A new hip fracture risk index derived from FEA-computed proximal femur fracture loads and energies-to-failure.

Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient-specific finite element (FE) analysis (FEA) incorporates bone geometry and bone density in the proximal femur. We developed a global FEA-computed fracture risk index to increase the prediction accuracy of hip fracture incidence. PURPOSE: Quantitative CT-based patient-specific finite element (FE) analysis (FEA) incorporates bone geometry and bone density in the proximal femur to compute the force (fracture load) and energy necessary to break the proximal femur in a particular loading condition. The fracture loads and energies-to-failure are individually associated with incident hip fracture, and provide different structural information about the proximal femur. METHODS: We used principal component analysis (PCA) to develop a global FEA-computed fracture risk index that incorporates the FEA-computed yield and ultimate failure loads and energies-to-failure in four loading conditions of 110 hip fracture subjects and 235 age- and sex-matched control subjects from the AGES-Reykjavik study. Using a logistic regression model, we compared the prediction performance for hip fracture based on the stratified resampling. RESULTS: We referred the first principal component (PC1) of the FE parameters as the global FEA-computed fracture risk index, which was the significant predictor of hip fracture (p-value < 0.001). The area under the receiver operating characteristic curve (AUC) using PC1 (0.776) was higher than that using all FE parameters combined (0.737) in the males (p-value < 0.001). CONCLUSIONS: The global FEA-computed fracture risk index increased hip fracture risk prediction accuracy in males.

Use of Quantitative Computed Tomography to Assess for Clinically-relevant Skeletal Effects of Prolonged Spaceflight on Astronaut Hips.

INTRODUCTION: In 2010, experts in osteoporosis and bone densitometry were convened by the Space Life Sciences Directorate at NASA Johnson Space Center to identify a skeletal outcome in astronauts after spaceflight that would require a clinical response to address fracture risk. After reviewing astronaut data, experts expressed concern over discordant patterns in loss and recovery of bone mineral density (BMD) after spaceflight as monitored by dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT). The pilot study described herein demonstrates the use of QCT to evaluate absence of recovery in hip trabecular BMD by QCT as an indicator of a clinically actionable response. METHODOLOGY: QCT and DXA scans of both hips were performed on 10 astronauts: once preflight and twice postflight about 1 wk and 1 yr after return. If trabecular BMD had not returned to baseline (i.e., within QCT measurement error) in 1 or both hips 1 yr after flight, then another QCT hip scan was obtained at 2 yr after flight. RESULTS: Areal BMD by DXA recovered in 9 of 10 astronauts at 1 yr postflight while incomplete recovery of trabecular BMD by QCT was evident in 5 of 10 astronauts and persisted in 4 of the 5 astronauts 2 yr postflight. CONCLUSION: As an adjunct to DXA, QCT is needed to detect changes to hip trabecular BMD after spaceflight and to confirm complete recovery. Incomplete recovery at 2 yr should trigger the need for further evaluation and possible intervention to mitigate premature fragility and fractures in astronauts following long-duration spaceflight.

Liquid Calibration Phantoms in Ultra-Low-Dose QCT for the Assessment of Bone Mineral Density.

INTRODUCTION: Cortical bone is affected by metabolic diseases. Some studies have shown that lower cortical bone mineral density (BMD) is related to increases in fracture risk which could be diagnosed by quantitative computed tomography (QCT). Nowadays, hybrid iterative reconstruction-based (HIR) computed tomography (CT) could be helpful to quantify the peripheral bone tissue. A key focus of this paper is to evaluate liquid calibration phantoms for BMD quantification in the tibia and under hybrid iterative reconstruction-based-CT with the different hydrogen dipotassium phosphate (K2HPO4) concentrations phantoms. METHODOLOGY: Four ranges of concentrations of K2HPO4 were made and tested with 2 exposure settings. Accuracy of the phantoms with ash gravimetry and intermediate K2HPO4 concentration as hypothetical patients were evaluated. The correlations and mean differences between measured equivalent QCT BMD and ash density as a gold standard were calculated. Relative percentage error (RPE) in CT numbers of each concentration over a 6-mo period was reported. RESULTS: The correlation values (R2 was close to 1.0), suggested that the precision of QCT-BMD measurements using standard and ultra-low dose settings were similar for all phantoms. The mean differences between QCT-BMD and the ash density for low concentrations (about 93 mg/cm3) were lower than high concentration phantoms with 135 and 234 mg/cm3 biases. In regard to accuracy test for hypothetical patient, RPE was up to 16.1% for the low concentration (LC) phantom for the case of high mineral content. However, the lowest RPE (0.4 to 1.8%) was obtained for the high concentration (HC) phantom, particularly for the high mineral content case. In addition, over 6 months, the K2HPO4 concentrations increased 25% for 50 mg/cm3 solution and 0.7 % for 1300 mg/cm3 solution in phantoms. CONCLUSION: The excellent linear correlations between the QCT equivalent density and the ash density gold standard indicate that QCT can be used with submilisivert radiation dose. We conclude that using liquid calibration phantoms with a range of mineral content similar to that being measured will minimize bias. Finally, we suggest performing BMD measurements with ultra-low dose scan concurrent with iterative-based reconstruction to reduce radiation exposure.

Runners With Patellofemoral Pain Exhibit Greater Peak Patella Cartilage Stress Compared With Pain-Free Runners.

The primary purpose of this study is to determine whether recreational runners with patellofemoral pain (PFP) exhibit greater peak patella cartilage stress compared with pain-free runners. A secondary purpose was to determine the kinematic and/or kinetic predictors of peak patella cartilage stress during running. A total of 22 female recreational runners (12 with PFP and 10 pain-free controls) participated in this study. Patella cartilage stress profiles were quantified using subject-specific finite element models simulating the maximum knee flexion angle during the stance phase of running. Input parameters to the finite element model included subject-specific patellofemoral joint geometry, quadriceps muscle forces, and lower-extremity kinematics in the frontal and transverse planes. Tibiofemoral joint kinematics and kinetics were quantified to determine the best predictor of stress using stepwise regression analysis. Compared with the pain-free runners, those with PFP exhibited greater peak hydrostatic pressure (PFP vs control: 21.2 [5.6] MPa vs 16.5 [4.6] MPa) and maximum shear stress (PFP vs control: 11.3 [4.6] MPa vs 8.7 [2.3] MPa). Knee external rotation was the best predictor of peak hydrostatic pressure and peak maximum shear stress (38% and 25% of variances, respectively), followed by the knee extensor moment (21% and 25% of variances, respectively). Runners with PFP exhibit greater peak patella cartilage stress during running compared with pain-free individuals. The combination of knee external rotation and a high knee extensor moment best predicted the elevated peak stress during running.

Physical Activity for Strengthening Fracture Prone Regions of the Proximal Femur.

PURPOSE OF REVIEW: Physical activity improves proximal femoral bone health; however, it remains unclear whether changes translate into a reduction in fracture risk. To enhance any fracture-protective effects of physical activity, fracture prone regions within the proximal femur need to be targeted. RECENT FINDINGS: The proximal femur is designed to withstand forces in the weight-bearing direction, but less so forces associated with falls in a sideways direction. Sideways falls heighten femoral neck fracture risk by loading the relatively weak superolateral region of femoral neck. Recent studies exploring regional adaptation of the femoral neck to physical activity have identified heterogeneous adaptation, with adaptation principally occurring within inferomedial weight-bearing regions and little to no adaptation occurring in the superolateral femoral neck. There is a need to develop novel physical activities that better target and strengthen the superolateral femoral neck within the proximal femur. Design of these activities may be guided by subject-specific musculoskeletal modeling and finite-element modeling approaches.

A staged approach using machine learning and uncertainty quantification to predict the risk of hip fracture.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. The study cohort included 547 patients, with 94 experiencing hip fracture. To assess the risk of hip fracture, clinical variables and clinical variables combined with hip DXA imaging features were evaluated as predictors, followed by a novel staged approach. Hip DXA imaging features included those extracted by convolutional neural networks (CNNs), shape measurements, and texture features. Two ensemble machine learning models were evaluated: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and imaging features) using the logistic regression as the base classifier and bootstrapping for ensemble learning. The staged approach was developed using uncertainty quantification from Ensemble 1 which was used to decide if hip DXA imaging features were necessary to improve prediction for each subject. Ensemble 2 exhibited the highest performance, achieving an Area Under the Curve (AUC) of 0.95, an accuracy of 0.92, a sensitivity of 0.81, and a specificity of 0.94. The staged model also performed well, with an AUC of 0.85, an accuracy of 0.86, a sensitivity of 0.56, and a specificity of 0.92, outperforming Ensemble 1, which had an AUC of 0.55, an accuracy of 0.73, a sensitivity of 0.20, and a specificity of 0.83. Furthermore, the staged model suggested that 54.49 % of patients did not require DXA scanning, effectively balancing accuracy and specificity, while offering a robust solution when DXA data acquisition is not feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of advanced modeling strategies. Our staged approach offers a cost-effective holistic view of patient health. It can identify individuals at risk of hip fracture with a high accuracy while reducing unnecessary DXA scans. This approach has great promise to guide the need for interventions to prevent hip fracture while reducing diagnostic cost and exposure to radiation.

A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture.

Hip fractures present a significant healthcare challenge, especially within aging populations, where they are often caused by falls. These fractures lead to substantial morbidity and mortality, emphasizing the need for timely surgical intervention. Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. We propose a novel staged model that combines advanced imaging and clinical data to improve predictive performance. By using convolutional neural networks (CNNs) to extract features from hip DXA images, along with clinical variables, shape measurements, and texture features, our method provides a comprehensive framework for assessing fracture risk. The study cohort included 547 patients, with 94 experiencing hip fracture. A staged machine learning-based model was developed using two ensemble models: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and DXA imaging features). This staged approach used uncertainty quantification from Ensemble 1 to decide if DXA features are necessary for further prediction. Ensemble 2 exhibited the highest performance, achieving an Area Under the Curve (AUC) of 0.9541, an accuracy of 0.9195, a sensitivity of 0.8078, and a specificity of 0.9427. The staged model also performed well, with an AUC of 0.8486, an accuracy of 0.8611, a sensitivity of 0.5578, and a specificity of 0.9249, outperforming Ensemble 1, which had an AUC of 0.5549, an accuracy of 0.7239, a sensitivity of 0.1956, and a specificity of 0.8343. Furthermore, the staged model suggested that 54.49% of patients did not require DXA scanning. It effectively balanced accuracy and specificity, offering a robust solution when DXA data acquisition is not always feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of the advanced modeling strategies. Our staged approach offers a cost-effective holistic view of patients' health. It could identify individuals at risk with a high accuracy but reduce the unnecessary DXA scanning. Our approach has great promise to guide interventions to prevent hip fractures with reduced cost and radiation.

Measuring bone mineral density with fat-water MRI: comparison with computed tomography.

PURPOSE: To develop a method for measuring bone mineral density (BMD) with MRI, and to validate this method against quantitative computed tomography (QCT). MATERIALS AND METHODS: A mathematical relationship between signal intensities from proton-density-weighted in-phase images generated by multi-fat-peak T2*-IDEAL MRI and BMD was derived using a set of calibration standards constructed from various concentrations of hydroxyapatite in water. Using these standards, the relationship between hydroxyapatite concentration and MRI signal intensity was examined. A T2*-IDEAL protocol was performed on the patella of 5 volunteers and the signal model was used to compute BMD of all voxels of the patella. The BMD data were validated by obtaining QCT scans of the same patella, computing QCT BMD of all voxels, and comparing the MRI and QCT BMD data by performing linear regression analysis on a voxel-by-voxel basis. RESULTS: A strong linear correlation between hydroxyapatite concentration of the calibration standards and MRI signal intensities was observed (r = 0.98; P < 0.01). In the patella, BMD measurements (N = 28796 voxels) from the MRI signal model were significantly correlated with those from QCT (r = 0.82; P < 0.001; slope = 1.02; and intercept = -0.26). CONCLUSION: A standardized phantom consisting of hydroxyapatite and water can be used to accurately quantify BMD in vivo using MRI.

The influence of isolated femur and tibia rotations on patellar tendon stress: A sensitivity analysis using finite element analysis.

The purpose of this study was to determine the influence of frontal and transverse plane rotations of the femur and tibia on peak maximum principal stress in the patellar tendon. Using finite element modeling, patellar tendon stress profiles of eight healthy individuals were obtained during a simulated squatting task (45° of knee flexion). The femur and tibia of each model were rotated 10° (in 2° increments) along their respective axes beyond that of the natural degree of rotation. This process was repeated for the transverse plane (internal and external rotation) and frontal plane (adduction and abduction). Quasi-static loading simulations were performed to quantify peak maximum principal stress in patellar tendon. Internal and external rotations of the femur and tibia that exceeded 4° beyond that of the natural rotation resulted in progressively greater patellar tendon stress (p < 0.05). Incremental femur and tibia adduction and abduction resulted in an increase in patellar tendon stress, but only at the end range of motions evaluated. These results suggest that tibiofemoral rotations in the frontal and transverse planes have the potential to influence patellar tendon stress. In particular, patellar tendon stress is highly sensitive to small degrees of tibia and/or femur motions in the transverse plane.

Persons with Patellar Tendinopathy Exhibit Greater Patellar Tendon Stress during a Single-Leg Landing Task.

PURPOSE: This study aimed to compare peak maximum principal stress in the patellar tendon between persons with and without patellar tendinopathy during a simulated single-leg landing task. A secondary purpose was to determine the biomechanical predictor(s) of peak maximum principal stress in the patellar tendon. METHODS: Using finite element (FE) modeling, patellar tendon stress profiles of 28 individuals (14 with patellar tendinopathy and 14 pain-free controls) were created at the time of the peak knee extensor moment during single-leg landing. Input parameters to the FE model included subject-specific knee joint geometry and kinematics, and quadriceps muscle forces. Independent t -tests were used to compare the peak maximum principal stress in the patellar tendon and biomechanical variables used as input variables to the FE model (knee flexion, knee rotation in the frontal and transverse planes and the peak knee extensor moment) between groups. A stepwise regression model was used to determine the biomechanical predictor(s) of peak maximum principal stress in the patellar tendon for both groups combined. RESULTS: Compared with the control group, persons with patellar tendinopathy exhibited greater peak maximum principal stress in the patellar tendon (77.4 ± 25.0 vs 60.6 ± 13.6 MPa, P = 0.04) and greater tibiofemoral joint internal rotation (4.6° ± 4.6° vs 1.1° ± 4.2°, P = 0.04). Transverse plane rotation of the tibiofemoral joint was the best predictor of peak maximum principal stress in the patellar tendon ( r = 0.51, P = 0.01). CONCLUSIONS: Persons with patellar tendinopathy exhibit greater peak patellar tendon stress compared with pain-free individuals during single-leg landing. The magnitude of peak patellar tendon stress seems to be influenced by the amount of tibiofemoral rotation in the transverse plane.

Multi-view information fusion using multi-view variational autoencoder to predict proximal femoral fracture load.

Background: Hip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or "strength") and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Results: We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. Conclusion: The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for predicting FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation exposure from QCT.

ST-V-Net: incorporating shape prior into convolutional neural networks for proximal femur segmentation.

We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the entire cohort and then for male and female subjects separately, 90% of the subjects were used in ten-fold stratified cross-validation for training and the rest of the subjects were used to evaluate the performance of models. In the entire cohort, the proposed model achieved a Dice similarity coefficient (DSC) of 0.9888, a sensitivity of 0.9966 and a specificity of 0.9988. Compared with V-Net, the Hausdorff distance was reduced from 9.144 to 5.917 mm, and the average surface distance was reduced from 0.012 to 0.009 mm using the proposed ST-V-Net. Quantitative evaluation demonstrated excellent performance of the proposed ST-V-Net for automatic proximal femur segmentation in QCT images. In addition, the proposed ST-V-Net sheds light on incorporating shape prior to segmentation to further improve the model performance.

The feasibility study of XACT imaging for characterizing osteoporosis.

BACKGROUND: Osteoporosis is a progressive bone disease that is characterized by a decrease in bone mass and the deterioration in bone microarchitecture, which might be related to age and space travel. An unmet need exists for the development of novel imaging technologies to characterize osteoporosis. PURPOSE: The purpose of our study is to investigate the feasibility of X-ray-induced acoustic computed tomography (XACT) imaging for osteoporosis detection. METHODS: An in-house simulation workflow was developed to assess the ability of XACT for osteoporosis detection. To evaluate this simulation workflow, a three-dimensional digital bone phantom for XACT imaging was created by a series of two-dimensional micro-computed tomography (micro-CT) slices of normal and osteoporotic bones in mice. In XACT imaging, the initial acoustic pressure rise caused by the X-ray induce acoustic (XA) effect is proportional to bone density. First, region growing was deployed for image segmentation of different materials inside the bone. Then k-wave simulations were deployed to model XA wave propagation, attenuation, and detection. Finally, the time-varying pressure signals detected at each transducer location were used to reconstruct the XACT image with a time-reversal reconstruction algorithm. RESULTS: Through the simulated XACT images, cortical porosity has been calculated, and XA signal spectra slopes have been analyzed for the detection of osteoporosis. The results have demonstrated that osteoporotic bones have lower bone mineral density and higher spectra slopes. These findings from XACT images were in good agreement with porosity calculation from micro-CT images. CONCLUSION: This work explores the feasibility of using XACT imaging as a new imaging tool for Osteoporosis detection. Considering that acoustic signals are generated by X-ray absorption, XACT imaging can be combined with traditional X-ray imaging that holds potential for clinical management of osteoporosis and other bone diseases.

A preliminary safety assessment of vertebral augmentation with32P brachytherapy bone cement.

Comprehensive treatment for vertebral metastatic lesions commonly involves vertebral augmentation (vertebroplasty or kyphoplasty) to relieve pain and stabilize the spine followed by multiple sessions of radiotherapy. We propose to combine vertebral augmentation and radiotherapy into a single treatment by adding32P, aß-emitting radionuclide, to bone cement, thereby enabling spinal brachytherapy to be performed without irradiating the spinal cord. The goal of this study was to address key dosimetry and safety questions prior to performing extensive animal studies. The32P was in the form of hydroxyapatite powder activated by neutron bombardment in a nuclear reactor. We performedex vivodosimetry experiments to establish criteria for safe placement of the cement within the sheep vertebral body. In anin vivostudy, we treated three control ewes and three experimental ewes with brachytherapy cement containing 2.23-3.03 mCi32P ml-1to identify the preferred surgical approach, to determine if32P leaches from the cement and into the blood, urine, or feces, and to identify unexpected adverse effects. Ourex vivoexperiments showed that cement with 4 mCi32P ml-1could be safely implanted in the vertebral body if the cement surface is at least 4 mm from the spinal cord in sheep and 5 mm from the spinal cord in humans.In vivo, a lateral retroperitoneal surgical approach, ventral to the transverse processes, was identified as easy to perform while allowing a safe distance to the spinal cord. The blood, urine, and feces of the sheep did not contain detectable levels of32P, and the sheep did not experience any neurologic or other adverse effects from the brachytherapy cement. These results demonstrate, on a preliminary level, the relative safety of this brachytherapy cement and support additional development and testing.

Physical activity induced adaptation can increase proximal femur strength under loading from a fall onto the greater trochanter.

Physical activity enhances proximal femur bone mass, but it remains unclear whether the benefits translate into an enhanced ability to resist fracture related loading. We recently used baseball pitchers as a within-subject controlled model to demonstrate physical activity induced proximal femur adaptation in regions associated with weight bearing and increased strength under single-leg stance loading. However, there was no measurable benefit to resisting common injurious loading (e.g. a fall onto the greater trochanter). A lack of power and a small physical activity effect size may have contributed to the latter null finding. Softball pitchers represent an alternative within-subject controlled model to explore adaptation of the proximal femur to physical activity, exhibiting greater dominant-to-nondominant (D-to-ND) leg differences than baseball pitchers. The current study used quantitative computed tomography, statistical parametric mapping, and subject-specific finite element (FE) modeling to explore adaptation of the proximal femur to physical activity in female softball pitchers (n = 25). Female cross-country runners (n = 15) were included as symmetrically loaded controls, showing very limited D-to-ND leg differences. Softball pitchers had D-to-ND leg differences in proximal femur, femoral neck, and trochanteric volumetric bone mineral density and content, and femoral neck volume. Voxel-based morphometry analyses and cortical bone mapping showed D-to-ND leg differences within a large region connecting the superior femoral head, inferior femoral neck and medial intertrochanteric region, and within the greater trochanter. FE modeling revealed pitchers had 19.4% (95%CI, 15.0 to 23.9%) and 4.9% (95%CI, 1.7 to 8.2%) D-to-ND leg differences in predicted ultimate strength under single-leg stance loading and a fall onto the greater trochanter, respectively. These data affirm the spatial and strength adaptation of the proximal femur to weight bearing directed loading and demonstrate that the changes can also have benefits, albeit smaller, on resisting loads associated with a sideways fall onto the greater trochanter.

Effect of cortical bone micro-structure in fragility fracture patients on lamellar stress.

This work investigates how changes in cortical bone microstructure alter the risk of fragility fractures. The secondary osteons of non-osteoporotic (by DXA) women with fragility fractures have reduced lamellar width and greater areas of birefringent brightness in transverse sections, a pathological condition. We used hierarchical finite element (FE) models of the proximal femur of two women aged 67 and 88 (younger and older) during one-legged stance. At specific locations of the anterior-inferior neck (ROI), we analyzed micro-models containing osteons comprised of alternating birefringent extinct and bright lamellae. The plane of lamellar isotropy (XY) was transverse to the osteon longitudinal axis (Z) which was parallel to the femoral neck axis. To evaluate changes in fracture risk with changes in microstructure, we investigated principal and von Mises stresses, and planar stress measures that accounted for transverse isotropy. For both younger and older femurs, 48% to 100% of stress measures were larger in models with healthy architecture than in models with pathological architecture, while controlling for type of lamella and osteon. These findings suggest that bone adaptation reduces stress at most pathological lamellar sites. However, in the bright lamellae of the younger femur, the pathological tensile, compressive and distortional stresses in the transverse plane and distortional stress in the longitudinal planes were larger than the non-negligible corresponding stresses in 6 of the 28 osteon models with healthy architecture, in 5 of the 7 locations. Therefore, a minority of sites with pathological architecture present greater stress, and therefore, greater fracture risk.

Heterogeneous Spatial and Strength Adaptation of the Proximal Femur to Physical Activity: A Within-Subject Controlled Cross-Sectional Study.

Physical activity (PA) enhances proximal femur bone mass, as assessed using projectional imaging techniques. However, these techniques average data over large volumes, obscuring spatially heterogeneous adaptations. The current study used quantitative computed tomography, statistical parameter mapping, and subject-specific finite element (FE) modeling to explore spatial adaptation of the proximal femur to PA. In particular, we were interested in adaptation occurring at the superior femoral neck and improving strength under loading from a fall onto the greater trochanter. High/long jump athletes (n = 16) and baseball pitchers (n = 16) were utilized as within-subject controlled models as they preferentially load their take-off leg and leg contralateral to their throwing arm, respectively. Controls (n = 15) were included but did not show any dominant-to-nondominant (D-to-ND) leg differences. Jumping athletes showed some D-to-ND leg differences but less than pitchers. Pitchers had 5.8% (95% confidence interval [CI] 3.9%-7.6%) D-to-ND leg differences in total hip volumetric bone mineral density (vBMD), with increased vBMD in the cortical compartment of the femoral neck and trochanteric cortical and trabecular compartments. Voxel-based morphometry analyses and cortical bone mapping showed pitchers had D-to-ND leg differences within the regions of the primary compressive trabeculae, inferior femoral neck, and greater trochanter but not the superior femoral neck. FE modeling revealed pitchers had 4.1% (95% CI 1.4%-6.7%) D-to-ND leg differences in ultimate strength under single-leg stance loading but no differences in ultimate strength to a fall onto the greater trochanter. These data indicate the asymmetrical loading associated with baseball pitching induces proximal femur adaptation in regions associated with weight bearing and muscle contractile forces and increases strength under single-leg stance loading. However, there were no benefits evident at the superior femoral neck and no measurable improvement in ultimate strength to common injurious loading during aging (ie, fall onto the greater trochanter), raising questions as to how to better target these variables with PA. © 2019 American Society for Bone and Mineral Research.

Quantitative computed tomography reveals the effects of race and sex on bone size and trabecular and cortical bone density.

To examine the effects of race and sex on bone density and geometry at specific sites within the proximal femur and lumbar spine, we used quantitative computed tomography to image 30 Caucasian American (CA) men, 25 African American (AA) men, 30 CA women, and 17 AA women aged 35-45 yr. Volumetric integral bone mineral density (BMD), trabecular BMD (tBMD), and cross sectional area were measured in the femoral neck, trochanter, total femur, and L1/L2 vertebrae. Volumetric cortical BMD (cBMD) was also measured in the femur regions of interest. Differences were ascertained using a multivariate regression model. Overall, AA subjects had denser bones than CA subjects, but there were no racial differences in bone size. Men had larger femoral necks but not larger vertebrae than women. The AA men had higher tBMD and cBMD in the femur than CA men, whereas AA women had higher femoral tBMD but not higher femoral cBMD than CA women. These data support the idea that higher hip fracture rates in women compared with men are associated with smaller bone size. Lower fracture rates in AA elderly compared with CA elderly are consistent with higher peak bone density, particularly in the trabecular compartment, and potentially lower rates of age-related bone loss rather than larger bone size.

Effect of an UHMWPE patellar component on stress fields in the patella: a finite element analysis.

An increased stress in the patella due to the implantation of a patellar button may also be another potential source of pain in total knee arthroplasty patients. This study assessed the location inside the patella having largest stress change after implantation of an ultra high molecular polyethylene patella button. Finite elements models of the patellae before and after implantation of patellar button were created. Experimentally determined spring constants of muscles and ligaments, and patellofemoral contacting loads were applied to the models at 30 degrees , 60 degrees , and 90 degrees of knee flexion. The Von Mises stress of the intact patella decreased with increased knee flexion, while that of implanted patella increased. Also, the stress range in the implanted patella was 3-9 times higher than in the intact one. The highly stressed region of the intact patella moved proximally with higher knee flexion angles, while that of the implanted model stayed near the central anterior patella. At 90 degrees of knee flexion, the stress in the anterodistal patella increased considerably after implantation of a patella button so that the anterodistal patella may be susceptible to be painful source after the total knee replacement.

Hip load capacity cut-points for Astronaut Skeletal Health NASA Finite Element Strength Task Group Recommendations.

Concerns raised at a 2010 Bone Summit held for National Aeronautics and Space Administration Johnson Space Center led experts in finite element (FE) modeling for hip fracture prediction to propose including hip load capacity in the standards for astronaut skeletal health. The current standards for bone are based upon areal bone mineral density (aBMD) measurements by dual X-ray absorptiometry (DXA) and an adaptation of aBMD cut-points for fragility fractures. Task Group members recommended (i) a minimum permissible outcome limit (POL) for post-mission hip bone load capacity, (ii) use of FE hip load capacity to further screen applicants to astronaut corps, (iii) a minimum pre-flight standard for a second long-duration mission, and (iv) a method for assessing which post-mission physical activities might increase an astronaut's risk for fracture after return. QCT-FE models of eight astronaut were analyzed using nonlinear single-limb stance (NLS) and posterolateral fall (NLF) loading configurations. QCT data from the Age Gene/Environment Susceptibility (AGES) Reykjavik cohort and the Rochester Epidemiology Project were analyzed using identical modeling procedures. The 75th percentile of NLS hip load capacity for fractured elderly males of the AGES cohort (9537N) was selected as a post-mission POL. The NLF model, in combination with a Probabilistic Risk Assessment tool, was used to assess the likelihood of exceeding the hip load capacity during post-flight activities. There was no recommendation to replace the current DXA-based standards. However, FE estimation of hip load capacity appeared more meaningful for younger, physically active astronauts and was recommended to supplement aBMD cut-points.