Introduction. The increased prevalence of osteoporosis in the patient population undergoing reverse shoulder arthroplasty (RSA) results in significantly increased complication rates. Mainly demographic and clinical predictors are currently taken into the preoperative assessment for risk stratification without quantification of preoperative computed tomography (CT) data (e.g. bone density). It was hypothesized that preoperative CT bone density measures would provide objective quantification with subsequent classification of the patients’ humeral bone quality. Methods. Thirteen bone density parameters from 345 preoperative CT scans of a clinical RSA cohort represented the data set in this study. The data set was divided into testing (30%) and training data (70%), latter included an 8-fold cross validation. Variable selection was performed by choosing the variables with the highest descriptive value for each correlation clustered variables. Machine learning models were used to improve the clustering (Hierarchical Ward) and classification (Support Vector Machine (SVM)) of bone densities at risk for complications and were compared to a conventional statistical model (Logistic Regression (LR)). Results. Clustering partitioned this cohort (training data set) into a high bone density subgroup consisting of 96 patients and a low bone density subgroup consisting of 146 patients. The optimal number of clusters (n = 2) was determined based on optimization metrics. Discrimination of the cross validated classification model showed comparable performance for the training (accuracy=91.2%; AUC=0.967) and testing data (accuracy=90.5 %; AUC=0.958) while outperforming the conventional statistical model (Logistic Regression (LR)). Local interpretable model-agnostic explanations (LIME) were created for each patient to explain how the predicted output was achieved. Conclusion. The trained and tested model provides preoperative information for surgeons treating patients with potentially poor bone quality. The use of machine learning and patient-specific calibration showed that multiple 3D bone density scores improved accuracy for objective preoperative bone quality assessment

Introduction and Objective. Forced external rotation is hypothesized as the key mechanism of syndesmotic ankle injuries. This complex trauma pattern ruptures the syndesmotic ligaments and induces a three-dimensional deviation from the normal distal tibiofibular joint configuration. However, current diagnostic imaging modalities are impeded by a two-dimensional assessment, without taking into account ligamentous stabilizers. Therefore, our aim is two-fold: (1) to construct an articulated statistical shape model of the normal ankle with inclusion of ligamentous morphometry and (2) to apply this model in the assessment of a clinical cohort of patients with syndesmotic ankle injuries. Materials and Methods. Three-dimensional models of the distal tibiofibular joint were analyzed in asymptomatic controls (N= 76; Mean age 63 +/− 19 years), patients with syndesmotic ankle injury (N = 13; Mean age 35 +/− 15 years), and their healthy contralateral equivalent (N = 13). Subsequently, the statistical shape model was generated after aligning all ankles based on the distal tibia. The position of the syndesmotic ligaments was predicted based on previously validated iterative shortest path calculation methodology. Evaluation of the model was described by means of accuracy, compactness and generalization. Canonical Correlation Analysis was performed to assess the influence of syndesmotic lesions on the distal tibiofibular joint congruency. Results. Our presented model contained an accuracy of 0.23 +/− 0.028 mm. Mean prediction accuracy of ligament insertions was 0.53 +/− 12 mm. A statistically significant difference in anterior syndesmotic distance was found between ankles with syndesmotic lesions and healthy controls (95% CI [0.32, 3.29], p = 0.017). There was a significant correlation between presence of syndesmotic injury and the morphological distal tibiofibular configuration (r = 0.873, p <0,001). Conclusions. In this study, we constructed a bony and ligamentous statistical model representing the distal tibiofibular joint Furthermore, the presented model was able to detect an elongation injury of the anterior inferior tibiofibular ligament after traumatic syndesmotic lesions in a clinical patient cohort

Intra-articular cartilage pressure distribution in the knee joint is critical in the understanding of osteoarthritis. Combining personalized statistical modeling of the morphological characteristics with discrete element modeling enables patient-specific predictions of the pressure on the tibial plateau. However, modeling of the meniscus during gait is complicated by the dynamic nature of the structure. Nevertheless, the position of the meniscus has a substantial impact on intra-articular stress distribution. Therefore, the focus of this presentation will be on how modeling of meniscal movement during knee flexion improves insight in general meniscal kinematics for the use in tibiofemoral stress distribution calculations

During shoulder arthroplasty the native functionality of the diseased shoulder joint is restored, this functionality is strongly dependent upon the native anatomy of the pre-diseased shoulder joint. Therefore, surgeons often use the healthy contralateral scapula to plan the surgery, however in bilateral diseases such as osteoarthritis this is not always feasible. Virtual reconstructions are then used to reconstruct the pre-diseased anatomy and plan surgery or subject-specific implants. In this project, we develop and validate a statistical shape modeling method to reconstruct the pre-diseased anatomy of eroded scapulae with the aim to investigate the existence of predisposing anatomy for certain shoulder conditions. The training dataset for the statistical shape model 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. The statistical shape model was then constructed from the dataset using principle component analysis. The cross-validation was performed similarly to the procedure described by Plessers et al. Virtual defects were created on each of the training set models, which closely resemble the morphology of glenoid defects according to the Wallace classification method. 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. Scapula 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, critical shoulder angle, glenoid offset and glenoid center position. The root-mean-square error between the measurements of the training data and reconstructed models was calculated for the different severities of glenoid defects. For the least severe defect, the mean error on the inclination, version and critical shoulder angle (°) was 2.22 (± 1.60 SD), 2.59 (± 1.86 SD) and 1.92 (± 1.44 SD) respectively. The reconstructed models predicted the native glenoid offset and centre position (mm) an accuracy of 0.87 (± 0.96 SD) and 0.88 (± 0.57 SD) respectively. The overall reconstruction error was 0.71 mm for the reconstructed part. For larger defects each error measurement increased significantly. A virtual reconstruction methodology was developed which can predict glenoid parameters with high accuracy. This tool will be used in the planning of shoulder surgeries and investigation of predisposing scapular morphologies

Introduction. Kienböck's disease is generally defined as the collapse of the lunate bone, and this may lead to early wrist osteoarthritis. Replacing the collapsed lunate with an implant has regained renewed interest with the advancing technology of additive manufacturing, enabling the design of patient-specific implants. The aims of this project are (1) to determine how accurate it is to use the contralateral lunate shape as a template for patient-specific lunate implants, and (2) to study the effects of shape variations wrist kinematics using 4D-computed tomography (CT) scanning. Methods. A 3D statistical shape model (SSM) of the lunate was built based on bilateral CT scans of 54 individuals. Using SMM, shape variations of the lunate were identified and the intra- and inter-subject shape variations were compared by performing an intraclass correlation analysis. A radiolucent motor-controlled wrist-holder was designed to guide flexion/extension and radial/ulnar deviation of ex vivo wrist specimens under 4D-CT scanning. In this pilot, three shape mode variations were tested per specimen in two specimens were. After post-processing each CT, the scapholunate angle (SLA) and capitolunate angle (CLA) were measured. Results. The shape of the lunate was not symmetrical, defined as exceeding the intra-subject variation in five different shape modes. The FE tests show a generalized increase in scapholunate and capitolunate angle when using lunate implants, and comparing variation of shape modes showed that shape mode 3 has a significant effect on the measured angles (p<0.05). Discussion. The design of patient-specific lunate implants may prove to be challenging using a ‘mirror’-design as it will lead to a degree of shape asymmetry. The pilot study, to determine the effects of those shape variations on wrist kinematics suggest that the degree of shape variation observed indeed may alter the wrist kinematics, although this needs to be further investigated in study using more specimens

Inter-subject variability is inherently present in patient anatomy and is apparent in differences in shape, size and relative alignment of the bony structures. Understanding the variability in patient anatomy is useful for distinguishing between pathologies and to assist in surgical planning. With the aim of supporting the development of stratified orthopaedic interventions, this work introduces an Articulated Statistical Shape Model (ASSM) of the lower limb. The model captures inter-subject variability and allows reconstructing ‘virtual’ knee joints of the lower limb shape while considering pose. A training dataset consisting of 173 lower limbs from CT scans of 110 subjects (77 male, 33 female) was used to construct the ASSM of the lower limb. Each bone of the lower limb was segmented using ScanIP (Simpleware Ltd., UK), reconstructed into 3D surface meshes, and a SSM of each bone was created. A series of sizing and positioning procedures were carried out to ensure all the lower limbs were in full extension, had the same femoral length and that the femora were aligned with a coincident centre. All articulated lower limbs were represented as: (femur scale factor) × (full extension articulated lower limb + relative transformation of tibia, fibula and patella to femur). Articulated lower limbs were in full extension were used to construct a statistical shape model, representing the variance of lower limb morphology. Relative transformations of the tibia, fibula and patella versus the femur were used to form a statistical pose model. Principal component analysis (PCA) was used to extract the modes of changes in the model. The first 30 modes of the shape model covered 90% of the variance in shape and the first 10 modes of the pose model covered 90% of the pose variance. The first mode captures changes of the femoral CCD angle and the varus/valgus alignment of the knee. The second mode represents the changes in the ratio of femur to tibia length. The third mode reflects change of femoral shaft diameter and patella size. The first mode characterising pose captures the medial/lateral translation between femur and tibia. The second mode represents variation in knee flexion. The third mode reflects variation in tibio-femoral joint space. An articulated statistical modelling approach was developed to characterize inter-subject variability in lower limb morphology for a set of training specimens. This model can generate large sets of lower limbs to systematically study the effect of anatomical variability on joint replacement performance. Moreover, if a series of images of the lower limb during a dynamic activity are used as training data, this method can be applied to analyse variance of lower limb motion across a population

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

Summary Statement. Corin has developed bone conserving prosthesis (MiniHip™) to better replicate the physiological load distribution in the femur. This study assessed whether the MiniHip™ prosthesis can better match the pre-osteoarthritic head centre for patient demographics when compared to contemporary long stem devices. Introduction. Leg length and offset discrepancy resulting from Total Hip Replacement (THR) is a major cause of concern for the orthopaedic community. The inability to substitute the proximal portion of the native femur with a device that suitably mimics the pre-operative offset and head height can lead to loss of abductor power, instability, lower back pain and the need for orthodoses. Contemporary devices are manufactured based on predicate studies to cater for the variations within the patient demographic. Stem variants, modular necks and heads are often provided to meet this requirement. The number of components and instruments that manufacturers are prepared to supply however is limited by cost and an unwillingness to introduce unnecessary complexity. This can restrict the ability to achieve the pre-osteoarthritic head centre for all patient morphologies. Corin has developed MiniHip™ to better replicate the physiological load distribution in the femur. This study assessed whether the MiniHip™ prosthesis can better match the pre-osteoarthritic head centre for patient demographics when compared to contemporary long stem devices. Methods. The Dorr classification is a well accepted clinical method for defining femoral endosteal morphology. This is often used by the surgeon to select the appropriate type and size of stem for the individual patient. It is accepted that a strong correlation exists between Flare Index (FI), characterising the thinning of cortical walls and development of ‘stove-pipe’ morphology, and age, in particular for females. A statistical model of the proximal femur was built from 30 full length femoral scans (Imorphics, UK). Minimum and maximum intramedullary measurements calculated from the statistical model were applied to relationships produced by combining Corins work with that of prior authors. This data was then used to generate 2D CAD models into which implants were inserted to compare the head centres achievable with the MiniHip™ compared to those of a contemporary long stem. Results. Results for the CAD overlay indicated the MiniHip prosthesis is better suited to restoring head centre for a range of morphological variations. In contrast, the long stem prosthesis requires a larger size range and increased inventory in terms of stem variants and modular components to achieve the same array of head centres. The disparity between the Corin FI and that of prior authors can be accounted for by the methods employed; the greyscale-based edge detection (Imorphics) compared to a manual identification method. Discussion/Conclusion. By overlaying the Corin MiniHip™ over the CAD representation of anticipated flare index, it is evident that the MiniHip™ stem is more suitable for the anticipated range of morphologies. The versatility of this design enables the restoration of head height and offset regardless of canal geometry, degree of offset and or CCD angle. This is not the case for contemporary long stem devices which rely on a more diaphyseal region for anchorage and stability and therefore depend on stem variants and modularity to cater for morphology changes

Bone marrow lesions (BMLs) have been extensively linked to the osteoarthritis (OA) disease pathway in the knee. Semi-quantitative evaluation has been unable to effectively study the spatial and temporal distribution of BMLs and consequently little is understood about their natural history. This study used a novel statistical model to precisely locate the BMLs within the subchondral bone and compare BML distribution with the distribution of denuded cartilage. MR images from individuals (n=88) with radiographic evidence of OA were selected from the Osteoarthritis Initiative. Slice-by-slice, subvoxel delineation of the lesions was performed across the paired images using the criteria laid out by Roemer (2009). A statistical bone model was fitted to each image across the cohort, creating a dense set of anatomically corresponded points which allowed BML depth, position and volume to be calculated. The association between BML and denudation was also measured semi-quantitatively by visually scoring the lesions as either overlapping or adjacent to denuded AC, or not. At baseline 75 subjects had BMLs present in at least one compartment. Of the 188 compartments with BMLs 46% demonstrated change greater than 727mm cubed, the calculated smallest detectable difference. The majority of lesions were found in medial compartments compared to lateral compartments and the patella (Figure 1A). Furthermore, in the baseline images 76.9% of all BMLs either overlapped or were adjacent to denuded bone. The closeness of this relationship in four individuals is shown in Figure 1B. The distribution of lesions follows a clear trend with the majority found in the patellofemoral joint, medial femoro-tibial joint and medial tibial compartment. Moreover the novel method of measurement and display of BMLs demonstrates that there is a striking similarity between the spatial distribution of BMLs and denuded cartilage in subjects with OA. This co-location infers the lesions have a mechanical origin much like the lesions that occur in healthy patients as a direct result of trauma. It is therefore suggested that OA associated BMLs are in fact no different from the BMLs caused by mechanical damage, but occur as a result of localised disruption to the joint mechanics, a common feature of OA

Background. Predicting length of stay (LOS) is key to providing a cost effective and efficient arthroplasty service in an era of increasing financial constraint. Previous studies predicting LOS have not considered enhanced recovery protocols in elective hip and knee arthroplasty. Our study aims to identify patient variables in the pre and peri-operative period to predict increased LOS on patients enrolled into the standardised Chichester and Worthing Enhanced Recovery Programme (CWERP). Methods. All patients undergoing elective hip and knee arthroplasty were enrolled into CWERP using standardised anaesthetic, surgical and analgesic protocols. A data analyst prospectively collated data over 6months from anaesthetic charts and daily ward review from 663 patients between Dec 2012 and June 2013. An independent statistician undertook statistical analysis (program R, version 3.1.1). 80% of the 6months consecutive data (530 patients) were analysed, and predictive variables identified. These variables were tested against the remaining 20% of data (133 patients) predicting a LOS greater or less than our median of 4 days. Results. 663 patients were enrolled into CWERP over this period, 54% in hip arthroplasty. Statistical analysis was performed using Chi-squared test for association between actual and predicted (dichotomised) LOS being significant (p<0.0000000017). In the initial 80% (530 patients), this identified the following statistically significant variables in predicting LOS > 4 days: Age > 80 yrs, ASA 4, failure to mobilise on day of surgery, urinary catheterisation and need for blood transfusion. The statistical model when applied to the remaining 20% (133 patients) correctly categorised LOS in 101 (76%) of the patients. Conclusions. Identifying patients who fulfil our variables in the preoperative period affords better planning, maximising resources, bed efficiency and discharge planning. This also provides opportunities for financial remuneration for higher risk patients. Level of Evidence. 4

Summary. Our statistical shape analysis showed that size is the primary geometrical variation factor in the medial meniscus. Shape variations are primarily focused in the posterior horn, suggesting that these variations could influence cartilage contact pressures. Introduction. Variations in meniscal geometry are known to influence stresses and strains inside the meniscus and the articulating cartilage surfaces. This geometry-dependent functioning emphasizes that understanding the natural variation in meniscus geometry is essential for a correct selection of allograft menisci and even more crucial for the definition of different sizes for synthetic meniscal implants. Moreover, the design of such implants requires a description of 3D meniscus geometry. Therefore, the aim of this study was to quantify 3D meniscus geometry and to determine whether variation in medial meniscus geometry is size or shape driven. Patients & Methods. Sagittal knee MR images (n=35; 15 males, 20 females, aged 33±12) were acquired at 3 Tesla using a 3D SPACE sequence with isotropic resolution of 0.5×0.5×0.5mm. 3D models were generated by manual segmentation of the medial menisci from the MR scans. The surface of a reference meniscus was then described by 250 landmarks. Using an affine iterative closest point transformation, these landmarks were registered onto the full set of 3D models. Based on the set of corresponding landmarks, a point distribution model was created using the Shapeworks software (NITRC, University of Utah), an open source algorithm for constructing correspondence-based statistical models of sets of similar shapes. Several modules from Shapeworks and the Arthron software (UCD, Dublin) were used to perform principal component analysis (PCA) upon the set of landmarks. The results of the PCA enabled quantification and visualisation of the primary modes of variation in meniscal geometry. Results. The majority (77%) of variation in medial meniscus geometry was found to be due to sizing (principal component (PC) 1). Including the shape-related PC's 2 to 4, increased the cumulative percentage of represented geometry variation to over 90%. The independent shape variations described by PCs 2–4 all display larger variations in geometry of the posterior meniscal horn than the anterior section. Discussion. From this study, we can conclude that geometry variation of the medial meniscus is mainly determined by differences in size. However, since the posterior aspect of the medial meniscus experiences higher loads during daily activities than the anterior part, the shape variations described by PCs 2–4 may have a significant influence on cartilage contact pressures. Therefore, PCA alone does not provide sufficient information to define the number of implant sizes to cover a majority of the population. Analysis of the sensitivity of cartilage contact pressures to the shape variations identified in this analysis could provide the additional information needed

Several experimental studies demonstrate that controlled substrate micro-patterning has a significant impact on cell behaviour. Several experiments reveal cell spread area is dependent on both substrate rigidity and ligand density. The biomechanisms underlying such observations are not fully understood. We demonstrate that a thermodynamically consistent statistical mechanics model explains several of the key phenomena observed experimentally. We implement a steady-state thermodynamically consistent framework for stress-fibre formation and focal adhesion assembly. A Markov chain Monte-Carlo (MCMC) methodology is used to compute the distribution of cell spread states for a given substrate ligand density and stiffness. Several million spread states are considered by imposing a sequence of random trial moves on the cell. For each spread state, we compute quantities such as the cytoskeletal protein distribution, SF orientation, and FA distribution via a mixed finite element/boundary element method scheme. The free energy of all accepted states averaged equates to the homeostatic free energy. Following completion of the MCMC scheme we can construct the probability distribution for an observable of interest. For cells on a rigid substrate both the mean spread area and SD increase as the collagen density increases. A peak spread area is observed at a collagen density of 300 ng.cm-2, with an area A/A0≅2.7. Further increases in collagen density lead to a reduction in cell area, motivated by focal adhesion free energy. On a compliant elastic substrate, lower spread areas are observed (peak A/A0≅1.8). Our computed dependence of spread area on substrate stiffness and ligand density has been observed experimentally

Last decade, a shift towards operative treatment of midshaft clavicle fractures has been observed [T. Huttunen et al., Injury, 2013]. Current fracture fixation plates are however suboptimal, leading to reoperation rates up to 53% [J. G. Wijdicks et al., Arch. Orthop. Trauma Surg, 2012]. Plate irritation, potentially caused by a bad geometric fit and plate prominence, has been found to be the most important factor for reoperation [B. D. Ashman et a.l, Injury, 2014]. Therefore, thin plate implants that do not interfere with muscle attachment sites (MAS) would be beneficial in reducing plate irritation. However, little is known about the clavicle MAS variation. The goal of this study was therefore to assess their variability by morphing the MAS to an average clavicle. 14 Cadaveric clavicles were dissected by a medical doctor (MH), laser scanned (Nikon, LC60dx) and a photogrammetry was created with Agisoft photoscan (Agisoft, Russia). Subsequently a CT-scan of these bones was acquired and segmented in Mimics (Materialise, Belgium). The segmented bone was aligned with the laser scan and MAS were indicated in 3-matic (Materialise, Belgium). Next, a statistical shape model (SSM) of the 14 segmented clavicles was created. The average clavicle from the SSM was then registered to all original clavicle meshes. This registration assures correspondences between source and target mesh. Hence, MAS of individual muscles of all 14 bones were indicated on the average clavicle. Mean area is 602 mm. 2. ± 137 mm. 2. for the deltoid muscle, 1022 mm. 2. ±207 mm. 2. for the trapezius muscle, and 683 mm. 2. ± 132 mm. 2. for the pectoralis major muscle. The sternocleidomastoid muscle has a mean area of 513 mm. 2. ± 190 mm. 2. and the subclavius muscle had the smallest mean area of 451 mm. 2. ± 162 mm. 2. Visualization of all MAS on the average clavicle resulted in 72% coverage of the surface, visualizing only each muscle's largest MAS led to 52% coverage. The large differences in MAS surface areas, as shown by the standard deviation, already indicate their variability. Difference between coverage by all MAS and only the largest, shows that MAS location varies strongly as well. Therefore, design of generic plates that do not interfere with individual MAS is challenging. Hence, patient-specific clavicle fracture fixation plates should be considered to minimally interfere with MAS

Introduction. With processing age, meniscus degeneration occurs which is often associated with osteoarthritis. Existing data about the influence of degeneration on the biomechanical properties of the meniscus are still contradictory, or completely unknown regarding the hydraulic permeability. Thus, the aim of this study was to characterise the biomechanical properties and structural composition of the meniscal tissue depending on its degree of degeneration. Methods. Menisci of 24 TKR-patients (≈67.1 yrs.) were harvested and the degeneration of each region (pars anterior PA, pars intermedia PI, pars posterior PP) classified according to Pauli et al. For biomechanical characterisation, confined compression tests (20% strain; velocity: 3%h. 0. /min, relaxation time: 1h) to determine equilibrium modulus (H. A. ) and hydraulic permeability (k) and tensile tests (velocity: 5%l. 0. /min) to determine the tensile modulus were performed. Therefore, cylindrical (Ø= 4.6mm, initial height h. 0. ≈ 2.3mm) and dumbbell-shaped (3.5mm × 1.4mm × 3.5mm) samples were punched out of each region and flattened to achieve parallel surfaces. Additionally, collagen and proteoglycan (PG) content were analysed by calculating the area-under-curve of their specific wavelength ranges (1293–1356cm. −1. and 980–1120cm. −1. , respectively) using infrared (IR) spectroscopy. To identify differences regarding the meniscus regions or its degeneration, a statistically mixed model was used. Results. The compression test showed a significant decrease in H. A. with increasing degeneration (from 78kPa to 55kPa) and from anterior to posterior region (PA: ≈90kPa to PP: ≈70kPa), whereas the hydraulic permeability increased significantly from ≈(1.4 to 3.1)*10. −14. m. 4. N. −1. s. −1. and ≈(1.5 to 3)*10. −14. m. 4. N. −1. s. −1. , respectively. However, the tensile modulus was constant for all regions but showed a decreasing tendency with rising degeneration from ≈(48 to 28)MPa. The collagen content showed a significant decrease with increasing degeneration. The PG content revealed no significant differences regarding the sampling region but a downwards trend with increasing degeneration. Discussion. For the first time, we were able to show a significant increase in the hydraulic permeability with progressive meniscus degeneration while decreasing aggregate modulus. Furthermore, according to a simultaneous downwards tendency in tensile modulus, the collagen content decreased significantly with increasing degeneration. These alterations in biomechanical properties in degenerative meniscal tissue are likely related to an increased water content, also shown e.g. by Pauli et al. In conclusion, our findings may contribute to the understanding of meniscus degeneration and how alterations of meniscal properties might influence the formation of osteoarthritis

Anterior-posterior (AP) x-rays are routinely taken following total hip replacement to assess placement and orientation of implanted components. Pelvic orientation at the time of an AP x-ray can influence projected implant orientation. 1. However, the extent of pelvic orientation varies between patients. 2. Without compensation for patient specific pelvic orientation, misleading measurements for implant orientation may be obtained. These measurements are used as indicators for post-operative dislocation stability and range of motion. Errors in which could result in differences between expectations and the true outcome achieved. The aim of this research was to develop a tool that could be utilised to determine pelvic orientation from an AP x-ray. An algorithm based on comparing projections of a statistical shape model of the pelvis (n=20) with the target X-ray was developed in MATLAB. For each iteration, the average shape was adjusted, rotated (to account for patient-specific pelvic orientation), projected onto a 2D plane, and the simulated outline determined. With respect to rotation, the pelvis was allowed to rotate about its transverse axis (pelvic flexion/extension) and anterior-posterior axis (pelvic adduction/abduction). Minimum root mean square error between the outline of the pelvis from the X-ray and the projected shape model outline was used to select final values for flexion and adduction. To test the algorithm, virtual X-rays (n=6) of different pelvis in known orientations were created using the algorithm described by Freud et al. 3. The true pelvic orientation for each case was randomly generated. Angular error was defined as the difference between the true pelvic orientation and that selected by the algorithm. Initial testing has exhibited similar accuracy in determining true pelvic flexion (x̄error = 2.74°, σerror=±2.21°) and true pelvic adduction (x̄error = 2.38°, σerror=±1.76°). For both pelvic flexion and adduction the maximum angular error observed was 5.62°. The minimum angular error for pelvic flexion was 0.37°, whilst for pelvic adduction it was 1.08°. Although the algorithm is still under development, the low mean, maximum, and standard deviations of error from initial testing indicate the approach is promising. Ongoing work will involve the use of additional landmarks for registration and training shapes to improve the shape model. This tool will allow surgeons to more accurately determine true acetabular orientation relative to the pelvis without the use of additional x-ray views or CT scans. In turn, this will help improve diagnoses of post-operative range of motion and dislocation stability

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.

We carried out a cross-sectional study with analysis of the demographic, clinical and laboratory characteristics of patients with metal-on-metal hip resurfacing, ceramic-on-ceramic and metal-on-polyethylene hip replacements. Our aim was to evaluate the relationship between metal-on-metal replacements, the levels of cobalt and chromium ions in whole blood and the absolute numbers of circulating lymphocytes. We recruited 164 patients (101 men and 63 women) with hip replacements, 106 with metal-on-metal hips and 58 with non-metal-on-metal hips, aged < 65 years, with a pre-operative diagnosis of osteoarthritis and no pre-existing immunological disorders.

Laboratory-defined T-cell lymphopenia was present in13 patients (15%) (CD8⁺ lymphopenia) and 11 patients (13%) (CD3⁺ lymphopenia) with unilateral metal-on-metal hips. There were significant differences in the absolute CD8⁺ lymphocyte subset counts for the metal-on-metal groups compared with each control group (p-values ranging between 0.024 and 0.046). Statistical modelling with analysis of covariance using age, gender, type of hip replacement, smoking and circulating metal ion levels, showed that circulating levels of metal ions, especially cobalt, explained the variation in absolute lymphocyte counts for almost all lymphocyte subsets.

The effect of zoledronic acid on bone ingrowth was examined in an animal model in which porous tantalum implants were placed bilaterally within the ulnae of seven dogs. Zoledronic acid in saline was administered via a single post-operative intravenous injection at a dose of 0.1 mg/kg. The ulnae were harvested six weeks after surgery. Undecalcified transverse histological sections of the implant-bone interfaces were imaged with backscattered scanning electron microscopy and the percentage of available pore space that was filled with new bone was calculated. The mean extent of bone ingrowth was 6.6% for the control implants and 12.2% for the zoledronic acid-treated implants, an absolute difference of 5.6% (95% confidence interval, 1.2 to 10.1) and a relative difference of 85% which was statistically significant. Individual islands of new bone formation within the implant pores were similar in number in both groups but were 69% larger in the zoledronic acid-treated group. The bisphosphonate zoledronic acid should be further investigated for use in accelerating or enhancing the biological fixation of implants to bone.