulation models often focus on strain shortly after the implant is introduced, or seat it quasi-statically. This may not produce a realistic representation of the magnitude of strain in the bone and dangerously under-represent fracture risk. This in-vitro study seeks to determine whether strain induced during impaction is similar both during the strike (dynamic strain) and shortly after the strike has occurred (post-strike strain). It is also asked whether post-strike strain is a reliable predictor of dynamic strain. A custom drop tower was used to seat acetabular components in 45 Sawbones models (SKU: 1522–02, Malmo, Sweden), CNC milled to represent the acetabular cavity. Ten strikes were used to seat each cup. 3 strike velocities (1.5 m/s, 2.75 m/s, 4 m/s) and 3 impact masses (600 g, 1.2 kg, 1.8 kg) were chosen to represent 9 different surgical scenarios. Two strain gages per Sawbone were mounted on the surface of the block, 2 mm from the rim of the cavity. Strain data was acquired at 50 khz. Each strain trace was then analysed to determine the peak dynamic strain during mallet strike and the static strain post-strike. A typical strain pattern was observed during seating. An initial pre-strike strain is followed by a larger dynamic peak as the implant is progressed into the bone cavity. Strain subsequently settles at a lower (tensile) value than peak dynamic post-strike, but higher than pre-strike strain. Over the 450 strikes conducted dynamic strain was on average 3.39 times larger than post-strike strain. A statistically significant linear relationship was observed between the magnitude of post-strike and dynamic strain (adjusted R. 2. =0.391, p<0.005). This indicates that, for a known scenario, post-strike strain can be used as an indicator for dynamic peak strain. However when only the maximum dynamic and post-strike strains were taken from across the 10 strikes used to seat the implant, the relationship between the two strains was not significant (R. 2. =0.300, p=0.73). This may be due to the fact that the two maximums did not often occur on the same strike. On average, max dynamic strain occurred 1.7 strikes after max post-strike strain. We conclude that peak dynamic strain is much larger than the strain immediately post-strike in a synthetic bone model. It is shown that post-strike strain is not a good predictor of dynamic strain when the max strain during any strike to seat the component is considered, or variables (such as mallet mass or velocity) are changed. It is important to consider dynamic strain in bone as well as post-strike strain in experimental or simulated bone models to ensure the most reliable prediction of fracture

Introduction. The purpose of this study was to experimentally evaluate impingement and dislocation of total hip replacements while performing dynamic movements under physiological-like conditions. Therefore, a hardware-in-the-loop setup has been developed, in which a physical hip prosthesis actuated by an industrial robot interacts with an in situ-like environment mimicked by a musculoskeletal multibody simulation-model of the lower extremity. Methods. The multibody model of the musculoskeletal system comprised rigid bone segments of the lower right extremity, which were mutually linked by ideal joints, and a trunk. All bone geometries were reconstructed from a computed tomography set preserving anatomical landmarks. Inertia properties were identified based on anthropometric data and by correlating bone density to Hounsfield units. Relevant muscles were modeled as Hill-type elements, passive forces due to capsular tissue have been neglected. Motion data were captured from a healthy subject performing dislocation-associated movements and were fed to the musculoskeletal multibody model. Subsequently, the robot moved and loaded a commercially available total hip prosthesis and closed the loop by feeding the physical contact information back to the simulation model. In this manner, a comprehensive parameter study analyzing the impact of implant position and design, joint loading, soft tissue damage and bone resection was implemented. Results. The parameter study revealed a generally high dislocation risk for the seating-to-rising with adduction scenarios. Improper implant positioning or design could be compensated by adjusting prosthesis components correspondingly. Gluteal insufficiency or lower joint loading did not result in higher impingement or dislocation risk. However, severe malfunction of the artificial joint was found for proximal bone resection. Discussion. Previous testing setups ignored the impact of active muscles or relied on simplified contact mechanics. Herein, total hip replacement stability has been investigated experimentally by using a hardware-in-the-loop simulation. Thereby, several influencing factors such as implant position and design as well as soft tissue insufficiency and imbalance could be systematically evaluated with the goal to enhance joint stability

For a proper functional restoration of the knee following knee arthroplasty, a comprehensive understanding of bony and soft tissue structures and their effects on biomechanics of the individual patient is essential. A systematic description of morphological knee joint parameters and a study of their effects could beneficial for an optimal patient-specific implant design. The goal of this study was the development of a full parametric model for a comprehensive analysis of the distal femoral morphology also enabling a systematic parameter variation in the context of a patient specific multi-parameter optimisation of the knee implant shape. The computational framework was implemented in MATLAB and tested on 20 CT-models which originated from pathological right knees. The femora were segmented semi-automatically and exported in STL-format. First, a 3D surface model was imported, visualised and reference landmarks were defined. Cutting planes were rotated around the transepicondylar axis and ellipses were fitted in the cutting contour using pattern recognition. The portions between the ellipses were approximated by using a piecewise cubic hermite interpolation polynom such that a closed contour was obtained following the characteristics of the real bone model. At this point the user could change the parameters of the ellipses in order to manipulate the approximated contour for e.g. higher-level biomechanical analyses. A 3D surface was generated by using the lofting technique. Finally, the parameter model was exported in STL-format and compared against the original 3D surface model to evaluate the accuracy of the framework. The presented framework could be successfully applied for automatic parameterisation of all 20 distal femur surface data-sets. The mean global accuracy was 0.09±0.62 mm with optimal program settings which is more accurate than the optimal resolution of the CT based data acquisition. A systematic variation of the femoral morphology could be proofed based on several examples such as the manipulation of the medial/lateral curvature in the frontal plane, contact width of the condyles, J-Curve and trochlear groove orientation. In our opinion, this novel approach might offer the opportunity to study the effect of femoral morphology on knee biomechanics in combination with validated biomechanical simulation models or experimental setups. New insights could directly be used for patient-specific implant design and optimisation

Introduction. Postoperative dislocation remains a vexing problem for patients and surgeons following total hip arthroplasty (THA). It is the commonest reason for revision THA in the US. Dual mobility (DM) THA implants markedly decrease the risk of THA instability. However, DM implants are more expensive than those used for conventional THA. The purpose of this study was to perform a cost-effectiveness analysis of DM implants compared to conventional bearing couples for unilateral primary THA using a computer model-based evaluation. Methods. A state-transition Markov computer simulation model was developed to compare the cost-utility of dual mobility versus conventional THA for hip osteoarthritis from a societal perspective (Figure 1). The model was populated with health outcomes and probabilities from registry and published data. Health outcomes were expressed as quality-adjusted life years (QALYs). Direct costs were derived from the literature and from administrative claims data, and indirect costs reflected estimated lost wages. All costs were expressed in 2013 US dollars. Health and cost outcomes were discounted by 3% annually. The base case modeled a 65-year-old patient undergoing THA for unilateral hip osteoarthritis. A lifetime time horizon was analyzed. The primary outcome was the incremental cost-effectiveness ratio (ICER). The willingness-to-pay threshold was set at $100,000/QALY. Threshold, one-way, two-way, and probabilistic sensitivity analyses were performed to assess model uncertainty. Results. DM THA exhibited absolute dominance over conventional THA with lower accrued costs (US$45,960 versus $47,103) and higher accrued utility (12.08 QALY versus 11.84 QALY). The ICER was -$4,771/QALY, suggesting that DM THA is cost-saving compared to conventional THA. The cost threshold at which dual mobility implants were cost-ineffective was $25,000 (Figure 2), and the threshold at which DM implants ceased being cost-saving was $12,845. Sensitivity analyses demonstrated that the probability of intraprosthetic dislocation, primary THA utility, and age at index THA most influenced model results. In the probabilistic sensitivity analysis, 90% of model iterations resulted in cost savings for DM THA (Figure 3). Discussion. Dual mobility components showed clear cost-utility advantages over conventional THA components, and DM implants are cost-saving for primary unilateral THA from a societal perspecitve. Model results suggest that DM THA need not be limited to only high-risk patients, although patient age and risk of dislocation are important determinants of its cost-utility

INTRODUCTION. Mechanical tissue properties of some ligaments and tendons have been described in the literature. However, to our knowledge no data exists describing the tensile properties of the Iliopsoas tendon. The iliopsoas complex is in very close proximity to the hip joint running through the psoas notch from the inner side of the pelvis to the lesser trochanter on the posterior aspect of the proximal femur. The tendon muscle complex wraps around the anterior aspect of the femoral head. Hip joint intervention such as total hip arthroplasty (THA) can interfere with iliopsoas function and contact mechanics, and thereby play a major role in the clinically known condition of anterior hip pain. For computer simulations such as finite element analysis (FEA) precise knowledge of soft-tissue mechanical properties is crucial for accurate models and therefore, the goal of this study was to describe the iliopsoas tensile properties using uniaxial testing equipment. METHODS. Ten iliopsoas tendons were harvested from five specimens (2 male, 3 female; 82.4 yrs ±7.4 yrs) and then carefully cleaned from any fat and muscle tissue. Two freeze clamps were fixed to each end of the tendon sample. The clamps were submerged in liquid nitrogen for 30 seconds to prevent tendon slip and attached to the test frame and load cell via carabiners allowing the tendon to rotate around its long axis. Width, thickness and initial gauge length of each tendon were measured before testing. The test protocol included 10 cycles of preconditioning between 6 N and 60 N at 0.4 mm/s, followed by continuous distraction at 0.4 mm/s until failure. For each tendon the linear stiffness was determined by fitting a straight line to the liner region on the force-displacement curve (Fig. 1). RESULTS. The average linear stiffness of the ten iliopsoas tendons was measured to be 339 N/mm ±81 N/mm and the average failure load resulted in 2154 N ±418 N (Fig. 2). Average width and thickness were determined to be 13.9 mm ±3.2 mm and 3.8 mm ±0.5 mm respectively. The initial gauge length of the ten tendons revealed an average of 56.5 mm ±10.5 mm. CONCLUSION. An average stiffness of 339 N/mm and average failure load of 2154 N was found in our experiments. A trend of increased stiffness and reduced failure load with higher age could be observed. Soft-tissue mechanical properties are dependent on tissue geometry such as cross-sectional area and length and therefore can be variable in comparison with other anatomical structures (e.g. patella tendon). To our knowledge no data has been published on the mechanical properties of iliopsoas tendons and therefore results from this research could be used for future simulation models involving the iliopsoas tendon such as FEA analysis to evaluate the effect of anterior hip pain due to soft-tissue impingement

Introduction. Currently, there is a focus on the development of novel materials to articulate against cartilage. Such materials should either eliminate or delay the necessity of total joint replacement. While cobalt-chromium (CoCr) alloy is still a material of choice and used for hemi-arthroplasties, spacers, and repair plugs, alternative materials are being studied. Pyrolytic carbon (PyC) is a biocompatible material that has been available since the 1980s. It has been widely and successfully used in small joints of the foot and the hand, but its tribological effects in direct comparison to cobalt-chromium (CoCr) remain to be investigated. Methods. A four station simulator (Figure 1), mimicking joint load and motion, was used for testing. The simulator is housed in an incubator, which and provides the necessary environmental conditions for cartilage survival. Articular cartilage disks (14mm in diameter) were obtained from the trochleas of six to eight months old steer for testing and free-swelling controls. Disks (n=8 per material) were placed in porous polyethylene scaffolds within polypropylene cups and mounted onto the simulator to articulate against 28mm balls of either PyC or CoCr. Each ball was pressed onto the cartilage disk with 40N. In order to allow fluidal load support, the contact migrated over the biphasic cartilage with a 5.2 mm excursion. Concomitantly, the ball oscillated with ±30° at 1 Hz. Testing was conducted for three hours per day over 10 days in Mini ITS medium. Media samples were collected at the end of each three hour test. Upon test commencement, media was pooled (days 1, 4, 7, 10) and analyzed for proteoglycans/sGAGs and hydroxyproline. In addition, total material release into media was estimated by determining the dry weight increase of media samples. For this purpose, 1 ml aliquots of fresh and test media were dialyzed, lyophilized and weighed on a high precision balance. Disk morphology and cell viability were histologically examined. Results. During each day of testing, cartilage control, CoCr and PyC samples released an average of 0.236, 0.253, re 0.268 mg/mL of glycol-proteins into the medium. After running-in (day 1), the increase was highly linear (R. 2. >0.99) and similar for all three testing conditions. Proteoglycan/GAG (Figure 2) and hydroxyproline release (Figure 3) were also similar for both materials (p=0.46 re. p=0.12), but significantly different from control (p<0.01). Histological and cell viability images support the hypothesis of superficial zone damage of the cartilage disks for both materials. Cell viability was not different from control (p>0.33). Discussion. The performance of PyC and CoCr was comparable using this in vitro simulation model, however appears not optimal. The observed surface fibrillation may lead to tissue breakdown in the long-term. The wear mechanism has yet to be elucidated but appears to be of adhesive nature. The lack of proteins in the medium might have suppressed boundary lubrication and thus may have played a role in the non-optimal performance of these materials. In summary, a live tissue model of articular cartilage found no difference comparing pyrolytic carbon with the current clinical gold standard CoCr

In the present study we describe the clinical results of the Scientific Hip Prosthesis® (SHP). With the goal of smoothening cement-bone interface stress peaks, the SHP was developed using shape optimization algorithms together with finite element modelling techniques. The resulting shape and cement stresses are seen in Figure 1. The introduction of the SHP prosthesis was performed in a stepwise fashion including a RSA study performed by Nivbrant et al. 1. RSA studies for prosthetic types that are in long-term use are of great value in predicting the survivorship related to the migration rate and pattern for that specific type of prosthesis. If a stem in a patient shows a much higher migration rate than the typical one, the stem may be identified as at high-risk for early loosening. The study of Nivbrant et al. 1. revealed unexpectedly high migration values and it was stated that the SHP stem was not the preferred stem to use despite the good Harris Hip Score and Pain score at two years follow-up. In the present study the clinical results of a single surgeon study consisting of 171 hips with a follow-up of 5–12 years were evaluated. The mean follow-up was 8.2 years (5.0–12.0). The survival rate was 98.8% at ten years follow-up for aseptic loosening of the stem. The mean Harris Hip Score at 10 year follow-up was 89.2 ± 7.5. This study therefore indicates that a new prosthetic design may function clinically rather well, despite the relatively high migration rates which have been reported. In case of a RSA study with a new prosthesis it may not be so evident what the expected “typical” migration rate or pattern is. So in order to predict early loosening the typical migration rate has to be known. Perhaps typical migration rates can be established using standardized cadaver migration experiments or computer simulation models techniques. Since these standardized tools are currently not available, the prediction of clinical survival of new prosthetic components remains a challenging task and the interpretation of migration rates with new designs should be considered with much caution

Introduction. Advanced medical imaging techniques have allowed the understanding of the patterns of relative bone motions at human joints. 1. However, poor imaging contrasts of soft tissues have not allowed the full understanding of various glenohumeral ligaments (GHL) functions during glenohumeral joint (GHJ) manoeuvres. This is presently a significant limitation to research as these structures are said to be responsible for the passive stability of the GHJ. 2. Furthermore, the repairs of GHJ instability often take recourse to these structures. 3. Earlier studies have presented a model that numerically reconstructs or simulates GHJ motions. 4. and how the locus of bony attachment points of the GHLs on a dynamic GHJ could be numerically tagged and trailed. 5. The aim of this study was to advance these previous findings by developing an algorithm that allows the quantification of GHL lengths at any instantaneous position of the GHJ. Materials and Method. CT scan of a set of humerus and scapula was reconstructed into two individual surface meshes of interconnected nodes, each node having a unique vectorial identification in space. The two attachment nodes (a and b) of a GHL were identified on the bones. 5. Least squares geometric sphere was fitted upon the humeral head (HH) and its centre (c) and radius (r) quantified. 6. Vectors a, b and c were applied to represent the ‘dominant ligament plane’ concomitant with the 2D ‘dominant plane’ of Runciman (1993). 7. This plane defined the path through which the ligament wrapped on the HH. The point of initial or end of contact of GHL on the HH was defined as the point on HH where a line from c intercepts the ligament at 90°. Total GHL length was calculated as the sum of its three segments, namely: (1) Proximal segment – a straight line from its glenoid attachment node to the point of initial contact (2) Wrap segment – an arc of (r) radius of curvature from initial to end contact points (3) Distal segment – a straight line from end contact point to the humeral node of attachment. The wrap segment was further refined by adjusting ligament contacts along this path to the actual surface contour of the HH by integrating all the surface nodes along the path. The algorithm was tested for short incremental steps of GHJ abduction, flexion, rotation and translations on the Amadi et al's kinematics simulation model. 4. . Results. From plotted graphs of 5 simulated GHL, lengths increased or decreased smoothly as the rotations and translations were increased or decreased at a constant rate, respectively. Some GHJ motion directions resulted in contrasting stretching or folding effects on different ligaments in a mathematically reasonable manner. Conclusion. This numerical application would allow the quantification of functional loading of each GHL during simulated or reconstructed GHJ motion and hence provide understanding of how the various GHL may be treated during surgical repairs

Introduction. Dislocation of total hip replacements (THRs) remains a severe complication after total hip arthroplasty. However, the contribution of influencing factors, such as implant positioning and soft tissue tension, is still not well understood due to the multi-factorial nature of the dislocation process. In order to systematically evaluate influencing factors on THR stability, our novel approach is to extract the anatomical environment of the implant into a musculoskeletal model. Within a hardware-in-the-loop (HiL) simulation the model provides hip joint angles and forces for a physical setup consisting of a compliant support and a robot which accordingly moves and loads the real implant components [2]. The purpose of this work was to validate the HiL test system against experimental data derived from one patient. Methods. The musculoskeletal model includes all segments of the right leg with a simplified trunk. Bone segments were reconstructed from a human computed tomography dataset. The segments were mutually linked in the multibody software SIMPACK (v8.9, Simpack AG, Gilching, Germany) by ideal joints starting from the ground-fixed foot. Furthermore, inertia properties were incorporated based on anthropometric data. Inverse dynamics was used to obtain muscle forces. Thus, optimization techniques were implemented to resolve the distribution problem of muscle forces whereas muscles were assumed to act along straight lines. For validation purposes the model was scaled to one patient with an instrumented THR [1]. Averaged kinematic measurements were used to obtain joint angles for a knee-bending motion. Then, the model was exported into real-time capable machine code and embedded into the HiL environment. Real implant components of a standard THR were attached to the endeffector of the robot and the compliant support. Finally, the HiL simulation was carried out simulating knee-bending. Experimentally measured hip joint forces from the patient [1] were used to validate the HiL simulation. Results. According to the joint angles obtained a knee-bending motion was carried out during the HiL simulation (Fig. 1). Predicted components of the hip joint force were in-between the envelopes of measured in-vivo data with partial deviation of the y-component (Fig. 2). The force application by the robot agreed well with the force values provided by the model. Discussion. Previous quasi-static mechanical setups for testing subluxation and dislocation of THRs neglected the impact of soft tissue structures on actual joint loading. Therefore, we combine the advantages of robot-based testing and numerical simulations within a HiL approach for dynamic analyses of THRs [2]. Thereby, validation is required to enhance the credibility of test results. The data presented demonstrate that the HiL test system with the embedded musculoskeletal model is capable of providing comparable THR loading as derived from in-vivo data. Certain deviations of the joint force's y-component will be the focus of up-coming model improvements. By considering dislocation-associated movements such as deep knee-bending, the influence of implant design and positioning on THR stability can be evaluated under reproducible, physiological-like conditions in subsequent studies