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Statistical shape modeling of femur shape variability in female patients with hip dysplasia.

ABSTRACT: Although increasing evidence suggests that abnormal femur geometry in developmental dysplasia of the hip (DDH) may contribute to intra-articular damage and the development of hip osteoarthritis, a comprehensive 3D description of femoral abnormalities in DDH remains incomplete. Statistical shape modeling (SSM) was used to quantify three-dimensional (3D) geometric variation among femurs in female patients with DDH and control subjects. SSM correspondence points (n?=?8,192) were placed on each femur using a gradient descent energy function to derive mean DDH and control femoral shapes and principal component analysis (PCA) was then used to describe shape variation. PCA results were associated with common 2D radiographic measures of femur shape using general linear models. For patients with DDH, the first eight principal components (modes) captured 90.9% of the cumulative variance accounted for (VAF). Notably, mode 2 captured 23.6% VAF and described variation in femoral version, the neck-shaft angle, and femoral neck length, while mode 3 captured 16.4% VAF and described variation in femoral version, femoral head size, and femoral offset. SSM captured complex geometric deformities in DDH, which may not be fully described by 2D measures of the acetabulum and proximal femur alone. By determining the primary shape variations among femurs in cases of DDH, SSM may further understanding of pathologies on the femoral side of dysplastic hips, in context with more commonly recognized acetabular deformities. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

SUBMITTER: Gaffney BMM

PROVIDER: S-EPMC6613213 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Anatomical variations of the equine femur and tibia using statistical shape modeling.

Project description:The objective of this study was to provide an overarching description of the inter-subject variability of the equine femur and tibia morphology using statistical shape modeling. Fifteen femora and fourteen tibiae were used for building the femur and tibia statistical shape models, respectively. Geometric variations in each mode were explained by biometrics measured on ±3 standard deviation instances generated by the shape models. Approximately 95% of shape variations within the population were described by 6 and 3 modes in the femur and tibia shape models, respectively. In the femur shape model, the first mode of variation was scaling, followed by notable variation in the femoral mechanical-anatomical angle and femoral neck angle in mode 2. Orientation of the femoral trochlear tubercle and femoral version angle were described in mode 3 and mode 4, respectively. In the tibia shape model, the main mode of variation was also scaling. In mode 2 and mode 3, the angles of the coronal tibial plateau and the medial and lateral caudal tibial slope were described, showing the lateral caudal tibial slope angle being significantly larger than the medial. The presented femur and tibia shape models with quantified biometrics, such as femoral version angle and posterior tibial slope, could serve as a baseline for future investigations on correlation between the equine stifle morphology and joint disorders due to altered biomechanics, as well as facilitate the development of novel surgical treatment and implant design. By generating instances matching patient-specific femorotibial joint anatomy with radiographs, the shape model could assist virtual surgical planning and provide clinicians with opportunities to practice on 3D printed models.

| S-EPMC10313054 | biostudies-literature

Anatomical variations of the equine femur and tibia using statistical shape modeling

Project description: Not available

| S-BSST1116 | biostudies-other

Prediction of femoral head coverage from articulated statistical shape models of patients with developmental dysplasia of the hip.

Project description:Developmental dysplasia of the hip (DDH) is commonly described as reduced femoral head coverage due to anterolateral acetabular deficiency. Although reduced coverage is the defining trait of DDH, more subtle and localized anatomic features of the joint are also thought to contribute to symptom development and degeneration. These features are challenging to identify using conventional approaches. Herein, we assessed the morphology of the full femur and hemi-pelvis using an articulated statistical shape model (SSM). The model determined the morphological and pose-based variations associated with DDH in a population of Japanese females and established which of these variations predict coverage. Computed tomography (CT) images of 83 hips from 47 patients were segmented for input into a correspondence-based SSM. The dominant modes of variation in the model initially represented scale and pose. After removal of these factors through individual bone alignment, femoral version and neck-shaft angle, pelvic curvature, and acetabular version dominated the observed variation. Femoral head oblateness and prominence of the acetabular rim and various muscle attachment sites of the femur and hemi-pelvis were found to predict 3D CT-based coverage measurements (R2 = 0.5-0.7 for the full bones, R2 = 0.9 for the joint). Statement of Clinical Significance: Currently, clinical measurements of DDH only consider the morphology of the acetabulum. However, the results of this study demonstrated that variability in femoral head shape and several muscle attachment sites were predictive of femoral head coverage. These morphological differences may provide insight into improved clinical diagnosis and surgical planning based on functional adaptations of patients with DDH.

| S-EPMC9124729 | biostudies-literature

Improving the Hip Fracture Risk Prediction with a Statistical Shape-and-Intensity Model of the Proximal Femur.

Project description:Severe predictions have been made regarding osteoporotic fracture incidence for the next years, with major economic and social impacts in a worldwide greying society. However, the performance of the currently adopted gold standard for fracture risk prediction, the areal Bone Mineral Density (aBMD), remains moderate. To overcome current limitations, the construction of statistical models of the proximal femur, based on three-dimensional shape and intensity (a hallmark of bone density), is here proposed for predicting hip fracture in a Caucasian postmenopausal cohort. Partial Least Square (PLS)-based statistical models of the shape, intensity and their combination were developed, and the corresponding modes and components were identified. Logistic regression models using the first two shape, intensity and shape-intensity PLS components were implemented and tested within a 10-fold cross-validation procedure as predictors of hip fracture. It emerged that (1) intensity components were superior to shape components in stratifying patients according to their fracture status, and that (2) a combination of intensity and shape improved patients risk stratification. The area under the ROC curve was 0.64, 0.85 and 0.92 for the models based on shape, intensity and shape-intensity combination respectively, against a 0.72 value for the aBMD standard approach. Based on these findings, the presented methodology turns out to be promising in tackling the need for an enhanced fracture risk assessment.

| S-EPMC8803671 | biostudies-literature

Investigation of association between hip osteoarthritis susceptibility loci and radiographic proximal femur shape.

Project description:ObjectiveTo test whether previously reported hip morphology or osteoarthritis (OA) susceptibility loci are associated with proximal femur shape as represented by statistical shape model (SSM) modes and as univariate or multivariate quantitative traits.MethodsWe used pelvic radiographs and genotype data from 929 subjects with unilateral hip OA who had been recruited previously for the Arthritis Research UK Osteoarthritis Genetics Consortium genome-wide association study. We built 3 SSMs capturing the shape variation of the OA-unaffected proximal femur in the entire mixed-sex cohort and for male/female-stratified cohorts. We selected 41 candidate single-nucleotide polymorphisms (SNPs) previously reported as being associated with hip morphology (for replication analysis) or OA (for discovery analysis) and for which genotype data were available. We performed 2 types of analysis for genotype-phenotype associations between these SNPs and the modes of the SSMs: 1) a univariate analysis using individual SSM modes and 2) a multivariate analysis using combinations of SSM modes.ResultsThe univariate analysis identified association between rs4836732 (within the ASTN2 gene) and mode 5 of the female SSM (P = 0.0016) and between rs6976 (within the GLT8D1 gene) and mode 7 of the mixed-sex SSM (P = 0.0003). The multivariate analysis identified association between rs5009270 (near the IFRD1 gene) and a combination of modes 3, 4, and 9 of the mixed-sex SSM (P = 0.0004). Evidence of associations remained significant following adjustment for multiple testing. All 3 SNPs had previously been associated with hip OA.ConclusionThese de novo findings suggest that rs4836732, rs6976, and rs5009270 may contribute to hip OA susceptibility by altering proximal femur shape.

| S-EPMC4864451 | biostudies-literature

Comprehensive analysis of pathological changes in hip joint capsule of patients with developmental dysplasia of the hip

Project description:Aims: Developmental dysplasia of the hip (DDH) is a complex musculoskeletal disease that occurs mostly in children. This study aimed to investigate the molecular changes in the hip joint capsule of patients with DDH. Results: More than one thousand genes were differentially expressed in hip joint capsules between healthy controls and DDH. Both gene ontology (GO) and Kyoto encyclopedia of genes and genome (KEGG) analyses revealed that extracellular matrix (ECM) modifications, muscle system processes, and cell proliferation were markedly influenced by the differentially expressed genes. Conclusion: DDH is associated with the loss of collagen fibers and fibroblasts, which may cause loose joint capsule formation. However, the degree of differentiation of fibroblasts to myofibroblasts needs further studies.

2022-03-21 | GSE169494 | GEO

Labrador hip dysplasia GWAS

Project description:Genome wide association study on Labrador retrievers including hip dysplasia and body weight

| PRJEB70894 | ENA

Novel statistical methodology reveals that hip shape is associated with incident radiographic hip osteoarthritis among African American women.

Project description:IntroductionHip shape is a risk factor for the development of hip osteoarthritis (OA), and current methods to assess hip shape from radiographs are limited; therefore this study explored current and novel methods to assess hip shape.MethodsData from a prior case-control study nested in the Johnston County OA Project were used, including 382 hips (from 342 individuals). Hips were classified by radiographic hip OA (RHOA) status as RHOA cases (baseline Kellgren Lawrence grade [KLG] 0 or 1, follow-up [mean 6 years] KLG ≥ 2) or controls (KLG = 0 or 1 at both baseline and follow-up). Proximal femur shape was assessed using a 60-point model as previously described. The current analysis explored commonly used principal component analysis (PCA), as well as novel statistical methodologies suited to high dimension low sample size settings (Distance Weighted Discrimination [DWD] and Distance Projection Permutation [DiProPerm] hypothesis testing) to assess differences between cases and controls.ResultsUsing these novel methodologies, we were able to better characterize morphologic differences by sex and race. In particular, the proximal femurs of African American women demonstrated significantly different shapes between cases and controls, implying an important role for sex and race in the development of RHOA. Notably, discrimination was improved with the use of DWD and DiProPerm compared to PCA.ConclusionsDWD with DiProPerm significance testing provides improved discrimination of variation in hip morphology between groups, and enables subgroup analyses even under small sample sizes.

| S-EPMC4799754 | biostudies-literature

A Radiation-Free Classification Pipeline for Craniosynostosis Using Statistical Shape Modeling.

Project description:BackgroundCraniosynostosis is a condition caused by the premature fusion of skull sutures, leading to irregular growth patterns of the head. Three-dimensional photogrammetry is a radiation-free alternative to the diagnosis using computed tomography. While statistical shape models have been proposed to quantify head shape, no shape-model-based classification approach has been presented yet.MethodsWe present a classification pipeline that enables an automated diagnosis of three types of craniosynostosis. The pipeline is based on a statistical shape model built from photogrammetric surface scans. We made the model and pathology-specific submodels publicly available, making it the first publicly available craniosynostosis-related head model, as well as the first focusing on infants younger than 1.5 years. To the best of our knowledge, we performed the largest classification study for craniosynostosis to date.ResultsOur classification approach yields an accuracy of 97.8 %, comparable to other state-of-the-art methods using both computed tomography scans and stereophotogrammetry. Regarding the statistical shape model, we demonstrate that our model performs similar to other statistical shape models of the human head.ConclusionWe present a state-of-the-art shape-model-based classification approach for a radiation-free diagnosis of craniosynostosis. Our publicly available shape model enables the assessment of craniosynostosis on realistic and synthetic data.

| S-EPMC9323148 | biostudies-literature

Risk factors for fracture in patients with fibrous dysplasia of the proximal femur.

Project description:ObjectiveThe primary aim of this retrospective observational clinical study was to explore the risk factors for fracture in patients with fibrous dysplasia (FD) of the proximal femur.MethodsWe investigated body mass index, bilateral radiographs on both sides, femoral neck shaft angle measurements, and markers of bone metabolism in patients with FD of the proximal femur according to whether or not they had sustained a hip fracture. Nine clinical parameters (age, sex, clinical classification, anatomic classification, femoral neck shaft angle, and procollagen type 1 N-terminal propeptide, C-terminal telopeptide of type I collagen, and osteocalcin levels) were selected for univariate analysis. Factors that were significant in univariate analysis were then subjected to multivariate logistic analysis.ResultsClinical classification, anatomic classification, femoral neck shaft angle, and the osteocalcin level were identified to be statistically significant risk factors for fracture in univariate analysis. Anatomic classification, femoral neck shaft angle, and the osteocalcin level remained significant risk factors in multivariate analysis.ConclusionsAnatomic classification, femoral neck shaft angle, and the osteocalcin level are important risk factors for fracture in patients with FD of the proximal femur and could be used to guide implementation of a fracture prevention strategy in these patients.

| S-EPMC9743019 | biostudies-literature

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