Femoral geometry as a risk factor for osteoporotic hip fracture in men and women

Estimation of population affinity using proximal femoral measurements based on computed tomographic images in the Japanese and western Australian populations

The present study analyzes morphological differences femora of contemporary Japanese and Western Australian individuals and investigates the feasibility of population affinity estimation based on computed tomographic (CT) data. The latter is deemed to be of practical importance because most anthropological methods rely on the assessment of aspects of skull morphology, which when damaged and/or unavailable, often hampers attempts to estimate population affinity. The study sample comprised CT scans of 297 (146 females; 151 males) Japanese and 330 (145 females; 185 males) Western Australian adult individuals. A total of 10 measurements were acquired in two-dimensional CT images of the left and right femora; two machine learning methods (random forest modeling [RFM]) and support vector machine [SVM]) were then applied for population affinity classification. The accuracy of the two-way (sex-specific and sex-mixed) model was between 71.38 and 82.07% and 76.09-86.09% for RFM and SVM, respectively. Sex-specific (female and male) models were slightly more accurate compared to the sex-mixed models; there were no considerable differences in the correct classification rates between the female- and male-specific models. All the classification accuracies were higher in the Western Australian population, except for the male model using SVM. The four-way sex and population affinity model had an overall classification accuracy of 74.96% and 79.11% for RFM and SVM, respectively. The Western Australian females had the lowest correct classification rate followed by the Japanese males. Our data indicate that femoral measurements may be particularly useful for classification of Japanese and Western Australian individuals.

The Morphology of the Femur Influences the Fracture Risk during Stumbling and Falls on the Hip-A Computational Biomechanical Study

Proximal femur fracture risk depends on subject-specific factors such as bone mineral density and morphological parameters. Here, we aim to analyze the dependency of the femoral strength on sixteen morphological parameters. Therefore, finite-element analyses of 20 human femurs during stumbling and lateral falls on the hip were conducted. Pearson correlation coefficients were calculated and morphological parameters with significant correlations were examined in principal component analysis and linear regression analysis. The dependency of the fracture strength on morphological parameters was more pronounced during lateral falls on the hip compared to stumbling. Significant correlations were observed between the neck shaft angle (r = -0.474), neck diameter (r = 0.507), the true distance between the femoral head center and femoral shaft axis (r = 0.459), and its projected distance on the frontal plane (r = 0.511), greater trochanter height (r = 0.497), and distance between the femoral head center and a plane parallel to the frontal plane containing the projection of the femoral head center to the femoral neck axis (r = 0.669). Principal component analysis was strongly weighted by parameters defining the lever arm during a lateral fall as well as the loaded cross-section in the femoral neck.

Utilizing 3-dimensional models to assess keel bone damage in laying hens throughout the lay cycle

The global egg industry is rapidly transitioning to cage-free egg production from conventional cages. Hens housed in cage-free systems have an increased prevalence of keel damage that could lead to reduced egg production and compromised well-being. The objective of this study was to determine the effects of dietary supplementation of n-3 fatty acids and vitamin D3 on keel damage in hens housed in multi-tier aviary systems (AV). Brown hens were placed in 4 AV system rooms after rearing at 17 wk of age (woa) with each room containing 576 birds. At 12 woa, rooms were randomly assigned to a dietary treatment of flaxseed oil, fish oil, vitamin D3, or control. Focal birds (36 per treatment) were longitudinally examined for keel damage using quantitative computed tomography (QCT) at nine timepoints from 16 to 52 woa. Three-dimensional digital twins of the keels were created from the QCT scans and visually assessed for damage. An overall keel severity score was recorded as well as the location, direction, and severity of each deviation or fracture. Severity was ranked on a 0 to 5 scale with 0 being no damage and 5 being severe. Damage scores were analyzed utilizing odds ratios with main effects of age and treatment. At 16 woa, 80% of hens had overall keel scores of 0 and 20% had scores of 1. At 52 woa, all hens had damage, with 31% having a score of 1, 61% scored 2 to 3, and 8% scored 4 to 5. Most fractures were not observed until peak lay. Dietary treatments did not affect likelihood of fracture incidences, but younger birds had lower odds of incurring keel fractures than older birds (P < 0.0001). The initial incidences of keel deviations occurred earlier than fractures, with most birds obtaining a keel deviation by 28 woa. Keel damage was not able to be prevented, but the age at which keel fractures and deviations initiate appear to be different, with deviations occurring during growth and fractures during lay.

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.

Association of Bone Shape and Alignment Analyzed Using Statistical Shape Modeling With Severity of First Metatarsophalangeal Joint Osteoarthritis

OBJECTIVE

We aimed to explore the relationship between bone shape and radiographic severity in individuals with first metatarsophalangeal joint osteoarthritis (first MTP joint OA).

METHODS

Weightbearing lateral and dorsoplantar radiographs were obtained for the symptomatic foot of 185 participants (105 females, aged 22 to 85 years) with clinically diagnosed first MTP joint OA. Participants were classified into none/mild, moderate, or severe categories using a standardized atlas. An 80-point model for lateral radiographs and 77-point model for dorsoplantar radiographs was used to define independent modes of variation using statistical shape modeling software. Odds ratios adjusted for confounders were calculated using ordinal regression to determine the association between radiographic severity and mode scores.

RESULTS

After assessment and grading of radiographs, 35 participants (18.9%) were included in the none/mild first MTP joint OA severity category, 69 (37.2%) in the moderate severity category, and 81 (43.7%) in the severe category. For lateral-view radiographs, 16 modes of variation were included, which collectively represented 83.2% of total shape variance. Of these, four modes were associated with radiographic severity. For dorsoplantar-view radiographs, 15 modes of variation were included, representing 82.6% of total shape variance. Of these, six modes were associated with radiographic severity.

CONCLUSIONS

Variations in the shape and alignment of the medial cuneiform, first metatarsal, and proximal and distal phalanx of the hallux are significantly associated with radiographic severity of first MTP joint OA. Prospective studies are required to determine whether bone shape characteristics are associated with the development and/or progression of this condition.

The effect of pre-fracture proximal femur geometry on hip fracture type in elderly patients

This study aimed to analyze the relationship between fracture type by determining data on the geometry of the proximal femur in the pre-fracture period in patients over 65 years of age who had hip fractures as a result of low-energy trauma. A total of 127 patients who were admitted to the hospital for reasons other than hip pathology within 1 year before the occurrence of hip fracture and who had an anterior-posterior pelvic X-ray were included in the study. Measurements were made to evaluate the proximal femur geometry, neck shaft angle, central edge angle, femoral head diameter, femoral neck diameter, femoral neck length, femoral offset length, femoral neck axial length, hip axis length, and femoral shaft diameter. As a result of these measurements, analyses were performed to determine the relationship between the control group and fracture types. The mean Neck shaft angle scores were significantly higher in both fracture types than in the control group (P = .034, P = .002). The mean Femoral offset length values of both fracture types were lower than those of the control group (P = .002, P = .011, respectively). Multiple logistic regression analysis revealed that the risk of collum femoris fracture increased as the Femoral head diameter value increased. (OD = 0.21, P = .002). The geometric parameters of the proximal femur play an important role in the formation of hip fracture types. Therefore, differences in proximal femur geometry in hip fracture types should be considered, and patient-focused choices should be made regarding the surgical procedures and implants to be used during fracture fixation.

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.

Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes

The adjusted binary classification (ABC) approach was proposed to assure that the binary classification model reaches a particular accuracy level. The present study evaluated the ABC for osteometric sex classification using multiple machine learning (ML) techniques: linear discriminant analysis (LDA), boosted generalized linear model (GLMB), support vector machine (SVM), and logistic regression (LR). We used 13 femoral measurements of 300 individuals from a modern Turkish population sample and split data into two sets: training (n = 240) and testing (n = 60). Then, the five best-performing measurements were selected for training univariate models, while pools of these variables were used for the multivariable models. ML classifier type did not affect the performance of unadjusted models. The accuracy of univariate models was 82−87%, while that of multivariate models was 89−90%. After applying ABC to the crossvalidation set, the accuracy and the positive and negative predictive values for uni- and multivariate models were ≥95%. Sex could be estimated for 28−75% of individuals using univariate models but with an obvious sexing bias, likely caused by different degrees of sexual dimorphism and between-group overlap. However, using multivariate models, we minimized the bias and properly classified 81−87% of individuals. A similar performance was also noted in the testing sample (except for FEB), with accuracies of 96−100%, and a proportion of classified individuals between 30% and 82% in univariate models, and between 90% and 91% in multivariate models. When considering different training sample sizes, we demonstrated that LR was the most sensitive with limited sample sizes (n < 150), while GLMB was the most stable classifier.

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.

Reliability analysis of CT torsion assessment after closed cephalomedullary nailing of trochanteric femoral fractures. A comparison study of six established methods

BACKGROUND

Posttraumatic maltorsion and implant failure after closed reduction of proximal femoral fractures remain a cause of concern. Although the reproducibility of torsion measuring techniques on CT for femoral shaft fractures has been thoroughly analyzed, little is known about the trochanteric fractures. Apart from the well-known CT limitations, posttraumatic alteration of bony landmarks makes torsional assessment even more challenging. Main goal of this study was to examine the reliability of different CT techniques on trochanteric femoral fractures after closed nail fixation. Secondary goal was to see whether the measurements within the examined population were influenced by the fracture type and patient age or BMI.

METHODS

20 cases (AO.31-A1 or -A2) were retrospectively examined. Six established CT techniques for torsional assessment were performed from three different investigators twice at different time points. The intraclass correlation coefficient (ICC for 95% CI) was used to analyze the interobserver and intraobserver reliability.

RESULTS

The Hernandez method (0.986) followed by the Jend method (0.982) by a mean difference of <1° showed the highest reliability. Although increasing fracture complexity from A1 to A2 led to an overall worsening of the measurement precision, the Hernandez and Jend techniques revealed a very good consistency. Within the examined population, age and BMI had no impact on the precision of the measurements.

CONCLUSIONS

The Hernandez and Jend methods represent reliable alternatives for torsional assessment of trochanteric femur fractures treated with closed nail fixation when compared to the other measurement techniques here involved. Documentation of the torsion measuring method used in each case constitutes an essential element of the radiological reports.

Causal Associations of Anthropometric Measurements With Fracture Risk and Bone Mineral Density: A Mendelian Randomization Study

Uncovering additional causal clinical traits and exposure variables is important when studying osteoporosis mechanisms and for the prevention of osteoporosis. Until recently, the causal relationship between anthropometric measurements and osteoporosis had not been fully revealed. In the present study, we utilized several state-of-the-art Mendelian randomization (MR) methods to investigate whether height, body mass index (BMI), waist-to-hip ratio (WHR), hip circumference (HC), and waist circumference (WC) are causally associated with two major characteristics of osteoporosis, bone mineral density (BMD) and fractures. Genomewide significant (p  ≤ 5 × 10^-8 ) single-nucleotide polymorphisms (SNPs) associated with the five anthropometric variables were obtained from previous large-scale genomewide association studies (GWAS) and were utilized as instrumental variables. Summary-level data of estimated bone mineral density (eBMD) and fractures were obtained from a large-scale UK Biobank GWAS. Of the MR methods utilized, the inverse-variance weighted method was the primary method used for analysis, and the weighted-median, MR-Egger, mode-based estimate, and MR pleiotropy residual sum and outlier methods were utilized for sensitivity analyses. The results of the present study indicated that each increase in height equal to a single standard deviation (SD) was associated with a 9.9% increase in risk of fracture (odds ratio [OR] = 1.099; 95% confidence interval [CI] 1.067-1.133; p = 8.793 × 10^-10 ) and a 0.080 SD decrease of estimated bone mineral density (95% CI -0.106-(-0.054); p = 2.322 × 10^-9 ). We also found that BMI was causally associated with eBMD (beta = 0.129, 95% CI 0.065-0.194; p = 8.113 × 10^-5 ) but not associated with fracture. The WHR adjusted for BMI, HC adjusted for BMI, and WC adjusted for BMI were not found to be related to fracture occurrence or eBMD. In conclusion, the present study provided genetic evidence for certain causal relationships between anthropometric measurements and bone mineral density or fracture risk. © 2021 American Society for Bone and Mineral Research (ASBMR).

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.

3D Analysis of the Proximal Femur Compared to 2D Analysis for Hip Fracture Risk Prediction in a Clinical Population

Due to the adverse impacts of hip fractures on patients' lives, it is crucial to enhance the identification of people at high risk through accessible clinical techniques. Reconstructing the 3D geometry and BMD distribution of the proximal femur could be beneficial in enhancing hip fracture risk predictions; however, it is associated with a high computational burden. It is also not clear whether it provides a better performance than 2D model analysis. Therefore, the purpose of this study was to compare the 2D and 3D model reconstruction's ability to predict hip fracture risk in a clinical population of patients. The DXA scans and CT scans of 16 cadaveric femurs were used to create training sets for the 2D and 3D model reconstruction based on statistical shape and appearance modeling. Subsequently, these methods were used to predict the risk of sustaining a hip fracture in a clinical population of 150 subjects (50 fractured, and 100 non-fractured) that were monitored for five years in the Canadian Multicentre Osteoporosis Study. 3D model reconstruction was able to improve the identification of patients who sustained a hip fracture more accurately than the standard clinical practice (by 40%). Also, the predictions from the 2D statistical model didn't differ significantly from the 3D ones (p > 0.76). These results indicated that to enhance hip fracture risk prediction in clinical practice implementing 2D statistical modeling has comparable performance with lower associated computational load.

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.

Evaluation of Hip Geometry Parameters in Patients With a Distal Radius Fracture

BACKGROUND

Patients with a distal radius fracture (DRF) have an increased risk of subsequent fractures including hip fractures. The purpose of this study was to evaluate whether women with a DRF have certain hip geometry parameters known to indicate susceptibility to hip fractures.

METHODS

We compared bone mineral density (BMD) and hip geometry parameters (hip axis length, neck shaft angle, mean cortical thickness, femur neck width, cross-sectional area [CSA], cross-sectional moment of inertia, section modulus, and buckling ratio) in 181 women with a DRF (DRF group) and 362 propensity score-matched women without a fracture (control group). We evaluated the associations between DRF and hip geometry parameters using logistic regression analysis.

RESULTS

The DRF group had lower hip BMD; lower cortical thickness, CSA, and section modulus; and higher buckling ratio than the control group (all p < 0.05). The occurrence of a DRF was significantly associated with decreases in neck shaft angle (odds ratio [OR], 1.047; 95% confidence interval [CI], 1.008-1.088) and CSA (OR, 3.114; 95% CI, 1.820-5.326) after adjusting for age, BMI, and total hip BMD.

CONCLUSIONS

In this study, women with a DRF were more likely than women without a DRF to have hip geometry parameters known to indicate susceptibility to hip fractures. Our results suggest that not only low hip BMD but also a decreased CSA could account for the increased risk of subsequent hip fracture in patients with a DRF.

Subregional statistical shape modelling identifies lesser trochanter size as a possible risk factor for radiographic hip osteoarthritis, a cross-sectional analysis from the Osteoporotic Fractures in Men Study

OBJECTIVE

Statistical shape modelling (SSM) of hip dual-energy X-ray absorptiometry (DXA) scans has identified relationships between hip shape and radiographic hip OA (rHOA). We aimed to further elucidate shape characteristics related to rHOA by focusing on subregions identified from whole-hip shape models.

METHOD

SSM was applied to hip DXAs obtained in the Osteoporotic Fractures in Men Study. Whole-hip shape modes (HSMs) associated with rHOA were combined to form a composite at-risk-shape. Subsequently, subregional HSMs (cam-type and lesser trochanter modes) were built, and associations with rHOA were examined by logistic regression. Subregional HSMs were further characterised, by examining associations with 3D-HSMs derived from concurrent hip CT scans.

RESULTS

4,098 participants were identified with hip DXAs and radiographs. Composite shapes from whole-hip HSMs revealed that lesser trochanter size and cam-type femoral head are related to rHOA. From sub-regional models, lesser trochanter mode (LTM)1 [OR 0.74; 95%CI 0.63.0.87] and cam-type mode (CTM)3 [OR 1.27; 1.13.1.42] were associated with rHOA, associations being similar to those for whole hip HSMs. 515 MrOS participants had hip DXAs and 3D-HSMs derived from hip CT scans. LTM1 was associated with 3D-HSMs that also represented a larger lesser trochanter [3D-HSM7 (beta (β)-0.23;-0.33,-0.14) and 3D-HSM9 (β0.36; 0.27.0.45)], and CTM3 with 3D-HSMs describing cam morphology [3D-HSM3 (β-0.16;-0.25,-0.07) and 3D-HSM6 (β 0.19; 0.10.0.28)].

CONCLUSION

Subregional SSM of hip DXA scans suggested larger lesser trochanter and cam morphology underlie associations between overall hip shape and rHOA. 3D hip modelling suggests our subregional SSMs represent true anatomical variations in hip shape, warranting further investigation.

Evaluation and Management of Osteoporosis and Sarcopenia in Patients with Distal Radius Fractures

Distal radius fractures (DRFs) are one of the most common fractures seen in elderly people. Patients with DRFs have a high incidence of osteoporosis and an increased risk of subsequent fractures, subtle early physical performance changes, and a high prevalence of sarcopenia. Since DRFs typically occur earlier than vertebral or hip fractures, they reflect early changes of the bone and muscle frailty and provide physicians with an opportunity to prevent progression of frailty and secondary fractures. In this review, we will discuss the concept of DRFs as a medical condition that is at the start of the fragility fracture cascade, recent advances in the diagnosis of bone fragility including emerging importance of cortical porosity, fracture healing with osteoporosis medications, and recent progress in research on sarcopenia in patients with DRFs.

The effect of pubertal timing, as reflected by height tempo, on proximal femur shape: Findings from a population-based study in adolescents

OBJECTIVE

To examine the relationship between pubertal timing (using measures of height tempo) and proximal femur shape in a large adolescent cohort.

METHODS

Hip DXA scans were obtained in offspring from the Avon Longitudinal Study of Parents and Children. To quantify hip morphology, the images were analyzed using Shape software based on a 53-point statistical shape model and independent modes of variation (hip shape mode (HSM) scores) for each image were generated. Height tempo (which corresponds to age at peak height velocity (aPHV)) was estimated from serial height measurements collected between age 5-20 years. Multivariable linear regression was used to examine cross-sectional associations between height tempo and the top ten HSMs at age 14 and 18, adjusting for sex and fat mass index (FMI).

RESULTS

Complete outcome and covariate data were available from 3827 and 3507 participants at age 14 and 18 years, respectively. Mean aPHV was 13.5 and 11.8 years for males and females, respectively. At age 14, height tempo was associated with a majority of modes, except for HSM4 and there was strong evidence of interaction by sex. In males, all modes showed evidence of an association with tempo, independent of FMI, with the strongest observed for HSM8 (adjusted β 0.38 (0.33, 0.43) p = 4.1 × 10-50). Compared with males, the associations were generally weaker in females, with the strongest effect observed for HSM8 (adjusted β 0.10 (0.05, 0.14) p = 1.6 × 10-5). The overall effect of later pubertal timing on proximal femur shape in males was a narrower femoral neck and larger superolateral head, whereas in females these changes were hard to discern. When assessed at age 18, there was little relationship between tempo and proximal femur shape in either sex.

CONCLUSION

Our results indicate that significant changes in hip shape occur during puberty, including aspects of shape which may be related to future risk of hip OA and/or fracture. However, puberty timing per se does not appear to exert long lasting effects on proximal femur shape.

Hip Structure Analyses in Acromegaly: Decrease of Cortical Bone Thickness After Treatment: A Longitudinal Cohort Study

Long‐standing growth hormone (GH) excess causes the skeletal clinical signs of acromegaly with typical changes in bone geometry, including increased cortical bone thickness (CBT). However, a high prevalence and incidence of vertebral fractures has been reported. The aim of this study was to assess the course of cortical bone dimensions in the hip by comparing patients with acromegaly and clinically nonfunctioning pituitary adenomas (NFPAs) at baseline and 1 year after pituitary surgery (1‐year PO) in a longitudinal cohort study. DXA was performed in patients with acromegaly (n = 56) and NFPA (n = 47). CBT in the femoral neck (CBTneck), calcar (CBTcalcar), and shaft (CBTshaft) were determined by hip structural analysis (HSA). CBT at baseline and the change to 1‐year PO were compared. Test results were adjusted for differences in gender distribution, age, and gonadal status. Cortical thickness analyses showed higher values [mm] at baseline in patients with acromegaly compared with NFPA: CBTneck median [25th; 75th] 6.2 [4.7; 8.0] versus 5.1 [4.1; 6.4] (p = 0.006), CBTcalcar 4.8 [4.2, 5.7] versus 4.0 [3.2, 4.5] (p < 0.001), CBTshaft 6.2 [5.1, 7.2] versus 5.2 [4.6, 6.0], (p = 0.003). In acromegaly, GH was correlated with CBTneck (r = 0.31, p = 0.020), whereas IGF‐1 was correlated with CBTcalcar (r = 0.39, p = 0.003) at baseline. In acromegaly, CBTneck decreased by 11.2%, p = 0.002 during follow‐up. Finally, the decrease in CBTneck and CBTcalcar in acromegaly was significant compared with NFPA (p = 0.023 and p = 0.017, respectively). Previous observations of increased CBT in acromegaly were confirmed with DXA‐derived HSA in a large, well‐defined cohort. The decline in CBT in acromegaly could contribute to the increased fracture risk in acromegaly despite increased bone dimensions and disease control. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Influence of femoral external shape on internal architecture and fracture risk

The internal architecture of the femur and its fracture behaviour vary greatly between subjects. Femoral architecture and subsequent fracture risk are strongly influenced by load distribution during physical activities of daily living. The objective of this work is to evaluate the impact of outer cortical surface shape as a key affector of load distribution driving femoral structure and fracture behaviour. Different femur cortical shapes are generated using a statistical shape model. Their mesoscale internal architecture is predicted for the same activity regime using a structural optimisation approach previously reported by the authors and fracture under longitudinal compression is simulated. The resulting total volume of bone is similar in all geometries although substantial differences are observed in distribution between trabecular and cortical tissue. Greater neck-shaft and anteversion angles show a protective effect in longitudinal compression while a thinner shaft increases fracture risk.

Improving the Hip Fracture Risk Prediction Through 2D Finite Element Models From DXA Images: Validation Against 3D Models

Osteoporotic fracture incidence represents a major social and economic concern in the modern society, where the progressive graying of the population involves an highly increased fracture occurrence. Although the gold standard to diagnose osteoporosis is represented by the T-score measurement, estimated from the Bone Mineral Density (BMD) using Dual-energy X-ray Absorptiometry (DXA), the identification of the subjects at high risk of fracture still remains an issue. From this perspective, the purpose of this work is to investigate the role that DXA-based two-dimensional patient-specific finite element (FE) models of the proximal femur, in combination with T-score, could play in enhancing the risk of fracture estimation. With this aim, 2D FE models were built from DXA images of the 28 post-menopausal female subjects involved. A sideways fall condition was reproduced and a Risk of Fracture (RF^) was computed on the basis of principal strains criteria. The identified RF^ was then compared to that derived from the CT-based models developed in a previous study. The 2D and 3D RF^ turned out to be significantly correlated (Spearman's ρ = 0.66, p < 0.001), highlighting the same patients as those at higher risk. Moreover, the 2D RF^ resulted significantly correlated with the T-score (Spearman's ρ = −0.69, p < 0.001), and managed to better differentiate osteopenic patients, drawing the attention to some of them. The Hip Structural Analysis (HSA) variables explaining the majority of the variance of the 2D and 3D fracture risk were the same as well, i.e., neck-shaft angle and narrow neck buckling ratio. In conclusion, DXA-based FE models, developable from currently available clinical data, appear promising in supporting and integrating the present diagnostic procedure.

The influence of ageing on the incidence and site of trauma femoral fractures: a cross-sectional analysis

BACKGROUND

This study aimed to determine the influence of ageing on the incidence and site of femoral fractures in trauma patients, by taking the sex, body weight, and trauma mechanisms into account.

METHODS

This retrospective study reviewed data from adult trauma patients aged ≥20 years who were admitted into a Level I trauma center, between January 1, 2009 and December 31, 2016. According to the femoral fracture locations, 3859 adult patients with 4011 fracture sites were grouped into five subgroups: proximal type A (n = 1359), proximal type B (n = 1487), proximal type C (n = 59), femoral shaft (n = 640), and distal femur (n = 466) groups. A multivariate logistic regression analysis was applied to identify independent effects of the univariate predictive variables on the occurrence of fracture at a specific site. A two-dimensional plot was presented visually with age and the propensity score accounts for the risk of a fracture at a specific femoral site.

RESULTS

This analysis revealed that older age was an independent variable that could positively predict the occurrence of proximal type A (OR [95%CI]: 1.03 [1.03-1.04], p < 0.001) and B fractures (1.02 [1.01-1.02], p < 0.001), and negatively predict the occurrence of proximal type C (0.96 [0.94-0.98], p < 0.001), shaft (0.95 [0.95-0.96], p < 0.001), and distal fractures (0.98 [0.98-0.99], p < 0.001).

DISCUSSION

Using the propensity scores which account for the risk of a fracture in a specific femoral site, this study revealed that the older patients were at a higher risk of developing proximal type A and type B fractures, while a lower risk of developing fractures in the shaft and distal femur. This incidence of fracture site can largely be explained by age-related factors, including a decrease in bone strength and falling being the most common mechanism of trauma in older patients.

CONCLUSIONS

This study revealed a difference in the involvement of age in the incidence of femoral fracture sites in the trauma patients.

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.

Surgically Relevant Morphological Parameters of Proximal Human Femur: A Statistical Analysis Based on 3D Reconstruction of CT Data

Objectives

Recently, more accurate description of the femoral geometry has become of interest to engineers and orthopedic surgeons. However, an appropriate database is lacking. Therefore, the aim of this study is to present morphological parameters and their correlations, which are relevant for medical issues such as impingement after total hip replacement, as well as for implant design and the etiology of hip fractures.

Methods

We investigated 12 well‐known morphological parameters of the femur in 169 healthy human subjects through evaluation of 3D‐reconstructed CT scans. Pearson's coefficients of correlations were calculated using a statistical t‐test method for each pair of parameters.

Results

The mean, maximum, minimum, median, and standard deviation values are reported for all parameters. Histograms showing the distribution of each morphological parameter are also presented. It is shown that absolute and horizontal offsets, total femur length, and NCVD parameters are normally distributed, but NCDF and NCDS are not. Furthermore, an inter‐correlation matrix was reported to reveal statistical correlations between these parameters. The strongest positive correlation existed between absolute offset (OSA) and horizontal offset (OSH), while the least positive correlation was found between NCDF and total femur length (TFL), and also between NCDS and NCDF. Anteversion angle (ATA) and OSA showed the least negative correlation. However, the strongest negative correlation was found between neck‐shaft angle (NSA) and greater trochanter height (GTH), as well as between OSA and NCVD.

Conclusions

Comprehending patients’ native bone morphology, including the variations and correlations, is essential for orthopedic surgeons to undertake preoperative planning and surgery as well as to appropriately design medical devices. Thus, more population‐based detailed databases are necessary. We investigated an extensive set of proximal femoral morphology parameters using a statistically standardized method to expand the existing knowledge. The results of our study can be used for diverse medical and biomechanical purposes.

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.

Review of 2-D/3-D Reconstruction Using Statistical Shape and Intensity Models and X-Ray Image Synthesis: Toward a Unified Framework

Patient-specific three-dimensional (3-D) bone models are useful for a number of clinical applications such as surgery planning, postoperative evaluation, as well as implant and prosthesis design. Two-dimensional-to-3-D (2-D/3-D) reconstruction, also known as model-to-modality or atlas-based 2-D/3-D registration, provides a means of obtaining a 3-D model of a patient's bones from their 2-D radiographs when 3-D imaging modalities are not available. The preferred approach for estimating both shape and density information (that would be present in a patient's computed tomography data) for 2-D/3-D reconstruction makes use of digitally reconstructed radiographs and deformable models in an iterative, non-rigid, intensity-based approach. Based on a large number of state-of-the-art 2-D/3-D bone reconstruction methods, a unified mathematical formulation of the problem is proposed in a common conceptual framework, using unambiguous terminology. In addition, shortcomings, recent adaptations, and persisting challenges are discussed along with insights for future research.

Extracapsular fracture of the femur in an elderly male from the Church of Nossa Senhora da Anunciada (Setúbal, Portugal)

In modern populations, hip fractures in older people are associated with high morbidity and mortality. Their incidence is rising; notwithstanding, fractures of the proximal femur are still relatively uncommon in archeological contexts. This case study represents a well-healed hip fracture in an aged male skeleton from Church of Nossa Senhora da Anunciada (16th-19th centuries AD) in Setúbal (Portugal). The individual was also diagnosed with diffuse idiopathic skeletal hyperostosis. Fractures of the proximal femur are usually associated with bone loss but in this case other causes are proposed, including the anatomy of the proximal femur, and the potential combined effect of diffuse idiopathic skeletal hyperostosis, cardiovascular disease, diabetes mellitus and falls.

Osteoporotic hip fracture prediction: is T-score based criterion enough? A Hip Structural Analysis based model

At present, the current gold-standard for osteoporosis diagnosis is based on bone mineral density measurement, which, however, has been demonstrated to poorly estimate fracture risk. Further parameters in the hands of the clinicians are represented by the Hip Structural Analysis (HSA) variables, which include geometric information of the proximal femur cross-section. The purpose of this study was to investigate the suitability of HSA parameters as additional hip fracture risk predictors. With this aim, twenty-eight three-dimensional patient-specific models of the proximal femur were built from CT images and a sideways fall condition was reproduced by finite element analyses. A tensile or compressive predominance based on minimum and maximum principal strains was determined at each volume element and a Risk Factor (RF) was calculated. The power of HSA variables combinations to predict the maximum superficial RF values was assessed by multivariate linear regression analysis. The optimal regression model, identified through the Akaike information criterion, only comprises two variables, the buckling ratio and the neck-shaft angle. In order to validate the study, the model was tested on two additional patients who suffered a hip fracture after a fall. The results classified the patients in the high risk level, confirming the prediction power of the adopted model.

Location of Femoral Fractures in Patients with Different Weight Classes in Fall and Motorcycle Accidents: A Retrospective Cross-Sectional Analysis

Background: This study aimed to determine the incidence of femoral fracture location in trauma patients with different weight classes in fall and motorcycle accidents. Methods: A total of 2647 hospitalized adult patients with 2760 femoral fractures from 1 January 2009 to 31 December 2014 were included in this study. Femoral fracture sites were categorized based on their location: proximal femur (type A, trochanteric; type B, neck; and type C, head), femoral shaft, and distal femur. The patients were further classified as obese (body mass index [BMI] of ≥30 kg/m²), overweight (BMI of <30 but ≥25 kg/m²), normal weight (BMI of <25 but ≥18.5 kg/m²), and underweight (BMI of <18.5 kg/m²). Odds ratios and 95% confidence intervals of the incidences of femoral fracture location were calculated in patients with different weight classes in fall or motorcycle accidents, and they were then compared with those in patients with normal weight. p values of <0.05 were considered statistically significant. Results: Most of the fractures sustained in fall accidents presented in the proximal type A (41.8%) and type B (45.3%) femur, whereas those sustained in motorcycle accidents involved the femoral shaft (37.1%), followed by the distal femur (22.4%) and proximal type A femur (21.2%). In fall accidents, compared with normal-weight patients, obese and overweight patients sustained lower odds of risk for proximal type B fractures but higher odds of risk for femoral shaft and distal femoral fractures. In motorcycle accidents, compared with normal-weight patients, obese patients sustained lower odds of risk for proximal type B fractures but no difference in odds of risk for femoral shaft and distal femoral fractures. Overweight and underweight patients who sustained fractures in a motorcycle accident did not have different fracture location patterns compared with normal-weight patients. Conclusions: This study revealed that femoral fracture locations differ between fall and motorcycle accidents. Moreover, greater soft tissue padding may reduce impact forces to the greater trochanteric region in obese patients during fall accidents, and during motorcycle accidents, the energy transmitted and the point of impact may dominantly determine the location of femoral fractures.

How does the femoral cortex depend on bone shape? A methodology for the joint analysis of surface texture and shape

In humans, there is clear evidence of an association between hip fracture risk and femoral neck bone mineral density, and some evidence of an association between fracture risk and the shape of the proximal femur. Here, we investigate whether the femoral cortex plays a role in these associations: do particular morphologies predispose to weaker cortices? To answer this question, we used cortical bone mapping to measure the distribution of cortical mass surface density (CMSD, mg/cm2) in a cohort of 125 females. Principal component analysis of the femoral surfaces identified three modes of shape variation accounting for 65% of the population variance. We then used statistical parametric mapping (SPM) to locate regions of the cortex where CMSD depends on shape, allowing for age. Our principal findings were increased CMSD with increased gracility over much of the proximal femur; and decreased CMSD at the superior femoral neck, coupled with increased CMSD at the calcar femorale, with increasing neck-shaft angle. In obtaining these results, we studied the role of spatial normalization in SPM, identifying systematic misregistration as a major impediment to the joint analysis of CMSD and shape. Through a series of experiments on synthetic data, we evaluated a number of registration methods for spatial normalization, concluding that only those predicated on an explicit set of homologous landmarks are suitable for this kind of analysis. The emergent methodology amounts to an extension of Geometric Morphometric Image Analysis to the domain of textured surfaces, alongside a protocol for labelling homologous landmarks in clinical CT scans of the human proximal femur.

DXA-derived hip shape is related to osteoarthritis: findings from in the MrOS cohort

OBJECTIVE

Statistical shape modelling (SSM) of radiographs has been used to explore relationships between altered joint shape and hip osteoarthritis (OA). We aimed to apply SSM to Dual-energy X-ray Absorptiometry (DXA) hip scans, and examine associations between resultant hip shape modes (HSMs), radiographic hip OA (RHOA), and hip pain, in a large population based cohort.

METHOD

SSM was performed on baseline hip DXA scans from the Osteoporotic Fractures in Men (MrOS) Study. Associations between the top ten HSMs, and prevalent RHOA from pelvic radiographs obtained 4.6 years later, were analysed in 4100 participants. RHOA was defined as Croft score ≥2. Hip pain was based on pain on walking, hip pain on examination, and Western Ontario and McMaster Universities Arthritis Index (WOMAC).

RESULTS

The five HSMs associated with RHOA showed features of either pincer- or cam-type deformities. HSM 1 (increased pincer-type deformity) was positively associated with RHOA [1.23 (1.09, 1.39)] [odds ratio (OR) and 95% CI]. HSM 8 (reduced pincer-type deformity) was inversely associated with RHOA [0.79 (0.70, 0.89)]. HSM 10 (increased cam-type deformity) was positively associated with RHOA [1.21 (1.07, 1.37)]. HSM 3 and HSM 4 (reduced cam-type deformity) were inversely associated with RHOA [0.73 (0.65, 0.83) and 0.82 (0.73, 0.93), respectively]. HSM 3 was inversely related to pain on examination [0.84 (0.76, 0.92)] and walking [0.88, (0.81, 0.95)], and to WOMAC score [0.87 (0.80, 0.93)].

CONCLUSIONS

DXA-derived measures of hip shape are associated with RHOA, and to a lesser extent hip pain, possibly reflecting their role in the pathogenesis of hip OA.

Sex estimation with the total area of the proximal femur: A densitometric approach

The estimation of sex is a central step to establish the biological profile of an anonymous skeletal individual. Imaging techniques, including bone densitometry, have been used to evaluate sex in remains incompletely skeletonized. In this paper, we present a technique for sex estimation using the total area (TA) of the proximal femur, a two-dimensional areal measurement determined through densitometry. TA was acquired from a training sample (112 females; 112 males) from the Coimbra Identified Skeletal Collection (University of Coimbra, Portugal). Logistic regression (LR), linear discriminant analysis (LDA), reduce error pruning trees (REPTree), and classification and regression trees (CART) were employed in order to obtain models that could predict sex in unidentified skeletal remains. Under cross-validation, the proposed models correctly estimated sex in 90.2-92.0% of cases (bias ranging from 1.8% to 4.5%). The models were evaluated in an independent test sample (30 females; 30 males) from the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal), with a sex allocation accuracy ranging from 90.0% to 91.7% (bias from 3.3% to 10.0%). Overall, data mining classifiers, especially the REPTree, performed better than the traditional classifiers (LR and LDA), maximizing overall accuracy and minimizing bias. This study emphasizes the significant value of bone densitometry to estimate sex in cadaveric remains in diverse states of preservation and completeness, even human remains with soft tissues.

Association of Osteoporosis Self-Assessment Tool for Asians (OSTA) Score with Clinical Presentation and Expenditure in Hospitalized Trauma Patients with Femoral Fractures

Background: A cross-sectional study to investigate the association of Osteoporosis Self-Assessment Tool for Asians (OSTA) score with clinical presentation and expenditure of hospitalized adult trauma patients with femoral fractures. Methods: According to the data retrieved from the Trauma Registry System between 1 January 2009 and 31 December 2015, a total of 2086 patients aged ≥40 years and hospitalized for treatment of traumatic femoral bone fracture were categorized as high-risk patients (OSTA < -4, n = 814), medium-risk patients (-1 ≥ OSTA ≥ -4, n = 634), and low-risk patients (OSTA > -1, n = 638). Two-sided Pearson's, chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U-test were used to analyze normally and non-normally distributed continuous data, respectively. Propensity-score matching in a 1:1 ratio was performed using Number Crunching Statistical Software (NCSS) software (NCSS 10; NCSS Statistical Software, Kaysville, UT, USA), with adjusted covariates including mechanism and Glasgow Coma Scale (GCS); injuries were assessed based on the Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS) was used to evaluate the effect of OSTA-related grouping on a patient's outcome. Results: High-risk and medium-risk patients were predominantly female, presented with significantly older age and higher incidences of co-morbidity, and were injured in a fall accident more frequently than low-risk patients. High-risk patients and medium-risk patients had a different pattern of femoral fracture and a significantly lower ISS. Although high-risk and medium-risk patients had significantly shorter lengths hospital of stay (LOS) and less total expenditure than low-risk patients did, similar results were not found in the selected propensity score-matched patients, implying that the difference may be attributed to the associated injury severity of the patients with femoral fracture. However, the charge of surgery is significantly lower in high-risk and medium-risk patients than in low-risk patients, regardless of the total population or the selected propensity score-matched patients. This lower charge of surgery may be attributed to a less aggressive surgery applied for older patients with high or medium risk of osteoporosis. Conclusions: This study of hospitalized trauma patients with femoral fracture according to OSTA risk classification revealed that high-risk and medium-risk patients had significantly higher odds of sustaining injury in a fall accident than low-risk patients; they also present a different pattern of femoral bone fracture as well as a significantly lower ISS, shorter hospital LOS, and less total expenditure. In addition, the significantly lower charge of surgery in high-risk and medium-risk patients than in low-risk patients may be because of the preference of orthopedists for less aggressive surgery in dealing with older patients with osteoporotic femoral bone fracture.

Proximal Femoral Geometry as Fracture Risk Factor in Female Patients with Osteoporotic Hip Fracture

Background

Proximal femoral geometry may be a risk factor of osteoporotic hip fractures. However, there existed great differences among studies depending on race, sex and age of subjects. The purpose of the present study is to analyze proximal femoral geometry and bone mineral density (BMD) in the osteoporotic hip fracture patients. Furthermore, we investigated proximal femoral geometric parameters affecting fractures, and whether the geometric parameters could be an independent risk factor of fractures regardless of BMD.

Methods

This study was conducted on 197 women aged 65 years or more who were hospitalized with osteoporotic hip fracture (femur neck fractures ; 84, intertrochanteric fractures; 113). Control group included 551 women who visited to check osteoporosis. Femur BMD and proximal femoral geometry for all subjects were measured using dual energy X-ray absorptiometry (DXA), and compared between the control and fracture groups. Besides, proximal femoral geometric parameters associated with fractures were statistically analyzed.

Results

There were statistically significant differences in the age and weight, cross-sectional area (CSA)/length/width of the femoral neck and BMD of the proximal femur between fracture group and control group. BMD of the proximal femur in the control group was higher than in the fracture group. For the femoral neck fractures group, the odds ratio (OR) for fractures decrease in the CSA and neck length (NL) of the femur increased by 1.97 times and 1.73 times respectively, regardless of BMD. The OR for fractures increase in the femoral neck width increased by 1.53 times. In the intertrochanteric fracture group, the OR for fractures increase in the femoral neck width increased by 1.45 times regardless of BMD.

Conclusions

We found that an increase of the femoral neck width could be a proximal femoral geometric parameter which plays important roles as a risk factor for fracture independently of BMD.

A method for sex estimation using the proximal femur

The assessment of sex is crucial to the establishment of a biological profile of an unidentified skeletal individual. The best methods currently available for the sexual diagnosis of human skeletal remains generally rely on the presence of well-preserved pelvic bones, which is not always the case. Postcranial elements, including the femur, have been used to accurately estimate sex in skeletal remains from forensic and bioarcheological settings. In this study, we present an approach to estimate sex using two measurements (femoral neck width [FNW] and femoral neck axis length [FNAL]) of the proximal femur. FNW and FNAL were obtained in a training sample (114 females and 138 males) from the Luís Lopes Collection (National History Museum of Lisbon). Logistic regression and the C4.5 algorithm were used to develop models to predict sex in unknown individuals. Proposed cross-validated models correctly predicted sex in 82.5-85.7% of the cases. The models were also evaluated in a test sample (96 females and 96 males) from the Coimbra Identified Skeletal Collection (University of Coimbra), resulting in a sex allocation accuracy of 80.1-86.2%. This study supports the relative value of the proximal femur to estimate sex in skeletal remains, especially when other exceedingly dimorphic skeletal elements are not accessible for analysis.

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.

Relationship of Height to Site-Specific Fracture Risk in Postmenopausal Women

Height has been associated with increased risk of fracture of the neck of femur. However, information on the association of height with fractures at other sites is limited and conflicting. A total of 796,081 postmenopausal women, who reported on health and lifestyle factors including a history of previous fractures and osteoporosis, were followed for 8 years for incident fracture at various sites by record linkage to National Health Service hospital admission data. Adjusted relative risks of fracture at different sites per 10-cm increase in height were estimated using Cox regression. Numbers with site-specific fractures were: humerus (3036 cases), radius and/or ulna (1775), wrist (9684), neck of femur (5734), femur (not neck) (713), patella (649), tibia and/or fibula (1811), ankle (5523), and clavicle/spine/rib (2174). The risk of fracture of the neck of femur increased with increasing height (relative risk [RR] = 1.48 per 10-cm increase, 99% confidence interval [CI] 1.39-1.57) and the proportional increase in risk was significantly greater than for all other fracture sites (pheterogeneity < 0.001). For the other sites, fracture risk also increased with height (RR = 1.15 per 10 cm, CI 1.12-1.18), but there was only very weak evidence of a possible difference in risk between the sites (pheterogeneity = 0.03). In conclusion, taller women are at increased risk of fracture, especially of the neck of femur.

Non-invasive Assessment of Lower Limb Geometry and Strength Using Hip Structural Analysis and Peripheral Quantitative Computed Tomography: A Population-Based Comparison

Hip fracture is the most significant complication of osteoporosis in terms of mortality, long-term disability and decreased quality of life. In the recent years, different techniques have been developed to assess lower limb strength and ultimately fracture risk. Here we examine relationships between two measures of lower limb bone geometry and strength; proximal femoral geometry and tibial peripheral quantitative computed tomography. We studied a sample of 431 women and 488 men aged in the range 59-71 years. The hip structural analysis (HSA) programme was employed to measure the structural geometry of the left hip for each DXA scan obtained using a Hologic QDR 4500 instrument while pQCT measurements of the tibia were obtained using a Stratec 2000 instrument in the same population. We observed strong sex differences in proximal femoral geometry at the narrow neck, intertrochanteric and femoral shaft regions. There were significant (p < 0.001) associations between pQCT-derived measures of bone geometry (tibial width; endocortical diameter and cortical thickness) and bone strength (strength strain index) with each corresponding HSA variable (all p < 0.001) in both men and women. These results demonstrate strong correlations between two different methods of assessment of lower limb bone strength: HSA and pQCT. Validation in prospective cohorts to study associations of each with incident fracture is now indicated.

Association between femur size and a focal defect of the superior femoral neck

Within each sex, there is an association between hip fracture risk and the size of the proximal femur, with larger femurs apparently more susceptible to fracture. Here, we investigate whether the thickness and density of the femoral cortex play a role in this association: might larger femurs harbour focal, cortical defects? To answer this question, we used cortical bone mapping to measure the distribution of cortical mass surface density (CMSD, mg/cm(2)) in cohorts of 308 males and 125 females. Principal component analysis of the various femoral surfaces led to a measure of size that is linearly independent from shape. After mapping the data onto a canonical femur surface, we used statistical parametric mapping to identify any regions where CMSD depends on size, allowing for other confounding covariates including shape. Our principal finding was a focal patch on the superior femoral neck, where CMSD is reduced by around 1% for each 1% increase in proximal-distal size (p<0.000005 in the males, p<0.001 in the females). This finding appears to be consistent with models of functional adaptation, and may help with the design of interventional strategies for reducing fracture risk.

Negative Impact of Aromatase Inhibitors on Proximal Femoral Bone Mass and Geometry in Postmenopausal Women with Breast Cancer

Aromatase inhibitors (AIs), the standard therapy for estrogen receptor- or progesterone receptor-positive breast cancer in postmenopausal women, lead to increased hip fractures in breast cancer patients. To investigate the mechanism of increased incidence of hip fractures in breast cancer patients treated with AIs, we evaluated bone mineral density (BMD) in the cortical and trabecular compartments and assessed femoral geometry using quantitative computed tomography (QCT) in breast cancer patients. In total, 249 early breast cancer patients who underwent QCT in their fifties (mean age 54.3 years) were retrospectively analyzed. Proximal femoral BMD and geometrical parameters were compared. In all regions of the proximal femur, cortical areal BMDs were lower in the AI group than in the non-AI group (p < 0.05). Cortical thickness of the femoral neck, trochanter, and total hip was significantly lower in the AI group compared with the non-AI group (p < 0.05). Analysis of the narrowest section of the femoral neck showed significantly thinner cortical bone and smaller cortical area in the AI group than in the non-AI group (p < 0.05), especially in the superoposterior quadrant. Bone strength parameters in the femoral neck, such as the section modulus and cross-sectional moment of inertia, were significantly lower in the AI group than in the non-AI group (p < 0.05). In conclusion, AI treatment in breast cancer patients is associated with deterioration of femoral cortical BMD and geometry, which could contribute in site-specific weakened bone strength and increased incidence of hip fractures.

A two-level subject-specific biomechanical model for improving prediction of hip fracture risk

BACKGROUND

Sideways fall-induced hip fracture is a major worldwide health problem among the elderly population. However, all existing biomechanical models for predicting hip fracture mainly consider the femur related parameters. Their accuracy is limited as hip fracture is significantly affected by loading conditions as well. The objective of this study was to develop a biomechanical model for improving assessment of hip fracture risk by subject-specific prediction of fall-induced loading conditions.

METHOD

All information required to construct the models was extracted from the subject's whole-body and hip medical image in order to make the models subject-specific. Fall-induced hip fracture risk for eighty clinical cases was calculated under two sets of loading conditions: subject-specific determined by the proposed model, and non-subject-specific obtained from empirical functions. The predicted hip fracture risk indices were then compared with clinical observations.

FINDINGS

It was found that the subject-specific prediction of fall-induced loading conditions significantly improves the hip fracture risk assessment. Consistent to the clinical observations, the fracture risk predicted by the proposed model suggested that obesity is a protective factor for hip fracture and underweight subjects are more likely to experience a hip fracture.

INTERPRETATIONS

This study shows that hip fracture risk is affected by a number of factors, including body weight, body height, impact force, body mass index, hip soft tissue thickness, and bone quality. The proposed model provides a comprehensive, fast, accurate, and non-expensive method for prediction of hip fracture risk which should lead to more effective prevention of hip fractures.

Exercise capacity independently predicts bone mineral density and proximal femoral geometry in patients with acute decompensated heart failure

Heart failure is associated with increased risk of osteoporosis. We evaluated the prevalence and predictors of osteoporosis in hospitalized patients with ADHF using quantitative computed tomography. Osteoporosis and vertebral fracture are prevalent in patients with ADHF and exercise capacity independently predicts bone mass and femoral bone geometry.

INTRODUCTION

Heart failure is associated with reduced bone mass and increased risk of osteoporotic fractures. However, the prevalence and predictors of osteoporosis in hospitalized patients with acute decompensated heart failure (ADHF) are not well understood.

METHODS

Sixty-five patients (15 postmenopausal females and 50 males) with ADHF were prospectively and consecutively enrolled. After stabilization of heart failure symptoms, quantitative computed tomography for bone mineral density (BMD) and femoral geometry as well as biochemical, echocardiographic, and cardiopulmonary exercise tests were performed.

RESULTS

Fifteen postmenopausal female showed a high prevalence of osteoporosis (40%) and vertebral fracture (53%). Among 50 male patients, 12% had osteoporosis and 32% had osteopenia, while vertebral fracture was found in 12%. Lumbar volumetric BMD (vBMD) was significantly lower in ischemic patients than non-ischemic patients (107.9 ± 47.5 vs. 145.4 ± 40.9 mg/cm(3), p = 0.005) in male. Exercise capacity, indicated by peak oxygen consumption (VO2), was significantly associated with lumbar vBMD (r = 0.576, p < 0.001) and total hip areal BMD (aBMD) (r = 0.512, p = 0.001) and cortical thickness of the femur neck (r = 0.544, p = 0.001). When controlled for age, body mass index, N-terminal proBrain natriuretic protein (NT-proBNP), etiology of heart failure, hemoglobin, and thigh circumference, multivariate regression analysis revealed peak VO2 independently predicted lumbar vBMD (β = 0.448, p = 0.031), total hip aBMD (β = 0.547, p = 0.021), and cortical thickness of the femur neck (β = 0.590, p = 0.011).

CONCLUSION

In male patients with ADHF, osteoporosis and vertebral fracture are prevalent, and exercise capacity independently predicts bone mass and geometry. Given that heart failure patients with reduced exercise capacity carry a substantial increased risk of fracture, proper osteoporosis evaluation is important in these patients.

A new computer-tomography-based method of sex estimation: Development of Turkish population-specific standards

The identification of victims involved in mass fatality incidents has become an increasingly important issue nowadays, and identification of unknown individuals is an important aspect in criminal cases and Disaster Victim Identification scenarios. Therefore, the sex estimation is one of the most important biological attributes towards establishing personal identity. In addition, several studies have demonstrated that metric sex determination methods of the skeleton are population-specific due to variation in size and patterns of sexual dimorphism. Unfortunately, the modern Turkish population still lacks wide and representative population standards for identification. Previous research has shown that modern technologies, such as CT scanning appear to offer promising means for the establishment of new standards for contemporary populations. The main aim of this project is to examine the application of measurements taken from the femur in order to assess sex, as well as to contribute to the establishment of discriminant function equations for the Turkish population for forensic applications. The sample population was composed of CT images taken from 200 adult hospital patients. The images of the femora were segmented from the surrounding bones to ensure correct usage of landmarks as accurately as possible. The 3D reconstructions were then created using the volume-rendering function in OsiriX (v.5.6.). Thirteen measurements were acquired using a 3D viewer and were located and marked on each of the CT reconstructed femora. Thirteen anthropometric parameters were measured and analysed by basic descriptive statistics and discriminant analysis methods using the SPSS 21.0 software package. The intra-observer variation was assessed by obtaining the inter-cross correlation coefficient in order to evaluate the accuracy of the linear measurements taken. The accuracy of sex prediction ranged from 63.5 to 88% with single variables. In stepwise analysis, Epicondylar Breadth, Femur Vertical Diameter of Neck and Medial Lateral Subtrochanteric Diameter were found to be the most discriminating variables providing an accuracy of 91%. Ultimately, it is envisaged that this research study will produce data and interpretations that will inform on and improve standards of sex estimation from postcranial osteometric landmarks. Additionally, this research will consider how this data provides value for a developing discipline of forensic anthropology and how it integrates within the existing systems of criminal investigation and Disaster Victim Identification practices in Turkey.

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.

Growth and aging of proximal femoral bone: a study with women spanning three generations

Osteoporotic hip fracture is a serious clinical event associated with high morbidity and mortality. Understanding femoral growth patterns is important for promoting bone health in the young and preventing fractures in later life. In this study, growth patterns of areal bone mineral density (aBMD) and geometric properties of the proximal femur were measured by dual-energy X-ray absorptiometry. They were studied in 251 girls from premenarche (11.2 ± 0.7 years) to late adolescence (18.3 ± 1.1 years) and compared with their premenopausal mothers (n = 128, aged 44.9 ± 4.1 years) and postmenopausal grandmothers (n = 128, aged 70.0 ± 6.3 years). Hip axis length (HAL) was the first to reach peak growth velocity (-10.5 months before menarche), followed by neck diameter (ND) and neck cross-sectional area (CSA), (-7.1 and -4.1 months before menarche, respectively). Both neck-shaft angle (NSA) and aBMD of neck and total hip peaked at menarche. At 18 years (7-year follow-up), girls already had higher femoral neck aBMD but similar HAL and NSA compared with their mothers. Grandmothers had the longest HAL, narrowest NSA, widest ND but lowest aBMD and CSA. Hip strength index (HSI), an index of femoral neck strength during a fall, dropped rapidly after menarche in girls but thereafter remained relatively constant. Grandmothers had lower HSI than either mothers or girls. In conclusion, differences in proximal femoral bone mass and structure in adulthood are largely established before menarche, indicating that heritable factors are responsible for most of the individual variance. The development of geometric properties precedes aBMD in puberty, resulting in relatively constant hip strength after menarche. This asynchronous growth leads to adaptation of bone strength to the imposed loads, avoiding fractures in a biologically efficient manner. Both deterioration of aBMD and inadequate compensatory change in bone geometry after menopause contribute to the increased fracture risk later in life.