Statistical shape modelling reveals large and distinct subchondral bony differences in osteoarthritic knees

Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models

PURPOSE

Statistical shape models (SSMs) are widely used for morphological assessment of anatomical structures. However, a key limitation is the need for a clear relationship between the model's shape coefficients and clinically relevant anatomical parameters. To address this limitation, this paper proposes a novel deep learning-based anatomically parameterized SSM (DL-ANATSSM) by introducing a nonlinear relationship between anatomical parameters and bone shape information.

METHODS

Our approach utilizes a multilayer perceptron model trained on a synthetic femoral bone population to learn the nonlinear mapping between anatomical measurements and shape parameters. The trained model is then fine-tuned on a real bone dataset. We compare the performance of DL-ANATSSM with a linear ANATSSM generated using least-squares regression for baseline evaluation.

RESULTS

When applied to a previously unseen femoral bone dataset, DL-ANATSSM demonstrated superior performance in predicting 3D bone shape based on anatomical parameters compared to the linear baseline model. The impact of fine-tuning was also investigated, with results indicating improved model performance after this process.

CONCLUSION

The proposed DL-ANATSSM is therefore a more precise and interpretable SSM, which is directly controlled by clinically relevant parameters. The proposed method holds promise for applications in both morphometry analysis and patient-specific 3D model generation without preoperative images.

Research on the analysis of morphological characteristics in pediatric femoral neck fractures utilizing 3D CT mapping

Proximal femoral fractures in children are challenging in clinical treatment due to their unique anatomical and biomechanical characteristics. The distribution and characteristics of fracture lines directly affect the selection of treatment options and prognosis. Pediatric proximal femur fractures exhibit distinctive features, with the distribution and characteristics of the fracture line playing a crucial role in deciding optimal treatment. The study aims to investigate the morphological characteristics of pediatric femoral neck fracture (FNF) from clinical cases by fracture mapping technology and to analyze the relationship between fracture classifications and age. The CT data were collected from 46 consecutive pediatric inpatients' diagnoses of FNF from March 2009 to December 2022. The fracture imaging was reconstructed in three dimensions and performed the simulated anatomical reduction by Mimics and 3-matic. Both Delbet classification and Pauwels angle classification were documented according to the fracture line in each patient. Furthermore, all of the fracture lines in these patients were superimposed to form a fracture map and a heat map. This study included 24 boys and 22 girls (average age, 9.61 ± 3.17 years (4 to 16 years)). The fracture lines of the anterior and superior femoral neck were found to be mainly located in the middle and lower regions of the femoral neck, while fracture lines of the posterior and inferior neck were mainly concentrated in the middle region. Most children younger than 10 years had Delbet type III of fracture (69%), whereas those older than 10 years had Delbet type II of fracture (73%). Furthermore, most children had Pauwels angle type III of fracture (63%), especially in those over 10 years old (80%) (p = 0.0001). FNF in children is predominantly located in the middle and lower regions of the neck. Older children may be prone to be affected with higher fracture location of FNF or unstable type of fracture.

Effect of morphology and cortical thickness variations on tibial strains in different movements

Morphology and cortical thickness of tibia bone influence the strength and strain distribution of bone and also influence fatigue fracture risk. However, current studies have not extensively explored the effect of morphology and cortical thickness on tibial strain distribution during different activities. This study aims to assess the effect of tibial morphology and cortical thickness on tibial strain during six different sports movements. The tibial surfaces were reconstructed from 40 males' CT data, with cortical thickness assessed at the outer surface. A statistical shape model captured main variations in tibial morphology and cortical thickness. Finite Element models were created by scaling the mean shape along the first four principal components. Muscle and joint forces from different activities were calculated using static optimization and joint reaction analysis and applied to the models, assessing strained volume and peak strain at middle and distal tibia. The first four principal components accounted for 87 % of the total cumulative variance. Perturbations in the second principal components resulted in the greatest relative differences in peak mid-tibia tensile (128 %) and distal-tibia compressive (160 %) strain during sidestep cutting, but perturbations in the first principal components resulted in the greatest relative differences during other activities (70 %∼118 %, 107 %∼129 %). Perturbations in the first four principal components resulted in the small relative differences in strained volume during walking (-9%∼5%). For runners, tibial size and cortical thickness are more related to tibial fatigue fracture risk, whereas for athletes with frequent directional changes, like basketball players, the tibial shaft size is more relevant.

Shape modelling reveals age-related knee bony shape changes in asymptomatic knees

Osteoarthritis (OA) causes bony shape changes within the knee. Furthermore, the risk of developing OA increases with age. However, age alone does not cause OA. It is therefore important to understand the healthy age-related trajectories of knee shape before attributing these changes to OA. The aim of this study was to determine the association between bony knee shape and age using statistical-shape modelling (SSM). 96 participants received a CT scan of their knee. Three-dimensional models were created using manual segmentation. Separate SSM's for the distal femur and proximal tibia were created. Linear regression models were used to assess the association between age and femoral and tibial shape. Fourteen modes of the femoral and tibial SSM's captured 68% and 73% shape variation, respectively. Only femoral mode 3 and tibial mode 7 were associated with age. Increasing age was related to larger femoral bone volume and deepening of the femoral trochlear groove. Furthermore, increased age was associated with medial tibial plateau expansion. Aspects of bony femoral and tibial shape were significantly associated with aging, including femoral and tibial bone size, femoral trochlear groove, and medial tibial plateau area. Changes in knee morphology occur as a normal process of aging without osteoarthritis development. This may be a response to mechanical loading over time. Further research investigating the effect of these changes on loading in the knee may provide valuable information for knee health in older age.

Sex differences in patellar facet shape among healthy and osteoarthritic cohorts

OBJECTIVE

Patellofemoral osteoarthritis (OA) may be more common in females than males. Reasons for this are not fully understood, but sex differences in patellar morphology may help explain this phenomenon. We quantified differences in patellar morphology between males and females in healthy and patellofemoral OA populations.

DESIGN

A total of 97 (50F, 47M) healthy and 67 (40F, 27M) OA knees were scanned via computed tomography. OA individuals were on a waitlist for total knee replacement. Patella 3D models were segmented and 2D measurements were recorded: patellar width and height, lateral and medial facet width, and surface area. Medial and lateral facet surface topography was mapped using 81 points to describe 3D articular surface shape. Sex and group differences were assessed using Procrustes analysis of variance (ANOVA). Data were ordinated using Principal Component Analysis.

RESULTS

Differences in patellar 2D measurements between healthy and OA individuals were smaller than were differences between males and females from healthy and OA groups. Sex and healthy/OA differences were most pronounced for medial facet shape, which featured a posteriorly-curving facet and taller, narrower facet shape in males compared to females. Lateral facet shape variance was higher in OA cohorts compared to healthy groups.

CONCLUSIONS

Medial and lateral facet shapes showed different patterning of variation by sex and healthy/OA status. Lateral facet shape may be of interest in future models of OA risk in the patellofemoral joint, here showing increased magnitudes of variance associated with increased severity of disease (patellofemoral Kellgren and Lawrence score).

Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement: Findings from a study of 37,843 people in UK Biobank

Objective

We aimed to create an imaging biomarker for knee shape using knee dual-energy x-ray absorptiometry (DXA) scans and investigate its potential association with subsequent total knee replacement (TKR), independently of radiographic features of knee osteoarthritis and established risk factors.

Methods

Using a 129-point statistical shape model, knee shape (expressed as a B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of images and an overall score was assigned. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with TKR risk, adjusting for age, sex, height and weight.

Results

The analysis included 37,843 individuals (mean age 63.7 years). In adjusted models, B-score was associated with TKR: each unit increase in B-score, reflecting one standard deviation from the mean healthy shape, corresponded to a hazard ratio (HR) of 2.25 (2.08, 2.43), while a lower mJSW had a HR of 2.28 (1.88, 2.77). Among the 6719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In ROC analyses, a model combining B-score, osteophyte score, and demographics outperformed a model including demographics alone (AUC ​= ​0.87 vs 0.73).

Conclusions

Using statistical shape modelling, we derived a DXA-based imaging biomarker for knee shape that was associated with kOA progression. When combined with osteophytes and demographic data, this biomarker may help identify individuals at high risk of TKR, facilitating targeted interventions.

Systematic review of computed tomography parameters used for the assessment of subchondral bone in osteoarthritis

OBJECTIVE

To systematically review the published parameters for the assessment of subchondral bone in human osteoarthritis (OA) using computed tomography (CT) and gain an overview of current practices and standards.

DESIGN

A literature search of Medline, Embase and Cochrane Library databases was performed with search strategies tailored to each database (search from 2010 to January 2023). The search results were screened independently by two reviewers against pre-determined inclusion and exclusion criteria. Studies were deemed eligible if conducted in vivo/ex vivo in human adults (>18 years) using any type of CT to assess subchondral bone in OA. Extracted data from eligible studies were compiled in a qualitative summary and formal narrative synthesis.

RESULTS

This analysis included 202 studies. Four groups of CT modalities were identified to have been used for subchondral bone assessment in OA across nine anatomical locations. Subchondral bone parameters measuring similar features of OA were combined in six categories: (i) microstructure, (ii) bone adaptation, (iii) gross morphology (iv) mineralisation, (v) joint space, and (vi) mechanical properties.

CONCLUSIONS

Clinically meaningful parameter categories were identified as well as categories with the potential to become relevant in the clinical field. Furthermore, we stress the importance of quantification of parameters to improve their sensitivity and reliability for the evaluation of OA disease progression and the need for standardised measurement methods to improve their clinical value.

HyM3D: A hybrid method for the automatic 3D reconstruction of a defective cranial vault

BACKGROUND AND OBJECTIVE

The ability to accomplish a consistent restoration of a missing or deformed anatomical area is a fundamental step for defining a custom implant, especially in the maxillofacial and cranial reconstruction where the aesthetical aspect is crucial for a successful surgical outcome. At the same time, this task is also the most difficult, time-consuming, and complicated across the whole reconstruction process. This is mostly due to the high geometric complexity of the anatomical structures, insufficient references, and significant interindividual anatomical heterogeneity. Numerous solutions, specifically for the neurocranium, have been put forward in the scientific literature to address the reconstruction issue, but none of them has yet been persuasive enough to guarantee an easily automatable approach with a consistent shape reconstruction.

METHODS

This work aims to present a novel reconstruction method (named HyM3D) for the automatic restoration of the exocranial surface by ensuring both the symmetry of the resulting skull and the continuity between the reconstructive patch and the surrounding bone. To achieve this goal, the strengths of the Template-based methods are exploited to provide knowledge of the missing or deformed region and to guide a subsequent Surface Interpolation-based algorithm. HyM3D is an improved version of a methodology presented by the authors in a previous publication for the restoration of unilateral defects. Differently from the first version, the novel procedure applies to all kinds of cranial defects, whether they are unilateral or not.

RESULTS

The presented method has been tested on several test cases, both synthetic and real, and the results show that it is reliable and trustworthy, providing a consistent outcome with no user intervention even when dealing with complex defects.

CONCLUSIONS

HyM3D method proved to be a valid alternative to the existing approaches for the digital reconstruction of a defective cranial vault; furthermore, with respect to the current alternatives, it demands less user interaction since the method is landmarks-independent and does not require any patch adaptation.

A Region-Based Statistical Shape Modeling on the First Trapezoid-Metacarpal

A statistical shape model (SSM) based analysis was conducted in our study. We indicated the morphological differences of the first trapezoid-metacarpal (TMC) bone between the region-based statistical shape model (rSSM) and the nonregion-based statistical shape model (nrSSM). We aimed to characterize more specific and accurate variation results to detect and prevent osteoarthritis in an early way. CT image data of TMC from 31 healthy volunteers were simulated with 3D models. A training set of models was analyzed with principal component analysis, with both then- rSSM and rSSM. The region was identified automatically with Gaussian curvature analysis. We found four dominant shape variations from both nrSSM and rSSM. The rSSM showed more variations with fewer components compared with nrSSM. The first principal component revealed the size variation as the biggest component. A significant difference was presented in the second and the fourth principal component from rSSM, showing the torsion of the distal head of the first metacarpal which may increase the risk of osteoarthritis.

Statistical modeling: Assessing the anatomic variability of knee joint space width

Population-based knee joint space width (JSW) assessments are promising for the prevention and early diagnosis of osteoarthritis. This study aimed to establish the statistical shape and alignment model (SSAM) of knee joints for assessing anatomic variation in knee JSW in the healthy Chinese male population. CT scans of asymptomatic knee joints of healthy male participants (n = 107) were collected for manual segmentation to create mesh samples. The as-scanned positional error was reduced by a standard processing flow of deformable mesh registration. Principal component analysis (PCA) was performed to create a tibiofemoral SSAM that was trained on all mesh samples. The anatomic variability of the JSW in the healthy Chinese male population was then assessed using the SSAM with regression analysis and 3D analysis by color-coded mapping. Almost all PCA modes had a linear influence on the anatomic variation of the medial and lateral JSW. The JSW variability within the SSAM was mainly explained by mode 1 (45.1 % of variation), demonstrating that this mode had the greatest influence on JSW variation. 3D assessment of the JSW showed that the minimum medial JSW varied from 2.76 to 3.23 mm, and its site shifted a short distance on the medial tibial plateau. The root-mean-square fitting and generalization errors of the SSAM were below 1 mm. This study will benefit the design and optimization of prosthetic devices, and may be applicable to the prevention and early diagnosis of osteoarthritis.

Shape modelling of the oropharynx distinguishes associations with body morphology but not whiplash-associated disorder

Characterization of the oropharynx, a subdivision of the pharynx between the soft palate and the epiglottis, is limited to simple measurements. Structural changes in the oropharynx in whiplash-associated disorder (WAD) cohorts have been quantified using two-dimensional (2D) and three-dimensional (3D) measures but the results are inconsistent. Statistical shape modelling (SSM) may be a more useful tool for systematically comparing morphometric features between cohorts. This technique has been used to quantify the variability in boney and soft tissue structures, but has not been used to examine a hollow cavity such as the oropharynx. The primary aim of this project was to examine the utility of SSM for comparing the oropharynx between WAD cohorts and control; and WAD severity cohorts. The secondary aim was to determine whether shape is associated with sex, height, weight and neck length. Magnetic resonance (MR) T1-weighted images were obtained from healthy control (n = 20), acute WAD (n = 14) and chronic WAD (n = 14) participants aged 18-39 years. Demographic, WAD severity (neck disability index) and body morphometry data were collected from each participant. Manual segmentation of the oropharynx was undertaken by blinded researchers between the top of the soft palate and tip of the epiglottis. Digital 3D oropharynx models were constructed from the segmented images and principal component (PC) analysis was performed with the PC weights normalized to z-scores for consistency. Statistical analyses were undertaken using multivariate linear models. In the first statistical model the independent variable was group (acute WAD, chronic WAD, control); and in the second model the independent variable was WAD severity (recovered/mild, moderate/severe). The covariates for both models included height, weight, average neck length and sex. Shape models were constructed to visualize the effect of perturbing these covariates for each relevant mode. The shape model revealed five modes which explained 90% of the variance: mode 1 explained 59% of the variance and primarily described differences in isometric size of the oropharynx, including elongation; mode 2 (13%) primarily described lateral (width) and AP (depth) dimensions; mode 3 (8%) described retroglossal AP dimension; mode 4 (6%) described lateral dimensions at the retropalatal-retroglossal junction and mode 5 (4%) described the lateral dimension at the inferior retroglossal region. There was no difference in shape (mode 1 p = 0.52; mode 2 p = 0.96; mode 3 p = 0.07; mode 4 p = 0.54; mode 5 p = 0.74) between control, acute WAD and chronic WAD groups. There were no statistical differences for any mode (mode 1 p = 0.12; mode 2 p = 0.29; mode 3 p = 0.56; mode 4 p = 0.99; mode 5 p = 0.96) between recovered/mild and moderate/severe WAD. Sex was not significant in any of the models but for mode 1 there was a significant association with height (p = 0.007), mode 2 neck length (p = 0.044) and in mode 3 weight (p = 0.027). Although SSM did not detect differences between WAD cohorts, it did detect associations with body morphology indicating that it may be a useful tool for examining differences in the oropharynx.

Cartilage thickness and bone shape variations as a function of sex, height, body mass, and age in young adult knees

The functional relationship between bone and cartilage is modulated by mechanical factors. Scarce data exist on the relationship between bone shape and the spatial distribution of cartilage thickness. The aim of the study was to characterise the coupled variation in knee bone morphology and cartilage thickness distributions in knees with healthy cartilage and investigate this relationship as a function of sex, height, body mass, and age. MR images of 51 knees from young adults (28.4 ± 4.1 years) were obtained from a previous study and used to train a statistical shape model of the femur, tibia, and patella and their cartilages. Five multiple linear regression models were fitted to characterise morphology as a function of sex, height, body mass, and age. A logistic regression classifier was fitted to characterise morphological differences between males and females, and tenfold cross-validation was performed to evaluate the models’ performance. Our results showed that cartilage thickness and its distribution were coupled to bone morphology. The first five shape modes captured over 90% of the variance and described coupled changes to the bone and spatial distribution of cartilage thickness. Mode 1 (size) was correlated to sex (p < 0.001) and height (p < 0.0001). Mode 2 (aspect ratio) was also correlated to sex (p = 0.006) and height (p = 0.017). Mode 4 (condylar depth) was correlated to sex only (p = 0.024). A logistic regression model trained on modes 1, 2, and 4 could classify sex with an accuracy of 92.2% (95% CI [81.1%, 97.8%]). No other modes were influenced by sex, height, body mass, or age. This study demonstrated the coupled relationship between bone and cartilage, showing that cartilage is thicker with increased bone size, diaphysis size, and decreased femoral skew. Our results show that sex and height influence bone shape and the spatial distribution of cartilage thickness in a healthy young adult population, but body mass and age do not.

Multiparametric 3-D analysis of bone and joint space width at the knee from weight bearing computed tomography

OBJECTIVE

Computed tomography (CT) can deliver multiple parameters relevant to osteoarthritis. In this study we demonstrate that a 3-D multiparametric approach at the weight bearing knee with cone beam CT is feasible, can include multiple parameters from across the joint space, and can reveal stronger relationships with disease status in combination.

DESIGN

33 participants with knee weight bearing CT (WBCT) were analysed with joint space mapping and cortical bone mapping to deliver joint space width (JSW), subchondral bone plate thickness, endocortical thickness, and trabecular attenuation at both sides of the joint. All data were co-localised to the same canonical surface. Statistical parametric mapping (SPM) was applied in uni- and multivariate models to demonstrate significant dependence of parameters on Kellgren & Lawrence grade (KLG). Correlation between JSW and bony parameters and 2-week test-retest repeatability were also calculated.

RESULTS

SPM revealed that the central-to-posterior medial tibiofemoral joint space was significantly narrowed by up to 0.5 mm with significantly higher tibial trabecular attenuation up to 50 units for each increment in KLG as single features, and in a wider distribution when combined (p<0.05). These were also more strongly correlated with worsening KLG grade category. Test-retest repeatability was subvoxel (0.37 mm) for nearly all thickness parameters.

CONCLUSIONS

3-D JSW and tibial trabecular attenuation are repeatable and significantly dependent on radiographic disease severity at the weight bearing knee joint not just alone, but more strongly in combination. A quantitative multiparametric approach with WBCT may have potential for more sensitive investigation of disease progression in osteoarthritis.

Anatomically Parameterized Statistical Shape Model: Explaining Morphometry through Statistical Learning

Objective: Statistical shape models (SSMs) are a popular tool to conduct morphological analysis of anatomical structures which is a crucial step in clinical practices. However, shape representations through SSMs are based on shape coefficients and lack an explicit one-to-one relationship with anatomical measures of clinical relevance. While a shape coefficient embeds a combination of anatomical measures, a formalized approach to find the relationship between them remains elusive in the literature. This limits the use of SSMs to subjective evaluations in clinical practices. We propose a novel SSM controlled by anatomical parameters derived from morphometric analysis. Methods: The proposed anatomically parameterized SSM (ANAT_SSM) is based on learning a linear mapping between shape coefficients (latent space) and selected anatomical parameters (anatomical space). This mapping is learned from a synthetic population generated by the standard SSM. Determining the pseudo-inverse of the mapping allows us to build the ANAT_SSM. We further impose orthogonality constraints to the anatomical parameterization (OC-ANAT_SSM) to obtain independent shape variation patterns. The proposed contribution was evaluated on two skeletal databases of femoral and scapular bone shapes using clinically relevant anatomical parameters within each (five for femoral and six for scapular bone). Results: Anatomical measures of the synthetically generated shapes exhibited realistic statistics. The learned matrices corroborated well with the obtained statistical relationship, while the two SSMs achieved moderate to excellent performance in predicting anatomical parameters on unseen shapes. Conclusion: This study demonstrates the use of anatomical representation for creating anatomically parameterized SSMs and as a result, removes the limited clinical interpretability of standard SSMs. Significance: The proposed models could help analyze differences in relevant bone morphometry between populations, and be integrated in patient-specific pre-surgery planning or in-surgery assessment.

Bone in osteoarthritis: imaging and interventions

PURPOSE OF REVIEW

To review the recent literature on bone in osteoarthritis (OA), with a focus on imaging and intervention studies.

RECENT FINDINGS

Most studies focused on knee OA; hip and hand studies were uncommon. Bone shape studies demonstrated that shape changes precede radiographic OA, predict joint replacement, and have demonstrated high responsiveness. Novel quantitative 3D imaging markers (B-score) have better characterized OA severity, including preradiographic OA status. The addition of computerized tomography-derived 3D metrics has improved the prediction of hip joint replacement when compared to radiographs alone.Recent studies of bisphosphonates for knee OA have reported no benefits on pain or bone marrow lesion (BML) size. A meta-analysis on Vitamin D supplementation in knee OA suggested minimal symptom improvement and no benefits on the structure. Cathepsin K inhibition demonstrated reduction in OA bone change progression, but with no symptom benefit. Studies of injections of bone substitutes into BMLs (subchondroplasty) have generally been small and potential benefits remain unclear.

SUMMARY

Subchondral bone features are associated with pain, incidence and progression of OA. Recent studies have validated quantitative bone shape as a biomarker for OA trials. Trials of bone-targeted OA therapies have been disappointing although cathepsin K inhibition may slow structural progression.

Landmark-free morphometric analysis of knee osteoarthritis using joint statistical models of bone shape and articular space variability

Purpose: Osteoarthritis (OA) is a common degenerative disease involving a variety of structural changes in the affected joint. In addition to narrowing of the articular space, recent studies involving statistical shape analysis methods have suggested that specific bone shapes might be associated with the disease. We aim to investigate the feasibility of using the recently introduced framework of functional shapes (Fshape) to extract morphological features of OA that combine shape variability of articular surfaces of the tibia (or femur) together with the changes of the joint space. Approach: Our study uses a dataset of three-dimensional cone-beam CT volumes of 17 knees without OA and 17 knees with OA. Each knee is then represented as an object (Fshape) consisting of a triangulated tibial (or femoral) articular surface and a map of joint space widths (JSWs) measured at the points of this surface (joint space map, JSM). We introduce a generative atlas model to estimate a template (mean) Fshape of the sample population together with template-centered variables that model the transformations from the template to each subject. This approach has two potential advantages compared with other statistical shape modeling methods that have been investigated in knee OA: (i) Fshapes simultaneously consider the variability in bone shape and JSW, and (ii) Fshape atlas estimation is based on a diffeomorphic transformation model of surfaces that does not require a priori landmark correspondences between the subjects. The estimated atlas-to-subject Fshape transformations were used as input to principal component analysis dimensionality reduction combined with a linear support vector machine (SVM) classifier to identify the morphological features of OA. Results: Using tibial articular surface as the shape component of the Fshape, we found leave-one-out cross validation scores of ≈ 91.18 % for the classification based on the bone surface transformations alone, ≈ 91.18 % for the classification based on the residual JSM, and ≈ 85.29 % for the classification using both Fshape components. Similar results were obtained using femoral articular surfaces. The discriminant directions identified in the statistical analysis were associated with medial narrowing of the joint space, steeper intercondylar eminence, and relative deepening of the medial tibial plateau. Conclusions: The proposed approach provides an integrated framework for combined statistical analysis of shape and JSPs. It can successfully extract features correlated to OA that appear consistent with previous studies in the field. Although future large-scale study is necessary to confirm the significance of these findings, our results suggest that the functional shape methodology is a promising new tool for morphological analysis of OA and orthopedics data in general.

Shape is only a weak predictor of deep knee flexion kinematics in healthy and osteoarthritic knees

Tibiofemoral shape influences knee kinematics but little is known about the effect of shape on deep knee flexion kinematics. The aim of this study was to examine the association between tibiofemoral joint shape and kinematics during deep kneeling in patients with and without osteoarthritis (OA). Sixty-one healthy participants and 58 patients with end-stage knee OA received a computed tomography (CT) of their knee. Participants completed full flexion kneeling while being imaged using single-plane fluoroscopy. Six-degree-of-freedom kinematics were measured by registering a three-dimensional (3D)-static CT onto 2D-dynamic fluoroscopic images. Statistical shape modeling and bivariate functional principal component analysis (bfPCA) were used to describe variability in knee shape and kinematics, respectively. Random-forest-regression models were created to test the ability of shape to predict kinematics controlling for body mass index, sex, and group. The first seven modes of the shape model up to three modes of the bfPCAs captured more than 90% of the variation. The ability of the random forest models to predict kinematics from shape was low, with no more than 50% of the variation being explained in any model. Furthermore, prediction errors were high, ranging between 24.2% and 29.4% of the data. Variations in the bony morphology of the tibiofemoral joint were weakly associated with the kinematics of deep knee flexion. The models only explained a small amount of variation in the data with high error rates indicating that additional predictors need to be identified. These results contribute to the clinical understanding of knee kinematics and potentially the expectations placed on high-flexion total knee replacement design.