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

Non-linear methods in statistical shape analysis have become increasingly important in orthopedic research as they allow for more accurate and robust analysis of complex shape data such as articulated joints, bony defects and cartilage loss. These methods involve the use of non-linear transformations to describe shapes, rather than the traditional linear approaches, and have been shown to improve the precision and sensitivity of shape analysis in a variety of applications. In orthopedic research, non-linear methods have been used to study a range of topics, including the analysis of bone shape and structure in relation to osteoarthritis, the assessment of joint deformities and their impact on joint function, and the prediction of patient outcomes following surgical interventions. Overall, the use of non-linear methods in statistical shape analysis has the potential to advance our understanding of the relationship between shape and function in the musculoskeletal system and improve the diagnosis and treatment of orthopedic conditions

Following anterior cruciate ligament reconstruction (ACLR) using a semitendinosus (ST) autograft measures such as length, cross-sectional area, and volume may not fully describe the effects of tendon harvest on muscle morphology as these discrete measures cannot characterize three-dimensional muscle shape. This study aimed to determine between-limb ST shape similarity and regional morphology in individuals with a unilateral history of ACLR using a ST graft, and healthy controls. A secondary analysis of magnetic resonance imaging was undertaken from 18 individuals with unilateral history of ST ACLR and 18 healthy controls. ST muscles were manually segmented, and shape similarity were assessed between limbs and groups using Jaccard index (0-1) and Hausdorff distance (mm). ST length (cm), peak cross-sectional area (CSA) (cm. 2. ), and volume (cm. 3. ) was compared between surgically reconstructed and uninjured contralateral limbs, and between the left and right limbs of control participants with no history of injury. Cohen's d was reported as a measure of effect size. Compared to healthy controls, the ACLR group had significantly (p<0.001, d= −2.33) lower bilateral ST shape similarity. Furthermore, the deviation in muscle shape was significantly (p<0.001, d= 2.12) greater in the ACLR group. Within the ACLR group, maximum Hausdorff distance indicated ST from the ACLR limb deviated (23.1±8.68 mm) from the shape of the healthy contralateral ST, this was observed particularly within the distal region of the muscle. Compared to the uninjured contralateral limb and healthy controls, deficits in peak cross-sectional area and volume in ACLR group were largest in proximal (p<0.001, d= −2.52 to −1.28) and middle (p<0.001, d= −1.81 to −1.04) regions. Findings highlight morphological features in distal ST not identified by traditional discrete morphology measures. ST shape was most different in the distal region of the muscle, despite deficits in CSA and volume being most pronounced in proximal and middle regions. ST shape following ACLR may affect force transmission and distribution within the hamstrings and contribute to persistent deficits in knee flexor and internal rotator strength

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

The anatomy of the femur shows a high inter-patient variability, making it challenging to design standard prosthetic devices that perfectly adapt to the geometry of each individual. Over the past decade, Statistical Shape Models (SSMs) have been largely used as a tool to represent an average shape of many three-dimensional objects, as well as their variation in shape. However, no studies of the morphology of the residual femoral canal in patients who have undergone an amputation have been performed. The aim of this study was therefore to evaluate the main modes of variation in the shape of the canal, therefore simulating and analysing different levels of osteotomy. To assess the variability of the femoral canal, 72 CT-scans of the lower limb were selected. A segmentation was performed to isolate the region of interest (ROI), ranging from the lesser tip of the trochanter to the 75% of the length of the femur. The canals were then sized to scale, aligned, and 16 osteotomy levels were simulated, starting from a section corresponding to 25% of the ROI and up to the distal section. For each level, the main modes of variations of the femoral canal were identified through Principal Component Analysis (PCA), thus generating the mean geometry and the extreme shapes (±2 stdev) of the principal modes of variation. The shape of the canals obtained from these geometries was reconstructed every 10 mm, best- fitted with an ellipse and the following parameters were evaluated: i) ellipticity, by looking at the difference between axismax and axismin; ii) curvature of the canal, calculating the arc of circumference passing through the shapes’ centroids; iii) conicity, by looking at the maximum/minimum diameter; iv) mean diameter. To understand the association between the main modes and the shape variance, these parameters were compared, for each level of osteotomy, between the two extreme geometries of the main modes of variation. Results from PCA pointed out that the first three PCs explained more than the 87% of the total variance, for each level of simulated osteotomy. By analysing the extreme geometries for a distal osteotomy (e.g. 80% of the length of the canal), the first PC was associated to a combination of ROC (var%=41%), conicity (var%=28%) and ellipticity (var%=7%). PC2 was still associated with the ROC (var%=16%), while PC3 turned out to be associated with the diameter (var%=38%). Through the SSM presented in this study, a quantitatively evaluation of the deformation of the intramedullary canal has been made possible. By analysing the extreme geometries obtained from the first three modes of variance, it is clear that the first three PCs accounted for the variations in terms of curvature, conicity, ellipticity and diameter of the femoral canal with a different weight, depending on the level of osteotomy. Through this work, it was also possible to parametrize these variations according to the level of excision. The results given for the segment corresponding to the 80% of the length of the canal showed that, at that specified level, the ROC, conicity and ellipticity were the anatomical parameters with the highest range of variability, followed by the variation in terms of diameter. Therefore, the analysis carried out can provide information about the relevance of these parameters depending on the level of osteotomy suffered by the amputee. In this way, optimal strategies for the design and/or customization of osteo-integrated stems can be offered depending on the patient's residual limb

Aims. In computer simulations, the shape of the range of motion (ROM) of a stem with a cylindrical neck design will be a perfect cone. However, many modern stems have rectangular/oval-shaped necks. We hypothesized that the rectangular/oval stem neck will affect the shape of the ROM and the prosthetic impingement. Methods. Total hip arthroplasty (THA) motion while standing and sitting was simulated using a MATLAB model (one stem with a cylindrical neck and one stem with a rectangular neck). The primary predictor was the geometry of the neck (cylindrical vs rectangular) and the main outcome was the shape of ROM based on the prosthetic impingement between the neck and the liner. The secondary outcome was the difference in the ROM provided by each neck geometry and the effect of the pelvic tilt on this ROM. Multiple regression was used to analyze the data. Results. The stem with a rectangular neck has increased internal and external rotation with a quatrefoil cross-section compared to a cone in a cylindrical neck. Modification of the cup orientation and pelvic tilt affected the direction of projection of the cone or quatrefoil shape. The mean increase in internal rotation with a rectangular neck was 3.4° (0° to 7.9°; p < 0.001); for external rotation, it was 2.8° (0.5° to 7.8°; p < 0.001). Conclusion. Our study shows the importance of attention to femoral implant design for the assessment of prosthetic impingement. Any universal mathematical model or computer simulation that ignores each stem’s unique neck geometry will provide inaccurate predictions of prosthetic impingement. Cite this article: Bone Joint Res 2021;10(12):780–789

Aims. This study aimed to evaluate the relationship between hip shape and mid-term function in Perthes’ disease. It also explored whether the modified three-group Stulberg classification can offer similar prognostic information to the five-group system. Methods. A total of 136 individuals aged 12 years or older who had Perthes’ disease in childhood completed the Patient-Reported Outcomes Measurement Information System (PROMIS) Mobility score (function), Nonarthritic Hip Score (NAHS) (function), EuroQol five-dimension five-level questionnaire (EQ-5D-5L) score (quality of life), and the numeric rating scale for pain (NRS). The Stulberg class of the participants’ hip radiographs were evaluated by three fellowship-trained paediatric orthopaedic surgeons. Hip shape and Stulberg class were compared to PROM scores. Results. A spherical hip was associated with the highest function and quality of life, and lowest pain. Conversely, aspherical hips exhibited the lowest functional scores and highest pain. The association between worsening Stulberg class (i.e. greater deviation from sphericity) and worse outcome persisted after adjustment for age and sex in relation to PROMIS (predicted mean difference -1.77 (95% confidence interval (CI) -2.70 to -0.83)), NAHS (-5.68 (95% CI -8.45 to -2.90)), and NRS (0.61 (95% CI 0.14 to 1.08)), but not EQ-5D-5L (-0.03 (95% CI -0.72 to 0.11)). Conclusion. Patient-reported outcomes identify lower function, quality of life, and higher pain in aspherical hips. The magnitude of symptoms deteriorated with time. Hip sphericity (i.e. the modified three-group classification of spherical, oval, and aspherical) appeared to offer similar levels of detail to the five-group Stulberg classification. Cite this article: Bone Joint J 2023;105-B(6):711–716

For many years, marker-based systems have been used for motion analysis. However, the emergence of new technologies, such as 4D scanners provide exciting new opportunities for motion analysis. In 4D scanners, the subjects are measured as a dense mesh, which enables the use of shape analysis techniques. In this talk, we will explore how the combination of the rising new motion analysis methods and shape modelling may change the way we think about movement and its analysis

Abstract. Introduction. OtisMed Shape Match ® patient specific implant cutting jigs were designed to place TKA in kinematic alignment (KA) rather than traditional mechanical alignment (MA). This product was withdrawn from the market in 2013. It has been hypothesised that KA might lead to early implant failure. Initial evidence has not supported this. We present 10 year outcome data for the largest single centre cohort to date. Methodology. Between 2010 and 2013, 127 Shape Match® TKAs were implanted in 119 individuals. Retrospective review of long leg post-operative radiographs assessed femoral mechanical anatomical angle (FMA), tibial mechanical angle (TMA), hip-knee-ankle angle (HKA), posterior tibial slope (PTS) and femoral component flexion. Oxford Knee Scores (OKS), revision and further surgery rates were reviewed. Results. 4 (3.1%) patients underwent revision for instability, recurrent haemarthrosis, stiffness and infection respectively. In this subgroup, PTS ranged from 9–25° (SD 7.5°). PTS range for non-revision subgroup was 1–23° (SD 4.6). 1 patient with a PTS of 21° had failure of quadriceps tendon, but was not revised. Mean OKS at 1year = 38.1 (SD 1.08), 2 years = 39.3 (SD 1.08), 5 years = 40.8 (SD 4.11). PTS had the largest impact on OKS, with <10° slope conferring a higher OKS. Conclusions. At 10 year follow up, this cohort did identify several cases where excessive PTS was evident. This may have led to revision surgery and contributed post-operative complications. PTS, unlike other alignment measures, impacted OKS results. Overall revision rate and OKS were consistent with registry and other published data

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

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

Abstract. Objectives. The objective of this study is to investigate the effect of solvents and rheological properties of PCL/Hydroxyapatite ink on the shape fidelity of the 3D printed scaffolds for bone tissue engineering. Methods. A series of inks were made consisting of 50% (w/v) of polycaprolactone (PCL) filled with 0%, 3.5% and 12.5% (w/V) of hydroxyapatite (HA) in dichloromethane (DCM) and chloroform (CHF). Steady and oscillatory shear rheological tests were performed on a rheometer (Discovery HR-3). Solvent-cast direct ink writing was performed with a custom-made 3D printer for the fabrication of PCL/HA scaffold structures with 2–8 layers. Optical microscope and scanning electron microscopy (SEM) were used to assess the shape fidelity. Results. Shape fidelity of the inks was quantitively assessed on the 3D printed scaffold structures allowing subjective comparisons. The addition of HA particles increased zero-shear viscosity by up to 900%. For oscillatory tests, plateau of storage modulus was observed in the low-frequency region which is attributed to good dispersion of the HA particles inside the matrix that leads to the formation of filler networks, resulting in pseudo-solid behavior and shape fidelity improvement. As the HA concentration increases, the plateau becomes more pronounced and the shape fidelity increases. With the same concentration, all DCM inks also show higher viscosity (from 10% to 200%) and better shape fidelity than CHF inks. As DCM has a lower boiling point (39.6 °C) than CHF (61.2°C), DCM evaporates quicker reducing the fusion and diffusion of deposited ink filaments before solidification which is observed in SEM images. Conclusions. This study reveals insights into using rheological characterizations as a tool for evaluation of shape fidelity of solvent-based DIW inks and also provides fundamental information on the influence of different solvents on the fidelity of 3D printed scaffolds. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

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

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

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

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

Purpose and Background. Both overall spine shape and the size and shape of individual vertebrae undergo rapid growth and development during early childhood. Motor development milestones such as age of walking influence spine development, with delayed ambulation linked with spinal conditions including spondylolysis. However, it is unclear whether associations between motor development and spine morphology persist into older age. Therefore, these associations were examined using data from the MRC National Survey of Health and Development, a large nationally-representative British cohort, followed up since birth in 1946. Methods and Results. Statistical shape modelling was used to characterise spinal shape (L5-T10) and identify modes of variation in shape (SM) from dual energy x-ray absorptiometry images of the spine taken at age 60–64 years (N=1327 individuals; 51.8% female). Associations between walking age in months (reported by mothers at 2 years) and SMs were examined with adjustment for sex, birthweight, socioeconomic position, height, lean mass and fat mass. Later onset of independent walking was weakly associated with greater lordosis (SM1; P=0.05) and more uniform antero-posterior vertebral size along the spine (SM6, P=0.07). Later walking age was also associated with smaller relative anterior-posterior vertebral dimensions (SM3) among women whereas the opposite was found for men (P <0.01 for sex interaction). Conclusions. Spinal morphology in early old age was associated with the age that individuals began walking independently in childhood, potentially due to altered mechanical loading. This suggests that motor development may have a persisting effect on clinically-relevant features of spine morphology throughout life. Conflict of interest: None. Funded by the UK Medical Research Council (Grant MR/L010399/1) which supported FRS, SGM and AVP