Active Shape Models (ASM) have been widely used in the literature for the extraction of the tibial and the femoral bones from MRI. These methods use Statistical Shape Models (SSM) to drive the deformation and make the segmentation more robust. One crucial step for building such SSM is the shape correspondence (SC). Several methods have been described in the literature. The goal of this paper is to compare two SC methods, the Iterative Median Closest Point-Gaussian Mixture Model (IMCP-GMM) and the Minimum Description Length (MDL) approaches for the creation of a SSM, and to assess the impact on the accuracy of the femur segmentation in MRI. 28 MRI of the knee have been used. The validation has been performed by using the leave-one-out cross-validation technique. An ASMMDL and an ASMIMCP-GMMM has been built with the SSMs computed respectively with the MDL and IMCP-GMM methods. The computation time for building both SSMs has been also measured. For 90% of data, the error is inferior to 1.78 mm and 1.85 mm for respectively the ASMIMCP-GMM and the ASMMDL methods. The computation time for building the SSMs is five hours and two days for respectively the IMCP-GMM and the MDL methods. Both methods seem to give, at least, similar results for the femur segmentation in MRI. But (1) IMCP-GMM can be used for all types of shape, this is not the case for the MDL method which only works for closed shape, and (2) IMCP-GMM is much faster than MDL

Cerebral palsy (CP) is a neural condition that impacts and impairs the musculoskeletal system. Skeletal muscles, particularly in the lower limb, have previously been shown to be significantly reduced in volume in CP compared to typical controls. Muscle volume is a gross measure, however, and does not capture shape characteristics which—if quantified—could offer a robust and novel assessment of how this condition impacts skeletal muscle form and function in CP. In this study, we used mathematical shape modelling to quantify not just size, but also the shape, of soleus muscles in CP and typically developing (TD) cohorts to explore this question. Shape modelling is a mathematical technique used previously for bones, organs, and tumours. We obtained segmented muscle data from prior MRI studies in CP. We generated shape models of CP and TD cohorts and used our shape models to assess similarities and differences between the cohorts, and we statistically analysed shape differences. The shape models revealed similar principal components (PCs), i.e. the defining mathematical features of each shape, yet showed greater shape variability within the CP cohort. The model revealed a distinct feature (a superior –> inferior shift of the broad central region), indicating the model could identify muscular features that were not apparent with direct observation. Two PCs dominated the differences between CP and TD cohorts: size and aspect ratio (thinness) of the muscle. The distinct appearance characteristic in the CP model correspond to specific muscle impairments in CP to be discussed further. Overall, children with CP had smaller muscles that also tended to be long, thin, and narrow. Shape modelling captures shape features quantitatively, which indicate the ways that muscles are being impacted in CP. In the future, we hope to tailor this technique toward informing diagnosis and treatments in CP

Statistical shape modeling (SSM) and statistical density modeling (SDM) are tools capable of describing the main modes of deviation in the shape and density distribution of the shoulder using a set of uncorrelated variables called principal components (PCs). We hypothesize that the first PC of the SDM, which scales overall density up/down, will be inversely correlated with age and will, on average, be greater for males than females. We also hypothesize that there is a correlation between some PCs of shape and density. SSM and SDM were developed for scapulae and humeri by segmenting surface meshes from computed tomographic images of 75 cadaveric shoulders. Bones were co-registered and defined by the same surface mesh. Volumetric tetrahedral meshes were defined for one of the specimens serving as base meshes for SDM. Base meshes were morphed to each individual bone's surface and superimposed upon the corresponding CT data to determine image intensity in Hounsfield units at each node. Principal component analysis was performed on the exterior shape and internal density distribution of bones. T-tests were performed to find any differences in PC scores between males and females, and Pearson correlation coefficients were calculated for age and PC scores. Finally, correlation coefficients between each of the PCs of the shape and density models were calculated. For the humerus, the first three PCs of the SDM were significantly correlated with age (ρ = 0.40, −0.46, and 0.36, all p ≤ 0.007). For the scapula, the first and ninth PCs showed such correlation (ρ = −0.31, and −0.32, all p ≤ 0.02). Statistically significant differences due to sex were found for the second to sixth SDM PCs of the humerus, with differences in average PC scores of 1, 1, −0.7, −0.8, and −0.6 standard deviations, respectively, for males relative to females. For the scapula, the second, fifth and seventh SDM PCs were significantly different between males and females, with average PC scores differing by 1.1, 0.7, and −0.6 standard deviations. Finally, for both bones, the first PC of SSM showed a weak but significant correlation with the second PC of the SDM (ρ = 0.47, p < 0.001 for the humerus, and ρ = 0.39, p < 0.001 for the scapula). The results of this study suggest that age has a significant influence on the first PC of the SDM, associated with scaling the density in the cortical boundary. Moreover, the negative correlation of age with the second PC of the humerus in SDM which mostly influences the thickness of the cortical boundary implies cortical thinning with age. The second PC of both bones differed significantly between males and females, implying that cortical thickness differs between sexes. Also, there was a significant correlation between the size of the bones and the thickness of the cortical boundary. These findings can help guide the designs of population-based prosthesis components

Background. Degeneration of the shoulder joint is a frequent problem. There are two main types of shoulder degeneration: Osteoarthritis and cuff tear arthropathy (CTA) which is characterized by a large rotator cuff tear and progressive articular damage. It is largely unknown why only some patients with large rotator cuff tears develop CTA. In this project, we investigated CT data from ‘healthy’ persons and patients with CTA with the help of 3D imaging technology and statistical shape models (SSM). We tried to define a native scapular anatomy that predesignate patients to develop CTA. Methods. Statistical shape modeling and reconstruction:. A collection of 110 CT images from patients without glenohumeral arthropathy or large cuff tears was segmented and meshed uniformly to construct a SSM. Point-to-point correspondence between the shapes in the dataset was obtained using non-rigid template registration. Principal component analysis was used to obtain the mean shape and shape variation of the scapula model. Bias towards the template shape was minimized by repeating the non-rigid template registration with the resulting mean shape of the first iteration. Eighty-six CT images from patients with different severities of CTA were analyzed by an experienced shoulder surgeon and classified. CT images were segmented and inspected for signs of glenoid erosion. Remaining healthy parts of the eroded scapulae were partitioned and used as input of the iterative reconstruction algorithm. During an iteration of this algorithm, 30 shape components of the shape model are optimized and the reconstructed shape is aligned with the healthy parts. The algorithm stops when convergence is reached. Measurements. Automatic 3D measurements were performed for both the healthy and reconstructed shapes, including glenoid version, inclination, offset and critical shoulder angle. These measurements were manually performed on the mean shape of the shape model by a surgeon, after which the point-to-point correspondence was used to transfer the measurements to each shape. Results. The critical shoulder angle was found to be significantly larger for the CTA scapulae compared to the references (P<0.01). When analyzing the classified scapulae significant differences were found for the version angle in the scapulae of group 4a/4b and the critical shoulder angle of group 3 when compared to the references (P<0.05). Conclusion. Patients with CTA have a larger critical shoulder angle compared with reference patients. Some significant differences are found between the scapulae from patients in different stages of CTA and healthy references, however the differences are smaller than the accuracy of the SSM reconstruction. Therefore, we are unable to conclude that there is a predisposing anatomy in terms of glenoid version, inclination or offset for CTA

Introduction. Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to apply them in pre-clinical testing, implant development and pre-operative planning. By reconstructing the native situation of a defect pelvis using a Statistical Shape Model (SSM), a more quantitative analysis of the bone defects could be performed. The aim of this study is to develop such a SSM and to validate its accuracy using relevant clinical scenarios and parameters. Methods. An SSM was built on the basis of segmented 66 CT dataset of the pelvis showing no orthopedic pathology. By adjusting the SSM's so called modes of shape variation it is possible to synthetize new 3D pelvis shapes. By fitting the SSM to intact normal parts of an anatomical structure, missing or pathological regions can be extrapolated plausibly. The validity of the SSM was tested by a Leave-one-out study, whereby one pelvis at a time was removed from the 66 pelvises and was reconstructed using a SSM of the remaining 65 pelvises. The reconstruction accuracy was assessed by comparing each original pelvis with its reconstruction based on the root-mean-square (RMS) surface error and five clinical parameters (center of rotation, acetabulum diameter, inclination, anteversion, and volume). The influence of six different numbers of shape variation modes (reflecting the degrees of freedom of the SSM) and four different mask sizes (reflecting different clinical scenarios) was analyzed. Results. The Leave-one-out study showed that the reconstruction errors decreased when the number of shape variation modes included in the SSM increased from 0 to 20, but remained almost constant for higher numbers of shape variation modes. For the SSM with 20 shape variation modes, the RMS of the reconstruction error increased with increasing mask size, whereas the other parameters only increased from Mask_0 to Mask_1, but remained almost constant for Mask_1, Mask_2 and Mask_3. Median reconstruction errors for Mask_1, Mask_2, and Mask_3 were approximately 3 mm in Center of Rotation (CoR) position, 2 mm in Diameter, 3° in inclination and anteversion, as well as 5 ml in volume. Discussion. This is the first study analyzing and showing the feasibility of a quantitative analysis of acetabular bone defects using a SSM-based reconstruction method in the clinical scenario of a defect or implant in both acetabuli and incomplete CT-scans. Validation results showed acceptable reconstruction accuracy, also for clinical scenarios in which less healthy bone remains. Further studies could apply this method on a larger number of defect pelvises to obtain quantitative measures of acetabular bone defects

INTRODUCTION. Statistical shape models (SSM) have become a common tool to create reference models for design input and verification of total joint implants. In a recent discussion paper around Artificial Intelligence and Machine Learning, the FDA emphasizes the importance of independent test data [1]. A leave-one-out test is a standard way to evaluate the generalization ability of an SSM [2]; however, this test does not fulfill the independence requirement of the FDA. In this study, we constructed an SSM of the knee (femur and tibia). Next to the standard leave-one-out validation, we used an independent test set of patients from a different geographical region than the patients used to build the SSM. We assessed the ability of the SSM to predict the shapes of knees in this independent test set. METHODS. A dataset of 82 computed tomography (CT) scans of Caucasian patients (42 male, 40 female) from 11 different geographic locations in France, Germany, Austria, Italy and Australia were used as training set to make an SSM of the femur and tibia. A leave-one-out test was performed to assess the ability of the SSM to predict shapes within the training set. A test dataset of 4 CT scans of Caucasian patients from Russia were used for the validation. The SSM was fitted onto each of the femur and tibia shapes and the root mean square error (RMSE) was measured. RESULTS. The leave-one-out tests showed that the femur and tibia SSMs were able to predict patients in the input population with an RMSE of 0.59 ± 0.1 mm (average ± standard deviation) for the femur and 0.70 ± 0.1 mm for the tibia. The validation test showed that the femur and tibia SSMs were able to predict the shapes of the Russian patients with an RMSE 0.62 ± 0.1 mm for the femur and 0.71 ± 0.1 mm for the tibia. DISCUSSION. There were no significant differences in the ability of the SSM to predict femur and tibia shapes of patients in a new geographic region compared to the ability of the SSM to predict shapes within the training set. CONCLUSIONS. Based on this study, 11 different geographic locations in France, Germany, Austria, Italy and Australia provide a complete sample of the Caucasian population. Using an independent set of CT scans is a valuable tool to further validate the generalization ability of an SSM. For any figures or tables, please contact authors directly

Introduction. Removal of primary components during revision TKA procedure can damage underlying bone, resulting in defects that may need filled for stability of the revision reconstruction. Special revision components including cones and/or augments are often used to compensate for the missing bones. Little work has been done to characterize metaphyseal geometry in the vicinity of the knee joint, however, in order to motivate proper size and shape of cones and augments. The objective of this study was to use statistical shape modelling to evaluate variation in endosteal anatomy for revision TKA. Methods. Digital models of the femur and tibia were generated through segmentation of computed tomography scans, for the femur and the tibia (n∼500). Custom software was used to perform virtual surgery and statistical shape analysis of the metaphyseal geometry. A representative and appropriately sized revision femoral component was placed on each bone, assuming anterior referencing with an external rotation of 3 degrees from the posterior condyle axis. The outer and inner boundaries of the cortical bone were determined at the resection level and at 5 mm increments proximally, up to 40 mm. Similar analyses were performed on the tibia, using a typical revision resection (0 degrees medial and posterior slope), with outer and inner boundaries of the cortical bone were determined in 5 mm increments up to 40mm distal to the resection. Metaphyseal contours were exported relative to the central fixation feature of the implant, and average geometries were calculated based on size, and across the entire cohort. Principal Component Analysis (PCA) was used to quantify the variability in shape, specifically to evaluate the +/− 1 and 2 standard deviation geometries at each cross section level of Principal Component 1 (PC1). Results. Representative results illustrating the effect of size for the femur at single depth and the effect of depth and PC1 for tibia are reported. The average inner metaphyseal geometry of the femur (30mm proximal to resection) varied from 25.1×47.7 mm (AP x ML) at the smallest size to 54.5×78.0 at the largest size. The overall average tibia geometry decreased from 51.5×69.5 mm at the base resection level to 33.5×31.3 mm at the most distal resection level (40mm) distal to the resection. At the 20 mm level, the average tibia contour of 45.0×47.8 mm changed to 32.2×33.4 at −2 standard deviations of PC1 and 57.9×62.4 mm at the +2 standard deviations of PC1. Discussion. The generated contours can be used as a design input to optimize the shape of cones and augments, in order to fit potential defects in the femur and tibia encountered during revision TKA while respecting the anatomical constraints of the bone. Statistical shape analysis shows that these constraints are not strictly uniform scaling, based on bone size or on location in the metaphysis, but rather reflect variations in shape that may be used to optimize fit and stability of the prostheses

Introduction. A good anatomic fit of a Total Knee Arthroplasty is crucial to a good clinical outcome. The big variability of anatomies in the Asian and Caucasian populations makes it very challenging to define a design that optimally fits both populations. Statistical Shape Models (SSMs) are a valuable tool to represent the morphology of a population. The question is how to use this tool in practice to evaluate the morphologic fit of modern knee designs. The goal of our study was to define a set of bone geometries based on SSMs that well represent both the Caucasian and the Asian populations. Methods. A Statistical Shape Model (SSM) was built and validated for each population: the Caucasian Model is based on 120 CT scans from Russian, French, German and Australian patients. The Asian Model is based on 80 CT scans from Japanese and Chinese patients. We defined 7 Caucasian and 5 Asian bone models by using mode 1 of the SSM. We measured the antero-posterior (AP) and medio-lateral (ML) dimensions of the distal femur on all anatomies (input models and generated models) to check that those bone models well represent the studied population. In order to cover the whole population, 10 additional bone models were generated by using an optimization algorithm. First, a combined Asian-Caucasian SSM was generated of 92 patients, equally balanced between male and female, Caucasian and Asian. 10 AP/ML dimensions were defined to obtain a good coverage of the population. For a given AP/ML dimension, Markov chain Monte Carlo sampler was used to find the most average shape with AP/ML dimensions as close as possible to the target dimensions. The difference of the AP/ML dimensions of the generated models to the target dimensions was computed. A chi-squared distribution was used to assess how average the resulting shapes were compared to typical patient shapes. Results. The AP-ML dimensions of the 7 Caucasian bones and the 5 Asian bones well cover the range of the respective populations. For the Caucasian Femur, the AP/ML dimensions range from (53,6/64,9mm) for size 1 to (67,7/80,7mm) for size 7. For the Asian Femur, the AP/ML dimension range from (53,0/62,4mm) for size 1 to (60,5/72,4mm) for size 5. The dimensions of the 10 additionally generated bones differed in average (± 1 standard deviation) by 0,2±0,4mm in AP and 0,5±0,5mm in ML to the target dimensions. The maximal deviation was 0,9mm in AP and 1,0mm in ML. All 10 bones had a P-value of P < 10. -27. according to the chi-squared distribution. Conclusion. The proposed models of 7 Caucasian and 5 Asian bones well represent both populations. The 10 additional geometries enable to get a complete coverage of the population. Since they are very close to average, all these bone models provide more generalized reference shapes compared to individual patients. By performing a virtual implantation on those anatomies, the anatomical fit of implants to these populations can be evaluated. For any figures or tables, please contact authors directly

Aims. The aim of this study was to optimize screw hole placement in an acetabulum cup implant to improve secondary initial fixation by identifying the region of thickest acetabulum bone. The “scratch fit” of modern acetabular cup implants with highly porous coatings is often adequate for initial fixation in primary total hip arthroplasty. Initial fixation must limit micromotion to acceptable levels to facilitate osseointegration and long term cup stability. Secondary initial fixation can be required in cases with poor bone quality or bone loss and is commonly achieved with bone screws and a cup implant with multiple screw holes. To provide maximum secondary initial fixation, the cup screw holes should be positioned to allow access to the limited region of thick pelvic bone. Patients and Methods. Through a partnership with Materialise, a statistical shape model of the pelvis was created utilizing 80 CT scans (36 female, 44 male). To limit the effect of variation outside the area of cup implant fixation, the shape model includes only the inferior pelvis (cut off at the greater sciatic notch and above the anterior inferior iliac spine). A virtual implantation protocol was developed which creates instances of the pelvis shape model that accurately simulate the intraoperative reaming of the acetabulum to accept the cup implant. First a sphere is best fit to the native acetabulum and the diameter is rounded to the nearest whole millimeter. The diameter of the best fit sphere is increased by 1mm to simulate bone removal during the spherical reaming procedure. The sphere is translated medially and superiorly such that it is tangent to the teardrop and removes 2mm of superior acetabulum. The sphere is used to perform a Boolean subtraction from the shape model to create a virtually reamed pelvis shape model. The Materialise 3-Matic software was used to perform a thickness analysis of the prepared shape models. The output of the thickness analysis is displayed as a color “heat map” where green represents thin bone and red is thick bone. The region of thickest bone was identified and used to drive ideal screw hole placement in the cup implant to access this region. Results. The analysis finds there is a limited arc of thick bone in the acetabulum that begins superiorly and extends posterior-inferior that accounts for only about 15% of total reamed surface area. Maximum screw purchase is provided when screw holes in the cup implant are placed over this limited region of thick bone. The thickest bone, located superiorly, facilitates the placement of a long bone screw up the iliac column and the posterior-inferior region of thick bone facilitates the placement of additional posterior screws. Conclusion. The shape model development, virtual implantation protocol, and heat map thickness analysis allowed the placement of bone screw holes directly over the limited region of thick pelvic bone. This allows maximum screw purchase which is important in achieving adequate secondary initial fixation with bone screws. Disclaimer. Author is an engineer employed by DJO Surgical who funded this study

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

Bone shape estimation from partial observations, such as fluoroscopy or ultrasound, has been subject of significant interest over the past decade and can be regarded as the driving force behind several advances in statistical modelling of shape. While statistical models were initially used mostly as regularisers constraining shape matching algorithms, they are now increasingly employed due to their predictive ability, when only limited observations are available. With the current efforts toward minimal invasiveness, radiation exposure reduction, and optimization of the cost-effectiveness of procedures, two major challenges emerge on the field of statistical modelling. The first one is to develop methods that enable the use of as much information as possible that can be relevant for a specific shape prediction task, within the aforementioned limits. The second challenge concerns the accuracy of the resulting predictions, which needs to be quantified in order to evaluate the associated risks, and to optimise the data acquisition procedures. In terms of shape prediction, most studies so far have concentrated on individualizing statistical atlases based on imaging data. However, relevant information about skeletal morphology can also be obtained from simple anthropometric and morphometric measurements such as gender, age, body-mass index, and bone specific measurements. We develop a multivariate regression framework that enables to take into account such combinations of predictors simultaneously with sparse observations of the bone surface for improved prediction of the complete bone shape. In particular, we describe in a quantitative and localised fashion the individual contributions but also the complementarities of the heterogeneous sources of information with respect to bone morphology assessment. To do so, we compare the prediction errors obtained with different combinations of predictors, relying on cross-validation experiments. In addition to providing valuable and complementary predictive information, non-imaging measurements can be exploited to automatically initialise surface registration algorithms which increase their robustness for the determination of patient specific morphologies. A statistical model, by essence, is a mathematical model resulting from a learning phase using a set of training data. Statistical model based prediction is affected by three main sources of errors. The pre-processing of the training data, in particular the establishment of anatomical correspondences between the different samples, and the limited number of training elements constitute a first source of uncertainties. Second, the predictors can be affected by measurement noise, which will then propagate through the prediction process. Finally, and this is particularly important in the context of sparse observation data, the limited correlations between the predictors and the shape to predict imply theoretical limits for the achievable accuracy of such approaches. We have developed a framework enabling to account for these various sources of uncertainty, and propagating them through the prediction pipeline to generate confidence regions around the predicted shape. It relies extensively on cross-validation experiments in order to quantify the limitations of the statistical model with respect to the representation of new shapes (generalization ability) and to their prediction from partial data. Furthermore, we demonstrate the reliability of the obtained regions, following the procedure initially proposed in. We evaluate our approaches on a database of 140 femur bones, age range: 23–83, mean 62.57, stdv 15; 46% males and 54% females, with known age, height and weight. Morphometric measurements such as bone length, inter-condyle distance or anteversion angle are considered, either as predictors, together with sparse point clouds around the femoral head and greater trochanter, or as a pose-independent quality-of-fit metric. Cross-validation experiments indicate that a higher accuracy can be reached when complementing surface-based predictors with relevant anthropometric and morphometric information, and that reliable confidence regions can be estimated

Background. CT-based navigation system in total hip arthroplasty(THA) is widely used to achieve accurate implant placement. The purpose of this study was to evaluate the influence of initial error correction according to the differences in the shape of the acetabulum, and correction accuracy associated with operation approach after localization of registration points at anterior or posterior area of the acetabulum. Methods. We set the anterior pelvic plane(APP) as the reference plane, and defined the coordinates as follows: X-axis for external direction, Y-axis for anterior direction, and Z-axis for proximal direction. APP is defined by the anterior superior iliac spines and anterior border of the pubic symphysis. We made a bone model of bilateral acetabular dysplasia of the hip, after rotational acetabulum osteotomy(RAO) on one side, and performed registration using infrared-reflective markers. At first, we registered the initial error on navigation system, and calculated the accuracy of the error correction based on each shape of the acetabulum as we increased the surface matching points. Based on the actual operation approach, we also examined the accuracy of the error correction when concentrating the matching points in anterior or posterior areas of the acetabulum. Results. For the rotational acetabular osteotomy model, the range of possible initial error correction increased as the surface matching points increased on both X-axis and Y-axis: On the X-axis, the range increased from 6mm to 10mm as the surface matching point increased from 10 to 20; and on the Y-axis, the range increased from 2mm to 10mm as the point increased 10 to 50. The range did not increase on the Z-axis. For the acetabular dysplasia model, the range of possible initial error correction increased on the X-axis(the range increased from 2mm to 8mm as the point increased from 10 to 50); however, no increase was observed for the Y- and Z-axis. Furthermore, concentrating the surface matching points in the posterior area around the acetabulum was more effective for the correction of the initial rotational error. Discussion. Because of the different anatomical shapes of the acetabulum, the error directions that were difficult to correct tended to vary between dysplasia and post-RAO. The error correction of Z-axis was difficult on both shapes of the acetabulum. Thus, the careful initial setting on Z-axis is important to minimize the error. Surface matching point on the posterior part of the acetabulum is more effective in correcting the initial rotational error compared with the anterior part of the acetabulum. It was shown that the difference in the error correction was affected by the localization of the registration points around the acetabulum. We presumed that using surface matching points on posterior area of the acetabulum improves the accuracy of the CT-based navigation system on the anterior approach. When using the system, it is important to understand the tendency that the shape of the acetabulum and the localization of the surface matching points have influence on correction of the initial error

INTRODUCTION. During total knee arthroplasty (TKA), the pursuit of accurate alignment, proper bone cuts, and good soft tissue balancing sometimes can result in the overhang of the femoral component, especially in smaller-sized Asian knees. As size and shape of the distal femur are highly variable, component designs that offer increased shape and size offerings may be desirable to fit the distal femur. This study tested the hypothesis that increased shape and size offerings in TKA femoral designs may improve their fit to the Japanese femur compared to designs that offer only one shape and limited sizes. METHODS. Five contemporary femoral component designs were evaluated (Designs A-E). Design A has multiple mediolateral (ML) size offerings for a specific component anteroposterior (AP) size, and the finest increment (2mm) in AP sizes among all the designs. Designs B-E have single ML offerings across component AP sizes. For each design, virtual TKA resections were performed on the digital surfaces of 82 Japanese distal femora, each sized by selecting the component AP size that most closely matched but did not exceed the femoral AP dimension (Fig 1A,B). The aspect ratio (ML/AP) of the resected femora was regressed against the aspect ratio of their properly sized components per design. The closeness of each design to the perfect shape match was evaluated by the root-mean-square deviation (RMSD) of the deviations between the femoral bone and components. Differences in ML dimensions (overhang/underhang) between component and resected femora were calculated (Fig1C,D). The incidence of clinically significant femoral overhang (>3mm), in which component downsizing is required, were analyzed. RESULTS. Design A captured the shape variability in the resected femur, with component aspect ratios being the closest to the anatomy of the resected femur among the five designs (RMSD=0.04) (Fig 2). In contrast, Designs B-E had greater deviation from the shape of the resected femur (RMSD=0.08–0.12), indicating higher incidence of shape mismatch that may lead to surgical compromise. Designs C and E had the highest incidence and severity for clinically significant overhang, followed by Designs B and D (Fig 3A). Design A exhibited the lowest incidence and severity of clinically significant overhang and had the least variability in ML width differences (standard deviation=2.4mm) compared to the other designs (Designs B-E, standard deviation=4.0–4.9mm). In all the designs investigated, the percentage of bones that required downsizing was the highest in Designs C (48%) and E (39%), followed by Designs B and D (17% and 22%). In contrast, minimal downsizing was required in Design A (4%). The highest incidences of downsizing were generally observed in mid-sized components (Fig 3B). DISCUSSION. The design family with multiple ML offerings per AP size (Design A) provides the closest match to the shape of the distal femur compared to those with single ML offerings (Designs B-E). Additionally, increased AP size offerings in Design A (12 sizes) further improve component fit compared to Designs B-E (7–9 sizes). Among all five design families investigated, Design A exhibited minimal incidence of downsizing due to clinically significant overhang in the Japanese patients

Transforaminal lumbar interbody fusion (TLIF) using an implanted cage is the gold standard surgical treatment for disc diseases such as disc collapse and spinal cord compression, when more conservative medical therapy fails. Titanium (Ti) alloys are widely used implant materials due to their superior biocompatibility and corrosion resistance. A new Ti-6Al-4V TLIF cage concept featuring an I-beam cross-section was recently proposed, with the intent to allow bone graft to be introduced secondary to cage implantation. In designing this cage, we desire a clear pathway for bone graft to be injected into the implant, and perfused into the surrounding intervertebral space as much as possible. Therefore, we have employed shape optimization to maximize this pathway, subject to maintaining stresses below the thresholds for fatigue or yielding. The TLIF I-beam cage (Fig. 1(a)) with an irregular shape was parametrically designed considering a lumbar lordotic angle of 10°, and an insertion angle of 45° through the left or right Kambin's triangles with respect to the sagittal plane. The overall cage dimensions of 30 mm in length, 11 mm in width and 13 mm in height were chosen based on the dimensions of other commercially available cages. The lengths (la, lp) and widths (wa, wp) of the anterior and posterior beams determine the sizes of the cage's middle and posterior windows for bone graft injection and perfusion, so they were considered as the design variables for shape optimization. Five dynamic tests (extension/flexion bending, lateral bending, torsion, compression and shear compression, as shown in Fig. 2(b)) for assessing long term cage durability (10. 7. cycles), as described in ASTM F2077, were simulated in ANSYS 15.0. The multiaxial stress state in the cage was converted to an equivalent uniaxial stress state using the Manson-Mcknight approach, in order to test the cage based on uniaxial fatigue testing data of Ti-6Al-4V. A fatigue factor (K) and a critical stress (σcr) was introduced by slightly modifying Goodman's equation and von Mises yield criterion, such that a cage design within the safety design region on a Haigh diagram (Fig. 2) must satisfy K ≤ 1 and σcr ≤ SY = 875 MPa (Ti-6Al-4V yield strength) simultaneously. After shape optimization, a final design with la = 2.30 mm, lp = 4.33 mm, wa = 1.20 mm, wp = 2.50 mm, was converged upon, which maximized the sizes of the cage's windows, as well as satisfying the fatigue and yield strength requirements. In terms of the strength of the optimal cage design, the fatigue factor (K) under dynamic torsion approaches 1 and the critical stress (σcr) under dynamic lateral bending approaches the yield strength (SY = 875 MPa), indicating that these two loading scenarios are the most dangerous (Table 1). Future work should further validate whether or not the resulting cage design has reached the true global optimum in the feasible design space. Experimental validation of the candidate TLIF I-beam cage design will be a future focus. For any figures or tables, please contact authors directly (see Info & Metrics tab above).

Important factors affecting quality of life (QOL) after total knee arthroplasty (TKA) include postoperative knee kinematics and geometry, influenced by implant design and placement (Matsuda 2001; Nishikawa 2013; Noble 2005). Although specific design factors and their effect on kinematics or QOL have been investigated previously, the inter-relationships between preop-postop changes in kinematics, geometry and the resulting QOL have not been studied to our knowledge. These are essential to understand the interplay between the different factors, and to determine which factors manufacturers and surgeons should focus on when designing and implanting knee prostheses. In addition, the majority of TKA studies focus on the tibiofemoral (TF) joint, although the patellofemoral (PF) joint is routinely the source of postop complications; the PF joint is difficult to study due to polyethylene radio-transparency and because the femoral component obscures the patella from most directions. The purpose of this pilot study was to correlate changes in knee articular shape, over which the implant designers and surgeons have some control, to changes in kinematics and postop QOL, with a particular focus on the PF joint, to answer the following research questions for a sample population with a given implant design and surgeon: (1) Do changes in knee shape affect knee kinematics? In particular, is patellar tracking affected by groove location? (2) Do changes in knee kinematics affect QOL? (3) Do changes in knee shape (resulting from implant design and placement) affect QOL? (4) Do individuals with worse QOL differ from those with better QOL?

We present a novel method to derive the surface distance of an osteosynthesis plate w.r.t. the patient-specific surface of the distal femur based on 2D X-ray images. Our goal is to study from clinical data, how the plate-to-bone distance affects bone healing. The patient-specific 3D shape of the femur is, however, seldom recorded for cases of femoral osteosynthesis since this typically requires Computed Tomography (CT), which comes at high cost and radiation dose. Our method instead utilises two postoperative X-ray images to derive the femoral shape and thus can be applied on radiographs that are taken in clinical routine for follow-up. First, the implant geometry is used as a calibration object to relate the implant and the individual X-ray images spatially in a virtual X-ray setup. In a second step, the patient-specific femoral shape and pose are reconstructed in the virtual setup by fitting a deformable statistical shape and intensity model (SSIM) to the images. The relative positioning between femur and implant is then assessed in terms of displacement between the reconstructed 3D shape of the femur and the plate. A preliminary evaluation based on 4 cadaver datasets shows that the method derives the plate-to-bone distance with a mean absolute error of less than 1mm and a maximum error of 4.7 mm compared to ground truth from CT. We believe that the approach presented in this paper constitutes a meaningful tool to elucidate the effect of implant positioning on fracture healing

This work was motivated by the need to capture the spectrum of anatomical shape variability rather than relying on analyses of single bones. A novel tool was developed that combines image-based modelling with statistical shape analysis to automatically generate new femur geometries and measure anatomical parameters to capture the variability across the population. To demonstrate the feasibility of the approach, the study used data from 62 Caucasian subjects (31 female and 31 male) aged between 43 and 106 years, with CT voxel size ranging 0.488 × 0.488 × 1.5 mm to 0.7422 × 0.7422 × 0.97 mm. The scans were divided into female and male subgroups and high-quality subject-specific tetrahedral finite element (FE) meshes resulting from segmented femurs formed the so-called training samples. A source mesh of a segmented femur (25580 nodes, 51156 triangles) from the Visible Human dataset [Spitzer, 1996] was used for elastic surface registration of each considered target male and female subjects, followed by applying a mesh morphing strategy. To represent the variations in bone morphology across the population, gender-based Statistical Shape Models (SSM) were developed, using Principal Component Analysis. These were then sampled using the principal components required to capture 95% of the variance in each training dataset to generate 1000 new anatomical shapes [Bryan, 2010; Blanc, 2012] and to automatically measure key anatomical parameters known to critically influence the biomechanics after hip replacement (Figure 1). Analysis of the female and male training datasets revealed the following data for the five considered anatomical parameters: anteversion angle (12.6 ± 6.4° vs. 6.2 ± 7.5°), CCD angle (124.8 ± 4.7° vs. 126.3 ± 4.6°), femoral neck length (48.7 ± 3.8 mm vs. 52 ± 5 mm), femoral head radius (21.5 ± 1.3 mm vs. 24.9 ± 1.5 mm) and femur length (431.0 ± 17.6 mm vs. 474.5 ± 26.3 mm). However, using the SSM generated pool of 1000 femurs, the following data were computed for females against males: anteversion angle (10.5 ± 14.3° vs. 7.6 ± 7.2°), CCD angle (123.9 ± 5.8° vs. 126.7 ± 4°), femoral neck length (46.7 ± 7.7 mm vs. 51.5 ± 4.4 mm), femoral head radius (21.4 ± 1.2 mm vs. 24.9 ± 1.4 mm) and femur length (430.2 ± 16.1 mm vs. 473.9 ± 25.9 mm). The highest variability was found in the anteversion of the females where the standard deviation in the SSM-based sample was increased to 14.3° from 6.4° in the original training dataset (Figures 2 & 3). The mean values for both females (10.5°) and males (7.6 °) were found close to the values of 10° and 7° reported in [Mishra, 2009] in 31 females and 112 males with a [2°, 25°] and [2°, 35°] range, respectively. Femoral neck length of the female (male) subjects was 47.3 ± 6.2 mm (51.8 ± 4.1 mm) compared to 48.7 ± 3.8 mm (52 ± 5 mm) in the training dataset and 63.65 ± 5.15 mm in [Blanc, 2012] with n = 142, 54% female, 46% male and a [50.32–75.50 mm] range. For the measured CCD angle in both female (123.9 ± 5.8°) and male (126.7 ± 4°) subjects, a good correlation was found with reported values of 128.4 ± 4.75° [Atilla, 2007], 124.7 ± 7.4° [Noble, 1988] and 129.82 + 5.37° [Blanc, 2012]. In conclusion, the present study demonstrates that the proposed methodology based on gender-specific statistical shape modelling can be a valuable tool for automatically generating a large specific population of femurs to support implant design and planning of femoral reconstructive surgery

Ultra-high molecular weight polyethylene (UHMWPE) is the sole polymeric material currently used for weight-bearing surfaces in total joint arthroplasty. However, the wear phenomenon of UHMWPE components in knee and hip prostheses after total joint arthroplasty is one of the major restriction factors on the longevity of these implants. In order to minimize the wear of UHMWPE and to improve the longevity of artificial joints, it is necessary to clarify the factors influencing the wear mechanism of UHMWPE. In the microscopic surface observation of the virgin knee prosthesis with anatomical design, various grades of microscopic surface scratches and defects caused by machining and surface finishing processes during manufacture of the component were observed on the surface of the metallic femoral component [Fig. 1] (C. Cho et al, 2009), although the overall surface were finished at smoother level. It is thought that certain levels of the microscopic surface asperities caused by these surface damages in the metallic femoral component might contribute to increasing and/or accelerating wear of the UHMWPE tibial insert. Therefore, it is necessary to clarify quantitatively the influence of the microscopic surface asperities of the metallic components in virgin artificial joints on the wear of UHMWPE components. The primary purpose of this study was to investigate the influence of the microscopic surface asperities of the virgin metallic femoral component on the wear of the UHMWPE tibial insert in the virgin knee prosthesis. In this study, the authors focused on the three-dimensional shape of the microscopic surface asperities as a factor influencing the wear mechanism of the UHMWPE tibial insert. The 3D microscopic surface profile measurement of the virgin metallic femoral component using a laser microscope and reproduction of the femoral component surface using 3D CAD software were performed [Fig. 2] in order to produce idealized 3D finite element models of the microscopic surface asperity of the femoral component based on actual measurement data. Elasto-plastic finite element contact analyses between idealized microscopic surface asperities and UHMWPE were also performed in order to investigate the influence of the three-dimensional shape of the microscopic surface asperities of the virgin metallic femoral component on the wear of the UHMWPE tibial insert. The analytical findings of this study suggest that the aspect ratio and shape ratio [Fig. 3] of the microscopic surface asperity of the virgin metallic femoral component have an important influence on increasing and/or accelerating wear of the UHMWPE tibial insert

Objective. The aim of this study was to evaluate the shape of patella relative to the femoral epicondylar axis and to find sex differences. Materials and methods. Computed tomography (CT) images of 100 knees with tibiofemoral osteoarthritis in 100 patients were prospectively collected. All patients were diagnosed as varus-type osteoarthritis with no destructive patellar deformity. Fifty patients were male and 50 female. The average male age was 70.8±14.6 (mean ± SD) years and the average female age was 73.3±6.7 years. Forty nine knees were right and 51 knees were left. The average height of males was 162.6±7.4 cm and that of females 149.6±5.7 cm. Males were significantly taller than females. The CT scan was performed with 2mm-interval slices in the vertical plane to the long axis of femoral shaft. Every CT image was examined to determine the maximum distance between the medial and lateral femoral epicondyle (inter-epicondylar distance, IED) along the epicondylar axis. The maximum patellar width and thickness were also measured at the image which had these maximum distances, while patellar cartilage thickness in anteroposterior diameter was not measured in this study. For evaluating the patellar size, each measured value was divided by IED and calculated each ratio. The ratio of patellar width to patellar thickness was also calculated. All parameters were compared between males and females. Statistical software Statview ver.5.0 (SAS Institute Inc.) was used for all analyses with significance being set at the 5% level. Results. Measured values are presented on Table 1. The average IED, patellar width and patellar thickness of males were all significantly larger than those of females. As shown in Table 2, by contrast, each ratio to IED was almost the same between the sexes and there were no significant differences. The ratio of patellar width to patellar thickness was 46.7±2.6% in males and 46.6±2.9% in females. Discussion. Although some studies have assessed the actual measurement values of patella, no prior study, to our knowledge, has morphologically evaluated the patella relative to the femur. This is the first study to investigate the configuration and location of patella relative to femoral epicondylar axis. Our results showed the configuration of patella relative to the femoral epicondylar axis was the same between sexes. The patellar width is approximately 56% and TGD is approximately 39% of IED. The most common complications after the surgery are related to patellofemoral problems. The ideal thickness of the resurfaced patella has not been clearly investigated. Patellar disabilities are associated with both decreased and increased patellar thickness— a thin patella could lead to anteroposterior patellar instability and a thick patella could increase the risk of stiffness of the knee and patellar subluxation. Therefore, it is desirable to restore the original patellar thickness during surgery. The results of current study showed that the ratio of patellar width to the patellar thickness was about 47%, which is useful to determine the thickness of patella during surgeries for severely damaged knees or revision surgeries

Shape memory staples have several uses in both hand and foot and ankle surgery. There is relatively little data available regarding the biomechanical properties of staples, in terms of both the compression achieved and potential decay of mechanical advantage with time. An understanding of these properties is therefore important for the surgeon. Two blocks of synthetic polyurethane mimicking properties of cancellous bone were fixed in jigs to both the actuator and 6 degree-of-freedom load cell of an MTS servohydraulic testing machine. With the displacement between the blocks held constant the peak value and subsequent decay in compressive force applied by both the smooth and barbed version of the nitinol OSStaple (Biomedical Enterprises), Easyclip (LMT), Herbert Bone Screws (Martin) and the Headless Compression Screw (Synthes) was measured. Nitinol staples were energised once only. A second experiment was conducted to assess the effects of repeated energisation on these parameters. The Easyclip staples achieved a mean peak force of 5.2N, whilst the smooth and barbed OSStaples achieved values of 9.3N and 5.7N, respectively. The Herbert screws achieved a mean peak force of 9N and the headless compression screws 23.9N. The mean peak force achieved with 2 Easyclip staples in parallel was 8.1N. Following the application of a single energisation the OSStaples exhibited a significant reduction in compressive load, losing up to approximately 70% of the peak value attained. The repeated energisation of these nitinol staples produced progressive increases in both peak and trough loads, the positive effects exhibited a plateau with time. Performance of both OSStaples was comparable to the Herbert screw with regard to reduction load applied across a simulated fracture plane. The maximum load applied by the OSStaples diminished with time. Staples provide fixation without violating the fracture plane which has the potential to offer some benefits from a healing perspective