A method for assessment of the shape of the proximal femur and its relationship to osteoporotic hip fracture

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.

DXA-based statistical models of shape and intensity outperform aBMD hip fracture prediction: A retrospective study

Areal bone mineral density (aBMD) currently represents the clinical gold standard for hip fracture risk assessment. Nevertheless, it is characterised by a limited prediction accuracy, as about half of the people experiencing a fracture are not classified as at being at risk by aBMD. In the context of a progressively ageing population, the identification of accurate predictive tools would be pivotal to implement preventive actions. In this study, DXA-based statistical models of the proximal femur shape, intensity (i.e., density) and their combination were developed and employed to predict hip fracture on a retrospective cohort of post-menopausal women. Proximal femur shape and pixel-by-pixel aBMD values were extracted from DXA images and partial least square (PLS) algorithm adopted to extract corresponding modes and components. Subsequently, logistic regression models were built employing the first three shape, intensity and shape-intensity PLS components, and their ability to predict hip fracture tested according to a 10-fold cross-validation procedure. The area under the ROC curves (AUC) for the shape, intensity, and shape-intensity-based predictive models were 0.59 (95%CI 0.47-0.69), 0.80 (95%CI 0.70-0.90) and 0.83 (95%CI 0.73-0.90), with the first being significantly lower than the latter two. aBMD yielded an AUC of 0.72 (95%CI 0.59-0.82), found to be significantly lower than the shape-intensity-based predictive model. In conclusion, a methodology to assess hip fracture risk uniquely based on the clinically available imaging technique, DXA, is proposed. Our study results show that hip fracture risk prediction could be enhanced by taking advantage of the full set of information DXA contains.

Development of Local Software for Automatic Measurement of Geometric Parameters in the Proximal Femur Using a Combination of a Deep Learning Approach and an Active Shape Model on X-ray Images

Proximal femur geometry is an important risk factor for diagnosing and predicting hip and femur injuries. Hence, the development of an automated approach for measuring these parameters could help physicians with the early identification of hip and femur ailments. This paper presents a technique that combines the active shape model (ASM) and deep learning methodologies. First, the femur boundary is extracted by a deep learning neural network. Then, the femur's anatomical landmarks are fitted to the extracted border using the ASM method. Finally, the geometric parameters of the proximal femur, including femur neck axis length (FNAL), femur head diameter (FHD), femur neck width (FNW), shaft width (SW), neck shaft angle (NSA), and alpha angle (AA), are calculated by measuring the distances and angles between the landmarks. The dataset of hip radiographic images consisted of 428 images, with 208 men and 220 women. These images were split into training and testing sets for analysis. The deep learning network and ASM were subsequently trained on the training dataset. In the testing dataset, the automatic measurement of FNAL, FHD, FNW, SW, NSA, and AA parameters resulted in mean errors of 1.19%, 1.46%, 2.28%, 2.43%, 1.95%, and 4.53%, respectively.

Evolutionary roots of the risk of hip fracture in humans

The transition to bipedal locomotion was a fundamental milestone in human evolution. Consequently, the human skeleton underwent substantial morphological adaptations. These adaptations are responsible for many of today's common physical impairments, including hip fractures. This study aims to reveal the morphological changes in the proximal femur, which increase the risk of intracapsular hip fractures in present-day populations. Our sample includes chimpanzees, early hominins, early Homo Neanderthals, as well as prehistoric and recent humans. Using Geometric Morphometric methods, we demonstrate differences in the proximal femur shape between hominids and populations that practiced different lifestyles. We show that the proximal femur morphology is a risk factor for intracapsular hip fracture independent of osteoporosis. Changes in the proximal femur, such as the shortening of the femoral neck and an increased anterolateral expansion of the greater trochanter, are associated with an increased risk for intracapsular hip fractures. We conclude that intracapsular hip fractures are a trade-off for efficient bipedal walking in humans, and their risk is exacerbated by reduced physical activity.

Application of statistical shape modeling to the human hip joint: a scoping review

OBJECTIVE

The objective of this scoping review was to identify all examples of the application of statistical shape models to the human hip joint, with a focus on applications, population, methodology, and validation.

INTRODUCTION

Clinical radiographs are the most common imaging tool for management of hip conditions, but it is unclear whether radiographs can adequately diagnose or predict outcomes of 3D deformity. Statistical shape modeling, a method of describing the variation of a population of shapes using a small number of variables, has been identified as a useful tool to associate 2D images with 3D anatomy. This could allow clinicians and researchers to validate clinical radiographic measures of hip deformity, develop new ones, or predict 3D morphology directly from radiographs. In identifying all previous examples of statistical shape modeling applied to the human hip joint, this review determined the prevalence, strengths, and weaknesses, and identified gaps in the literature.

INCLUSION CRITERIA

Participants included any human population. The concept included development or application of statistical shape models based on discrete landmarks and principal component analysis. The context included sources that exclusively modeled the hip joint. Only peer-reviewed original research journal articles were eligible for inclusion.

METHODS

We searched MEDLINE, Embase, Cochrane CENTRAL, IEEE Xplore, Web of Science Core Collection, OCLC PapersFirst, OCLC Proceedings, Networked Digital Library of Theses and Dissertations, ProQuest Dissertations and Theses Global, and Google Scholar for sources published in English between 1992 and 2021. Two reviewers screened sources against the inclusion criteria independently and in duplicate. Data were extracted by 2 reviewers using a REDCap form designed to answer the review study questions, and are presented in narrative, tabular, and graphical form.

RESULTS

A total of 104 sources were considered eligible based on the inclusion criteria. From these, 122 unique statistical shape models of the human hip were identified based on 86 unique training populations. Models were most often applied as one-off research tools to describe shape in certain populations or to predict outcomes. The demographics of training populations were skewed toward older patients in high-income countries. A mean age between 60 and 79 years was reported in 29 training populations (34%), more than reported in all other age groups combined, and 73 training populations (85%) were reported or inferred to be from Europe and the Americas. Only 4 studies created models in a pediatric population, although 15 articles considered shape variation over time in some way. There were approximately equal numbers of 2D and 3D models. A variety of methods for labeling the training set was observed. Most articles presented some form of validation such as reporting a model's compactness (n = 71), but in-depth validation was rare.

CONCLUSIONS

Despite the high volume of literature concerning statistical shape models of the human hip, there remains a need for further research in key areas. We identified the lack of models in pediatric populations and low- and middle-income countries as a notable limitation to be addressed in future research.

Machine Learning-Derived Acetabular Dysplasia and Cam Morphology Are Features of Severe Hip Osteoarthritis: Findings From UK Biobank

The contribution of shape changes to hip osteoarthritis (HOA) remains unclear, as is the extent to which these vary according to HOA severity. In the present study, we used statistical shape modeling (SSM) to evaluate relationships between hip shape and HOA of different severities using UK Biobank DXA images. We performed a cross-sectional study in individuals with left hip dual-energy X-ray absorptiometry (DXA) scans. Statistical shape modeling (SSM) was used to quantify hip shape. Radiographic HOA (rHOA) was classified using osteophyte size and number and joint space narrowing. HOA outcomes ranged in severity from moderate (grade 2) to severe (grade ≥3) rHOA, hospital-diagnosed HOA, and subsequent total hip replacement (THR). Confounder-adjusted logistic regression between the top 10 hip shape modes (HSMs) and OA outcomes was performed. Further models adjusted for alpha angle (AA) and lateral center-edge angle (LCEA), reflecting acetabular dysplasia and cam morphology, respectively. Composite HSM figures were produced combining HSMs associated with separate OA outcomes. A total of 40,311 individuals were included (mean 63.7 years, 47.8% male), of whom 5.7% had grade 2 rHOA, 1.7% grade ≥3 rHOA, 1.3% hospital-diagnosed HOA, and 0.6% underwent THR. Composite HSM figures for grade 2 rHOA revealed femoral neck widening, increased acetabular coverage, and enlarged lesser and greater trochanters. In contrast, grade ≥3 rHOA, hospital-diagnosed HOA, and THR were suggestive of cam morphology and reduced acetabular coverage. Associations between HSMs depicting cam morphology and reduced acetabular coverage and more severe HOA were attenuated by AA and LCEA adjustment, respectively. Relationships between hip shape and HOA differed according to severity. Notably, cam morphology and acetabular dysplasia were features of severe HOA, but unrelated to moderate disease, suggesting possible prognostic utility. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

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

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.

Finite element analysis informed variable selection for femoral fracture risk prediction

Logistic regression classification (LRC) is widely used to develop models to predict the risk of femoral fracture. LRC models based on areal bone mineral density (aBMD) alone are poor, with area under the receiver operator curve (AUROC) scores reported to be as low as 0.63. This has led to researchers investigating methods to extract further information from the image to increase performance. Recently, the use of active shape (ASM) and appearance models (AAM) have resulted in moderate improvements, but there is a risk that inclusion of too many modes will lead to overfitting. In addition, there are concerns that the effort required to extract the additional information does not justify the modest improvement in fracture risk prediction. This raises the question, are we reaching the limits of the information that can be extracted from an image? Finite element analysis was used in combination with active shape and appearance modelling to select variables to develop LRC models of fracture risk. Active shape and active appearance models were constructed based on a previously reported cohort of 94 post-menopausal Caucasian women (47 with and 47 without a fracture). T-tests were used to identify differences between the two groups for each mode of variation. Femur strength was predicted for two load cases, stance and a fall. Stepwise multi-variate linear regression was used to identify shape and appearance modes that were predictors of strength for the femurs in the training set. Femurs were also synthetically generated to explore the influence of the first 10 modes of the shape and appearance models. Identified modes of variation were then used to generate LRC models to predict fracture risk. Only 6 modes, 4 active appearance and 2 active shape modes, were identified that had a significant influence on predicted fracture strength. Of these, only two active appearance modes were needed to substantially improve the predictive mode performance (ΔAUROC = 0.080). The addition of 3 more modes (1 AAM and two ASM) further improved the performance of the classifier (ΔAUROC = 0.123). Further addition of modes did not result in any further substantial improvements. Based on these findings, it is suggested that we are reaching the limits of the information that can be extracted from an image to predict fracture risk.

The influence of adult hip shape genetic variants on adolescent hip shape: Findings from a population-based DXA study

OBJECTIVE

Hip shape is a well-recognized risk factor for hip osteoarthritis (OA) and hip fracture. We aimed to investigate whether the genetic variants known to be associated with adult hip shape were also associated with adolescent hip shape.

METHODS

Hip DXA scans, obtained in offspring from the Avon Longitudinal Study of Parents and Children (ALSPAC) at two time points (mean ages 13.8 and 17.8 years), were used to quantify hip morphology using a 53-point Statistical Shape Model (SSM). Principal component analysis was used to generate hip shape modes (HSMs). Genetic variants which had previously shown genome-wide significant association with specific HSMs in adults were tested for association with the same HSMs in adolescents (at each timepoint separately) using SNPTEST v2.

RESULTS

Complete genotypic and phenotypic data were available for 3550 and 3175 individuals at 14 and 18 years, respectively. The strongest evidence for association with adolescent hip shape was for a variant located near SOX9 (rs2158915) with consistent effects across both time points for HSM1 (age 14: beta -0.05, p = 9.9 × 10-8; age 18: -0.05, p = 3.3 × 10-6) and HSM5 (age 14: beta -0.07, p = 1.6 × 10-4; age 18: -0.1, p = 2.7 × 10-6). There was also strong evidence of association between rs10743612 (near PTHLH) and HSM1 (age 14: 0.05, p = 1.1 × 10-5; age 18: 0.04, p = 0.003) and between rs6537291 (near HHIP) and HSM2 (age 14: -0.06, p = 0.001; age 18: -0.07, p = 0.001) across both time points. The genes with the strongest associations with hip shape in adolescents, (SOX9, PTHLH and HHIP) are known to be involved in endochondral bone formation. HSM1 indicates narrower aspect ratio of the upper femur, whereas both HSM2 and HSM5 reflect variation in the femoral head size and femoral neck width, features previously found to be related to the risk of OA in later life. The SOX9 locus has previously been found to associate with increased risk of hip fracture.

CONCLUSION

In conclusion, variants implicated in endochondral bone formation appear to consistently influence hip shape between adolescence and adulthood, including those aspects related to risk of hip OA and/or fracture in later life.

Combining shape and intensity dxa-based statistical approaches for osteoporotic HIP fracture risk assessment

Aiming to improve osteoporotic hip fracture risk detection, factors other than the largely adopted Bone Mineral Density (BMD) have been investigated as potential risk predictors. In particular Hip Structural Analysis (HSA)-derived parameters accounting for femur geometry, extracted from Dual-energy X-ray Absorptiometry (DXA) images, have been largely considered as geometric risk factors. However, HSA-derived parameters represent discrete and cross-correlated quantities, unable to describe proximal femur geometry as a whole and tightly related to BMD. Focusing on a post-menopausal cohort (N = 28), in this study statistical models of bone shape and BMD distribution have been developed to investigate their possible role in fracture risk. Due to unavailable retrospective patient-specific fracture risk information, here a surrogate fracture risk based on 3D computer simulations has been employed for the statistical framework construction. When considered separately, BMD distribution performed better than shape in explaining the surrogate fracture risk variability for the analysed cohort. However, the combination of BMD and femur shape quantities in a unique statistical model yielded better results. In detail, the first shape-intensity combined mode identified using a Partial Least Square (PLS) algorithm was able to explain 70% of the surrogate fracture risk variability, thus suggesting that a more effective patients stratification can be obtained applying a shape-intensity combination approach, compared to T-score. The findings of this study strongly advocate future research on the role of a combined shape-BMD statistical framework in fracture risk determination.

Sex differences in proximal femur shape: findings from a population-based study in adolescents

Hip shape is an important determinant of hip osteoarthritis (OA), which occurs more commonly in women. However, it remains unclear to what extent differences in OA prevalence are attributed to sex differences in hip shape. Here, we explore sex differences in proximal femur shape in a cohort of adolescents. Hip morphology was quantified using hip DXA scans from the Avon Longitudinal Study of Parents and Children. Independent modes of variation (hip shape mode (HSM) scores) were generated for each image using an adult reference statistical shape model (N = 19,379). Linear regression was used to examine sex differences for the top ten HSMs, adjusting for age, height, lean and fat mass. Complete outcome and covariate data were available for 4,428 and 4,369 participants at ages 14 and 18 years, respectively. Several HSMs showed sex differences at both time points. The combined effect of sex on hip shape at age 14 reflected flatter femoral head and smaller lesser trochanter in females compared with males and, following adjustment for age and body size, these differences became more pronounced. At age 18, smaller lesser trochanter and femoral neck width (FNW) in females still remained although differences in femoral head, femoral shaft and FNW were largely attenuated following adjustment. Sexual dimorphism in proximal femur shape can be discerned in adolescence and early adulthood. Observed differences in proximal femur shape, particularly at age 14 were largely independent of body size, however to what extent differences in hip shape in early life play a role in predisposing to hip OA in later life remains to be determined.

Unpicking observational relationships between hip shape and osteoarthritis: hype or hope?

PURPOSE OF REVIEW

To review recent findings concerning the observational relationship between hip shape and hip osteoarthritis (HOA) and their shared genetic influences, and the potential for clinical application.

RECENT FINDINGS

Recent observational studies have strengthened the evidence that specific shape deformities, such as cam and acetabular dysplasia, are related to HOA. Statistical shape modelling has emerged as a method to measure hip shape holistically, with the added advantage that this can be applied to dual X-ray absorptiometry scan images. This has led to several additional aspects of hip shape variation being identified, such as a wider femoral neck and larger lesser trochanter, in association with HOA. Furthermore, this method has formed the basis of genetic studies identifying novel genetic influences on hip shape, several of which are shared with known genetic risk factors for HOA.

SUMMARY

Shared genetic influences of hip shape and HOA raise the possibility that hip shape plays a casual role in the development of HOA, justifying preventive approaches aiming to combat these adverse consequences.

Describing the application of statistical shape modelling to DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children

Bones are complex objects with considerable variation in the shape and structure often attributed to anatomical, environmental or genetic differences. In addition, bone shape has been of interest in relation to its associations with disease processes. Hip shape is an important determinant of hip osteoarthritis and osteoporotic hip fracture; however, its quantification is difficult. While previous studies largely focused on individual geometrical indices of hip geometry such as neck-shaft angle or femoral neck width, statistical shape modelling offers the means to quantify the entire contour of the proximal femur, including lesser trochanter and acetabular eyebrow. We describe the derivation of independent modes of variation (hip shape mode scores) to characterise variation in hip shape from dual-energy X-ray absorptiometry (DXA) images in the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using statistical shape modelling. ALSPAC is a rich source of phenotypic and genotypic data which provides a unique opportunity to investigate the environmental and genetic influences on hip shape in adolescence, as well as comparison with adult hip shape.

Hip Fracture Discrimination Based on Statistical Multi-parametric Modeling (SMPM)

Studies using quantitative computed tomography (QCT) and data-driven image analysis techniques have shown that trabecular and cortical volumetric bone mineral density (vBMD) can improve the hip fracture prediction of dual-energy X-ray absorptiometry areal BMD (aBMD). Here, we hypothesize that (1) QCT imaging features of shape, density and structure derived from data-driven image analysis techniques can improve the hip fracture discrimination of classification models based on mean femoral neck aBMD (Neck.aBMD), and (2) that data-driven cortical bone thickness (Ct.Th) features can improve the hip fracture discrimination of vBMD models. We tested our hypotheses using statistical multi-parametric modeling (SMPM) in a QCT study of acute hip fracture of 50 controls and 93 fragility fracture cases. SMPM was used to extract features of shape, vBMD, Ct.Th, cortical vBMD, and vBMD in a layer adjacent to the endosteal surface to develop hip fracture classification models with machine learning logistic LASSO. The performance of these classification models was evaluated in two aspects: (1) their hip fracture classification capability without Neck.aBMD, and (2) their capability to improve the hip fracture classification of the Neck.aBMD model. Assessments were done with 10-fold cross-validation, areas under the receiver operating characteristic curve (AUCs), differences of AUCs, and the integrated discrimination improvement (IDI) index. All LASSO models including SMPM-vBMD features, and the majority of models including SMPM-Ct.Th features performed significantly better than the Neck.aBMD model; and all SMPM features significantly improved the hip fracture discrimination of the Neck.aBMD model (Hypothesis 1). An interesting finding was that SMPM-features of vBMD also captured Ct.Th patterns, potentially explaining the superior classification performance of models based on SMPM-vBMD features (Hypothesis 2). Age, height and weight had a small impact on model performances, and the model of shape, vBMD and Ct.Th consistently yielded better performances than the Neck.aBMD models. Results of this study clearly support the relevance of bone density and quality on the assessment of hip fracture, and demonstrate their potential on patient and healthcare cost benefits.

Age at Onset of Walking in Infancy Is Associated With Hip Shape in Early Old Age

Bones' shapes and structures adapt to the muscle and reaction forces they experience during everyday movements. Onset of independent walking, at approximately 12 months, represents the first postnatal exposure of the lower limbs to the large forces associated with bipedal movements; accordingly, earlier walking is associated with greater bone strength. However, associations between early life loading and joint shape have not been explored. We therefore examined associations between walking age and hip shape at age 60 to 64 years in 1423 individuals (740 women) from the MRC National Survey of Health and Development, a nationally representative British birth cohort. Walking age in months was obtained from maternal interview at age 2 years. Ten modes of variation in hip shape (HM1 to HM10), described by statistical shape models, were ascertained from DXA images. In sex-adjusted analyses, earlier walking age was associated with higher HM1 and HM7 scores; these associations were maintained after further adjustment for height, body composition, and socioeconomic position. Earlier walking was also associated with lower HM2 scores in women only, and lower HM4 scores in men only. Taken together, this suggests that earlier walkers have proportionately larger (HM4) and flatter (HM1, HM4) femoral heads, wider (HM1, HM4, HM7) and flatter (HM1, HM7) femoral necks, a smaller neck-shaft angle (HM1, HM4), anteversion (HM2, HM7), and early development of osteophytes (HM1). These results suggest that age at onset of walking in infancy is associated with variations in hip shape in older age. Early walkers have a larger femoral head and neck and smaller neck-shaft angle; these features are associated with reduced hip fracture risk, but also represent an osteoarthritic-like phenotype. Unlike results of previous studies of walking age and bone mass, associations in this study were not affected by adjustment for lean mass, suggesting that associations may relate directly to skeletal loading in early life when joint shape changes rapidly. © 2018 American Society for Bone and Mineral Research.

Using statistical shape modelling of DXA images to quantify the shape of the proximal femur at ages 14 and 18 years in the Avon Longitudinal Study of Parents and Children

Hip shape is an important determinant of hip osteoarthritis and osteoporotic hip fracture; however, little is known about its development in childhood and adolescence. While previous studies largely focused on individual geometrical indices of hip geometry such as neck-shaft angle or femoral neck width, statistical shape modelling offers the means to quantify the entire contour of the proximal femur, including lesser trochanter and acetabular eyebrow. We describe the derivation of independent modes of variation (hip shape mode scores) to characterise variation in hip shape from dual-energy X-ray absorptiometry (DXA) images in the Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using statistical shape modelling. ALSPAC is a rich source of phenotypic and genotypic data which provides a unique opportunity to investigate the environmental and genetic influences on hip shape in adolescence, as well as comparison with adult hip shape.

Significant morphological change in osteoarthritic hips identified over 6-12 months using statistical shape modelling

OBJECTIVE

Predicting who will develop osteoarthritis, assessing how rapidly their disease will progress and monitoring early responses to treatment are key to the development of therapeutic agents able to treat this crippling disease and to their future clinical use. Statistical Shape Modelling (SSM) enables quantification of variations in multiple geometric measures describing the whole hip joint to be considered in concert. This prospective study evaluates the responsiveness of SSM to changes in hip-shape within 1 year.

METHODS

Sixty-two people, mean age 67.1 yrs, were recruited. Dual-energy X-ray Absorptiometry images were taken at three timepoints (baseline, 6 and 12 months). Based on Kellgren-Lawrence grading (KLG) of their baseline images, subjects were classified into control/doubtful OA: KLG < 1 in both hips; moderate OA: KLG = 2; and severe OA: KLG ≥ 3 in their most severe hip. Morphology was quantified using SSM and changes in shape were assessed using generalised estimating equations. Standardized response means (SRMs) were calculated for the first and second 6 month periods, then the full 12 months.

RESULTS

Disease severity ranged from KLG0-KLG4 in the 124 hips assessed at baseline. Three SSM modes (Modes 1, 3 and 4) were associated with OA severity. Across the whole cohort, SRM magnitudes ranged from 0.16 to 0.63. The greatest subgroup SRM (magnitude 0.91) was observed over 12 months in those subjects with moderate OA (KLG2).

CONCLUSIONS

We have demonstrated that SSM can capture changes in hip shape over 6 and 12 months across the entire hip joint providing a sensitive measure of hip OA progression.

Associations between body mass index across adult life and hip shapes at age 60 to 64: Evidence from the 1946 British birth cohort

OBJECTIVE

To examine the associations of body mass index (BMI) across adulthood with hip shapes at age 60-64years.

METHODS

Up to 1633 men and women from the MRC National Survey of Health and Development with repeat measures of BMI across adulthood and posterior-anterior dual-energy X-ray absorptiometry bone mineral density images of the proximal femur recorded at age 60-64 were included in analyses. Statistical shape modelling was applied to quantify independent variations in hip mode (HM), of which the first 6 were examined in relation to: i) BMI at each age of assessment; ii) BMI gain during different phases of adulthood; iii) age first overweight.

RESULTS

Higher BMI at all ages (i.e. 15 to 60-64) and greater gains in BMI were associated with higher HM2 scores in both sexes (with positive HM2 values representing a shorter femoral neck and a wider and flatter femoral head). Similarly, younger age first overweight was associated with higher HM2 scores but only in men once current BMI was accounted for. In men, higher BMI at all ages was also associated with lower HM4 scores (with negative HM4 values representing a flatter femoral head, a wider neck and smaller neck shaft angle) but no associations with BMI gain or prolonged exposure to high BMI were found. Less consistent evidence of associations was found between BMI and the other four HMs.

CONCLUSION

These results suggest that BMI across adulthood may be associated with specific variations in hip shapes in early old age.

Statistical shape modelling of hip and lumbar spine morphology and their relationship in the MRC National Survey of Health and Development

The anatomical shape of bones and joints is important for their proper function but quantifying this, and detecting pathological variations, is difficult to do. Numerical descriptions would also enable correlations between joint shapes to be explored. Statistical shape modelling (SSM) is a method of image analysis employing pattern recognition statistics to describe and quantify such shapes from images; it uses principal components analysis to generate modes of variation describing each image in terms of a set of numerical scores after removing global size variation. We used SSM to quantify the shapes of the hip and the lumbar spine in dual-energy x-ray absorptiometry (DXA) images from 1511 individuals in the MRC National Survey of Health and Development at ages 60-64 years. We compared shapes of both joints in men and women and hypothesised that hip and spine shape would be strongly correlated. We also investigated associations with height, weight, body mass index (BMI) and local (hip or lumber spine) bone mineral density. In the hip, all except one of the first 10 modes differed between men and women. Men had a wider femoral neck, smaller neck-shaft angle, increased presence of osteophytes and a loss of the femoral head/neck curvature compared with women. Women presented with a flattening of the femoral head and greater acetabular coverage of the femoral head. Greater weight was associated with a shorter, wider femoral neck and larger greater and lesser trochanters. Taller height was accompanied by a flattening of the curve between superior head and neck and a larger lesser trochanter. Four of the first eight modes describing lumbar spine shape differed between men and women. Women tended to have a more lordotic spine than men with relatively smaller but caudally increasing anterior-posterior (a-p) vertebral diameters. Men were more likely to have a straighter spine with larger vertebral a-p diameters relative to vertebral height than women, increasing cranially. A weak correlation was found between body weight and a-p vertebral diameter. No correlations were found between shape modes and height in men, whereas in women there was a weak positive correlation between height and evenness of spinal curvature. Linear relationships between hip and spine shapes were weak and inconsistent in both sexes, thereby offering little support for our hypothesis. In conclusion, men and women entering their seventh decade have small but statistically significant differences in the shapes of their hips and their spines. Associations with height, weight, BMI and BMD are small and correspond to subtle variations whose anatomical significance is not yet clear. Correlations between hip and spine shapes are small.

Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments

Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.

Three dimensional measurement of minimum joint space width in the knee from stereo radiographs using statistical shape models

Objectives

An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry.

Materials and Methods

A validation study was performed using five cadaver specimens. The actual mJSW was varied and images were acquired with variation in the cadaver positioning. For comparison purposes, the mJSW was also assessed from plain radiographs. To study the influence of SSM model accuracy, the 3D mJSW measurement was repeated with models from the actual bones, obtained from CT scans.

Results

The SSM-based measurement method was more robust (consistent output for a wide range of input data/consistent output under varying measurement circumstances) than the conventional 2D method, showing that the 3D reconstruction indeed reduces the influence of patient positioning. However, the SSM-based method showed comparable sensitivity to changes in the mJSW with respect to the conventional method. The CT-based measurement was more accurate than the SSM-based measurement (smallest detectable differences 0.55 mm versus 0. 82 mm, respectively).

Conclusion

The proposed measurement method is not a substitute for the conventional 2D measurement due to limitations in the SSM model accuracy. However, further improvement of the model accuracy and optimisation technique can be obtained. Combined with the promising options for applications using quantitative information on bone morphology, SSM based 3D reconstructions of natural knees are attractive for further development.

Cite this article: E. A. van IJsseldijk, E. R. Valstar, B. C. Stoel, R. G. H. H. Nelissen, N. Baka, R. van’t Klooster, B. L. Kaptein. Three dimensional measurement of minimum joint space width in the knee from stereo radiographs using statistical shape models. Bone Joint Res 2016;320–327. DOI: 10.1302/2046-3758.58.2000626.

Can radiographs of hip fractures predict subsequent hip fractures? A shape modelling analysis

INTRODUCTION

The geometrical shape of the proximal femur has previously been shown to predict primary hip fractures. Hip fractures are routinely diagnosed on plain radiographs of the pelvis, and these have both hips viewable. We have investigated if statistical shape modelling of the uninvolved hip on plain radiographs, at the time of the first hip fracture episode, could predict a subsequent 'second fracture' on that (uninvolved) side.

MATERIALS AND METHODS

60 radiographs taken at the time of the index hip fracture were blinded and separated into two arms; patients sustaining one hip fracture only (n=30), and those who went on to sustain a second fracture (n=30), over the three-year follow-up period. Two separate shape models were used for these groups and compared using t-tests or Mann-Whitney U-tests, along with Cohen's d to measure the effect size of each measure.

RESULTS

We found no statistically significant difference in the shape of the femur between the first fracture and second fracture group (p>0.05) and no results reached a "medium" effect size (Cohen's d <0.5).

CONCLUSIONS

Shape modelling is feasible and can be applied in the routine clinical setting. However, we were unable to elucidate any predictive value in this relatively small sample. A reliable radiograph-based method of identifying patients at risk of second fracture would be of value in planning prevention, service provision, and cost analysis. Further work is required and a study with more patients might exclude the type 2 error in our work.

Bone morphology of the femur and tibia captured by statistical shape modelling predicts rapid bone loss in acute spinal cord injury patients

After spinal cord injury (SCI), bone loss in the paralysed limbs progresses at variable rates. Decreases in bone mineral density (BMD) in the first year range from 1% (slow) to 40% (rapid). In chronic SCI, fragility fractures commonly occur around the knee, with significant associated morbidity. Osteoporosis treatments await full evaluation in SCI, but should be initiated early and targeted towards patients exhibiting rapid bone loss. The potential to predict rapid bone loss from a single bone scan within weeks of a SCI was investigated using statistical shape modelling (SSM) of bone morphology, hypothesis: baseline bone shape predicts bone loss at 12-months post-injury at fracture-prone sites. In this retrospective cohort study 25 SCI patients (median age, 33 years) were scanned at the distal femur and proximal tibia using peripheral Quantitative Computed Tomography at <5 weeks (baseline), 4, 8 and 12 months post-injury. An SSM was made for each bone. Links between the baseline shape-modes and 12-month total and trabecular BMD loss were analysed using multiple linear regression. One mode from each SSM significantly predicted bone loss (age-adjusted P<0.05 R(2)=0.37-0.61) at baseline. An elongated intercondylar femoral notch (femur mode 4, +1 SD from the mean) was associated with 8.2% additional loss of femoral trabecular BMD at 12-months. A more concave posterior tibial fossa (tibia mode 3, +1 SD) was associated with 9.4% additional 12-month tibial trabecular BMD loss. Baseline bone shape determined from a single bone scan is a valid imaging biomarker for the prediction of 12-month bone loss in SCI patients.

ASSESSMENT OF OSTEOPOROTIC FEMORAL FRACTURE RISK: FINITE ELEMENT METHOD AS A POTENTIAL REPLACEMENT FOR CURRENT CLINICAL TECHNIQUES

Femoral fracture risk prediction is a necessary step preceding effective pharmacological intervention or pre-operative planning. Current clinical methods for fracture risk prediction rely on 2D imaging methods and have limited predictive value. Researchers are therefore trying to find improved methods for fracture prediction. During last few decades, many studies have focused on integration of 3D imaging techniques and the finite element (FE) method to improve the accuracy of fracture assessment techniques. In this paper, we review the recent advances in FE and other techniques for predicting the risk of femoral fractures. Based on a number of selected studies, the different steps that are involved in generation of patient-specific FE models are reviewed with particular emphasis on the fracture criteria. The inaccuracies that might arise due to the imperfections of the involved steps are also discussed. It is concluded that compared to image- and geometry-based techniques, FE is a more promising approach for prediction of fracture loads. However, certain technological advancements in FE modeling protocols are required before FE modeling can be recruited in clinical settings.

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

OBJECTIVE

To 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSION

These de novo findings suggest that rs4836732, rs6976, and rs5009270 may contribute to hip OA susceptibility by altering proximal femur shape.

Statistical shape and appearance models in osteoporosis

Statistical models (SMs) of shape (SSM) and appearance (SAM) have been acquiring popularity in medical image analysis since they were introduced in the early 1990s. They have been primarily used for segmentation, but they are also a powerful tool for 3D reconstruction and classification. All these tasks may be required in the osteoporosis domain, where fracture detection and risk estimation are key to reducing the mortality and/or morbidity of this bone disease. In this article, we review the different applications of SSMs and SAMs in the context of osteoporosis, and it concludes with a discussion of their advantages and disadvantages for this application.

Knee shape might predict clinical outcome after an anterior cruciate ligament rupture

We have investigated whether shape of the knee can predict the clinical outcome of patients after an anterior cruciate ligament rupture. We used statistical shape modelling to measure the shape of the knee joint of 182 prospectively followed patients on lateral and Rosenberg view radiographs of the knee after a rupture of the anterior cruciate ligament. Subsequently, we associated knee shape with the International Knee Documentation Committee subjective score at two years follow-up. The mean age of patients was 31 years (21 to 51), the majority were male (n = 121) and treated operatively (n = 135). We found two modes (shape variations) that were significantly associated with the subjective score at two years: one for the operatively treated group (p = 0.002) and one for the non-operatively treated group (p = 0.003). Operatively treated patients who had higher subjective scores had a smaller intercondylar notch and a smaller width of the intercondylar eminence. Non-operatively treated patients who scored higher on the subjective score had a more pyramidal intercondylar notch as opposed to one that was more dome-shaped. We conclude that the shape of the femoral notch and the intercondylar eminence is predictive of clinical outcome two years after a rupture of the anterior cruciate ligament.

Cite this article: Bone Joint J 2014;96-B:737–42.

Increasing shape modelling accuracy by adjusting for subject positioning: an application to the analysis of radiographic proximal femur symmetry using data from the Osteoarthritis Initiative

In total hip arthroplasty, the shape of the contra-lateral femur frequently serves as a template for preoperative planning. Previous research on contra-lateral femoral symmetry has been based on conventional hip geometric measurements (which reduce shape to a series of linear measurements) and did not take the effect of subject positioning on radiographic femur shape into account. The aim of this study was to analyse proximal femur symmetry based on statistical shape models (SSMs) which quantify global femoral shape while also adjusting for differences in subject positioning during image acquisition. We applied our recently developed fully automatic shape model matching (FASMM) system to automatically segment the proximal femur from AP pelvic radiographs to generate SSMs of the proximal femurs of 1258 Caucasian females (mean age: 61.3 SD=9.0). We used a combined SSM (capturing the left and right femurs) to identify and adjust for shape variation attributable to subject positioning as well as a single SSM (including all femurs as left femurs) to analyse proximal femur symmetry. We also calculated conventional hip geometric measurements (head diameter, neck width, shaft width and neck-shaft angle) using the output of the FASMM system. The combined SSM revealed two modes that were clearly attributable to subject positioning. The average difference (mean point-to-curve distance) between left and right femur shape was 1.0mm before and 0.8mm after adjusting for these two modes. The automatic calculation of conventional hip geometric measurements after adjustment gave an average absolute percent asymmetry of within 3.1% and an average absolute difference of within 1.1mm or 2.9° for all measurements. We conclude that (i) for Caucasian females the global shape of the right and left proximal femurs is symmetric without isolated locations of asymmetry; (ii) a combined left-right SSM can be used to adjust for radiographic shape variation due to subject positioning; and (iii) adjusting for subject positioning increases the accuracy of predicting the shape of the contra-lateral hip.

Morphometric evaluation of proximal femur in patients with unilateral total hip prosthesis

It is important to know the morphometric characteristics of the proximal femur. This is necessary to reduce the risk of complications related to surgical procedures performed in the area due to vascular, metabolic, or traumatic causes. It is of importance for achieving the alignment of the prosthesis to be implanted as well. The aim of this study was to evaluate the morphometric characteristics of the proximal femur and to establish a database for making and performing total hip prosthesis. Anteroposterior (AP) pelvic radiographs of 162 cases, with a mean age of 65.6 years, who had undergone unilateral total hip arthroplasty were used in this study. Femoral head diameter (FHD), femoral neck width (FNW), femoral neck length (FNL), femoral neck axis length (FNAL), intertrochanteric line length (ILL), and neck-shaft angle (NSA) were measured on radiographs obtained digitally using setrapacs media. FHD was found to be 48.1 ± 3.7 mm, FNW 35.4 ± 4.2 mm, FNL 30.8 ± 6.1 mm, FNAL 98.6 ± 9.4 mm, ILL 81.1 ± 7.9 mm, and NSA 130.4 ± 5.1° on average. The comparison of the mean values for females and males revealed a statistically significant difference between the FHD, FNW, FNL, FNAL, and ILL (P = 0.000). There was no statistically significant difference in NSA between males and females (P = 0.356). A weak correlation was found between age and parameter values using correlation analysis (r < 0.24, P > 0.05). In morphometric assessment of the proximal femur, taking into consideration regional and sexual differences is of importance for prosthesis design and surgical success.

Statistical shape and appearance models of bones

When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone.

Development of a fully automatic shape model matching (FASMM) system to derive statistical shape models from radiographs: application to the accurate capture and global representation of proximal femur shape

OBJECTIVE

To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.

DESIGN

AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.

RESULTS

De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).

CONCLUSIONS

The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis.

Computational anatomy in the study of bone structure

Osteoporosis is a major public health threat for millions of Americans with billions of dollars per year of national direct costs for osteoporotic fractures. Osteoporosis results in a decrease in overall bone mass and subsequent increase in the risk of bone fracture. Bone strength arises from the combination of bone size and shape, the distribution of bone mass throughout the structure, and the quality of the bone material. Advances in medical imaging have enabled a comprehensive assessment of bone structure through the analysis of high-resolution scans of relevant anatomical sites, eg, the proximal femur. However, conventional imaging analysis techniques use predefined regions of interest that do not take full advantage of such scans. Recently, computational anatomy, a set of imaging-based analysis algorithms, has emerged as a promising technique in studies of osteoporosis. Computational anatomy enables analyses that are not biased to one particular region and provide a more complete assessment of the whole structure. In this article, we review studies that have used computational anatomy to investigate the structure of the proximal femur in relation to age, fracture, osteoporotic treatment, and spaceflight effects.

Osteoporosis - a current view of pharmacological prevention and treatment

Postmenopausal osteoporosis is the most common bone disease, associated with low bone mineral density (BMD) and pathological fractures which lead to significant morbidity. It is defined clinically by a BMD of 2.5 standard deviations or more below the young female adult mean (T-score =−2.5). Osteoporosis was a huge global problem both socially and economically – in the UK alone, in 2011 £6 million per day was spent on treatment and social care of the 230,000 osteoporotic fracture patients – and therefore viable preventative and therapeutic approaches are key to managing this problem within the aging population of today. One of the main issues surrounding the potential of osteoporosis management is diagnosing patients at risk before they develop a fracture. We discuss the current and future possibilities for identifying susceptible patients, from fracture risk assessment to shape modeling and in relation to the high heritability of osteoporosis now that a plethora of genes have been associated with low BMD and osteoporotic fracture. This review highlights the current therapeutics in clinical use (including bisphosphonates, anti-RANKL [receptor activator of NF-κB ligand], intermittent low dose parathyroid hormone, and strontium ranelate) and some of those in development (anti-sclerostin antibodies and cathepsin K inhibitors). By highlighting the intimate relationship between the activities of bone forming (osteoblasts) and bone-resorbing (osteoclasts) cells, we include an overview and comparison of the molecular mechanisms exploited in each therapy.

Can we improve the prediction of hip fracture by assessing bone structure using shape and appearance modelling?

PURPOSE

There is a continuing need to improve the prediction of hip fractures to identify those at highest risk, enabling cost-effective use of preventative therapies.

METHODS

The aim of this work was to validate an innovative imaging biomarker for hip fracture by modelling the shape and texture of the proximal femur assessed from dual energy X-ray absorptiometry (DXA) scans. Scans used were acquired at baseline from elderly patients participating in a prospective, placebo-controlled fracture prevention study of the bisphosphonate, clodronate. 182 subjects who subsequently suffered a hip fracture were age, weight and height matched with two controls who did not suffer a fracture during a median 4-year follow-up period. Logistic regression was used to test if variables were good predictors of fracture and adjust for bone mineral density (BMD).

RESULTS

Shape mode 2, reflecting variability in neck-shaft angle, neck width and the size of both trochanters (0.81 (OR), 0.68-0.97 (CI), 0.024 (P)), and appearance mode 6, recording grey-level contrast (1.33, 1.11-1.59, 0.002), were significant predictors of hip fracture and remained so after adjustment for BMD (shape mode 2 (0.77, 0.64-0.93, 0.006), appearance mode 6 (1.32, 1.10-1.59, 0.003)). Receiver Operating Curve analysis showed the combination of shape mode 2, appearance mode 6 and BMD was 3% better than any single predictor.

CONCLUSION

Variables derived from shape and appearance models gave a prediction of fracture comparable to BMD and in combination with BMD gave an improvement in the prediction of hip fracture that could predict an additional 2000 hip fracture cases per year in the UK, potentially saving more than £20 million per year and 10,000 cases in the US.

Advances in bone imaging for osteoporosis

The diagnosis and management of osteoporosis have been improved by the development of new quantitative methods of skeletal assessment and by the availability of an increasing number of therapeutic options, respectively. A number of imaging methods exist and all have advantages and disadvantages. Dual-energy X-ray absorptiometry (DXA) is the most widely available and commonly utilized method for clinical diagnosis of osteoporosis and will remain so for the foreseeable future. The WHO 10-year fracture risk assessment tool (FRAX(®)) will improve clinical use of DXA and the cost-effectiveness of therapeutic intervention. Improved reporting of radiographic features that suggest osteoporosis and the presence of vertebral fracture, which are powerful predictors of future fractures, could increase the frequency of appropriate DXA referrals. Quantitative CT remains predominantly a research tool, but has advantages over DXA--allowing measurement of volumetric density, separate measures of cortical and trabecular bone density, and evaluation of bone shape and size. High resolution imaging, using both CT and MRI, has been introduced to measure trabecular and cortical bone microstructure. Although these methods provide detailed insights into the effects of disease and therapies on bone, they are technically challenging and not widely available, so they are unlikely to be used in clinical practice.

Hip fracture discrimination from dual-energy X-ray absorptiometry by statistical model registration

Although the areal Bone Mineral Density (BMD) measurements from dual-energy X-ray absorptiometry (DXA) are able to discriminate between hip fracture cases and controls, the femoral strength is largely determined by the 3D bone structure. In a previous work a statistical model was presented which parameterizes the 3D shape and BMD distribution of the proximal femur. In this study the parameter values resulting from the registration of the model onto DXA images are evaluated for their hip fracture discrimination ability with respect to regular DXA derived areal BMD measurements. The statistical model was constructed from a large database of QCT scans of females with an average age of 67.8 ± 17.0 years. This model was subsequently registered onto the DXA images of a fracture and control group. The fracture group consisted of 175 female patients with an average age of 66.4 ± 9.9 years who suffered a fracture on the contra lateral femur. The control group consisted of 175 female subjects with an average age of 65.3 ± 10.0 years and no fracture history. The discrimination ability of the resulting model parameter values, as well as the areal BMD measurements extracted from the DXA images were evaluated using a logistic regression analysis. The area under the receiver operating curve (AUC) of the combined model parameters and areal BMD values was 0.840 (95% CI 0.799-0.881), whilst using only the areal BMD values resulted in an AUC of 0.802 (95% CI 0.757-0.848). These results indicate that the discrimination ability of the areal BMD values is improved by supplementing them with the model parameter values, which give a more complete representation of the subject specific shape and internal bone distribution. Thus, the presented method potentially allows for an improved hip fracture risk estimation whilst maintaining DXA as the current standard modality.

Variant alleles of the Wnt antagonist FRZB are determinants of hip shape and modify the relationship between hip shape and osteoarthritis

OBJECTIVE

To test whether single-nucleotide polymorphisms (SNPs) of the FRZB gene are associated with hip shape, and to determine whether FRZB variant alleles affect the relationship between hip shape and radiographic osteoarthritis (OA) of the hip.

METHODS

A nested case-control study of Caucasian women, age ≥65 years, from the Study of Osteoporotic Fractures cohort was performed. Cases (n = 451) were defined as subjects with radiographic evidence of incident hip OA during followup, while controls (n = 601) were subjects in whom no radiographic hip OA was identified at baseline or followup. Statistical shape modeling (SSM) of the digitized hip radiographs was performed to assess the shape of the proximal femur, using 10 independent modes of shape variation generated by principal components analysis. In addition, center-edge angle and acetabular depth were assessed as geometric measurements of acetabular shape. The association of the rs288326 and rs7775 FRZB variant alleles with hip shape was analyzed using linear regression. The effect of these alleles on the relationship between hip shape and radiographic hip OA was analyzed using a logistic regression model with or without inclusion of interaction terms.

RESULTS

The rs288326 and rs7775 alleles were associated with the shape of the proximal femur (SSM mode 2). There was a significant interaction between the rs288326 SNP and proximal femur shape (SSM mode 2) in predicting radiographic hip OA (P for interaction = 0.022). Among subjects with the rs288326 variant allele, there was an increased likelihood of radiographic hip OA in association with increasing quartiles of proximal femur shape mode 2 (for the fourth quartile of mode 2, odds ratio 2.5, 95% confidence interval 1.15, 5.25; P for linear trend = 0.02).

CONCLUSION

The rs288326 and rs7775 FRZB SNPs are associated with the shape of the proximal femur. The presence of the rs288326 SNP alters the relationship between proximal femur shape and incident radiographic hip OA. These findings suggest that FRZB may serve an important role in determining hip shape and may modify the relationship between hip shape and OA.

Structural and functional maturation of distal femoral cartilage and bone during postnatal development and growth in humans and mice

The size and shape of joints markedly affect their biomechanical properties, but the macroscopic 3-dimensional (3-D) mechanism and extent of cartilage and joint maturation during normal growth are largely unknown. This study qualitatively illustrates the development of the bone-cartilage interface in the knee during postnatal growth in humans and C57BL/6 wild-type mice, quantitatively defines the 3-D shape using statistical shape modeling, and assesses growth strain rates in the mouse distal femur. Accurate quantification of the cartilage-bone interface geometry is imperative for furthering the understanding of the macroscopic mechanisms of cartilage maturation and overall joint development.

Improved radiograph measurement inter-observer reliability by use of statistical shape models

Pre- and post-operative radiographs of patients undergoing joint arthroplasty are often examined for a variety of purposes including preoperative planning and patient assessment. This work examines the feasibility of using active shape models (ASM) to semi-automate measurements from post-operative radiographs for the specific case of the Oxford™ Unicompartmental Knee. Measurements of the proximal tibia and the position of the tibial tray were made using the ASM model and manually. Data were obtained by four observers and one observer took four sets of measurements to allow assessment of the inter- and intra-observer reliability, respectively. The parameters measured were the tibial tray angle, the tray overhang, the tray size, the sagittal cut position, the resection level and the tibial width. Results demonstrated improved reliability (average of 27% and 11.2% increase for intra- and inter-reliability, respectively) and equivalent accuracy (p>0.05 for compared data values) for all of the measurements using the ASM model, with the exception of the tray overhang (p=0.0001). Less time (15s) was required to take measurements using the ASM model compared with manual measurements, which was significant. These encouraging results indicate that semi-automated measurement techniques could improve the reliability of radiographic measurements.