Multi-level patient-specific modelling of the proximal femur. A promising tool to quantify the effect of osteoporosis treatment

Decreased stress shielding with a PEEK femoral total knee prosthesis measured in validated computational models

Due to their high stiffness, metal femoral implants in total knee arthroplasty may cause stress shielding of the peri-prosthetic bone, which can lead to loss of bone stock. Using a polymer (PEEK) femoral implant reduces the stiffness mismatch between implant and bone, and therefore has the potential to decrease strain shielding. The goal of the current study was to evaluate this potential benefit of PEEK femoral components in cadaveric experiments. Cadaveric femurs were loaded in a materials testing device, while a 3-D digital image correlation set-up captured strains on the surface of the intact femurs and femurs implanted with PEEK and CoCr components. These experimental results were used to validate specimen-specific finite element models, which subsequently were used to assess the effect of metal and PEEK femoral components on the bone strain energy density. The finite element models showed strain maps that were highly comparable to the experimental measurements. The PEEK implant increased strain energy density, relative to the preoperative bone and compared to CoCr. This was most pronounced in the regions directly under the implant and near load contact sites. These data confirm the hypothesis that a PEEK femoral implant can reduce peri-prosthetic stress shielding.

Finite element models for fracture prevention in patients with metastatic bone disease. A literature review

Patients with bone metastases have an increased risk to sustain a pathological fracture as lytic metastatic lesions damage and weaken the bone. In order to prevent fractures, prophylactic treatment is advised for patients with a high fracture risk. Mechanical stabilization of the femur can be provided through femoroplasty, a minimally invasive procedure where bone cement is injected into the lesion, or through internal fixation with intra- or extramedullary implants. Clinicians face the task of determining whether or not prophylactic treatment is required and which treatment would be the most optimal. Finite element (FE) models are promising tools that could support this decision process. The aim of this paper is to provide an overview of the state-of-the-art in FE modeling for the treatment decision of metastatic bone lesions in the femur. First, we will summarize the clinical and mechanical results of femoroplasty as a prophylactic treatment method. Secondly, current FE models for fracture risk assessment of metastatic femurs will be reviewed and the remaining challenges for clinical implementation will be discussed. Thirdly, we will elaborate on the simulation of femoroplasty in FE models and discuss future opportunities. Femoroplasty has already proven to effectively relieve pain and improve functionality, but there remains uncertainty whether it provides sufficient mechanical strengthening to prevent pathological fractures. FE models could help to select appropriate candidates for whom femoroplasty provides sufficient increase in strength and to further improve the mechanical benefit by optimizing the locations for cement augmentation.

Nonlinear voxel-based finite element model for strength assessment of healthy and metastatic proximal femurs

Nonlinear finite element (FE) models can accurately quantify bone strength in healthy and metastatic femurs. However, their use in clinical practice is limited since state-of-the-art implementations using tetrahedral meshes involve a lot of manual work for which specific modelling software and engineering knowledge are required. Voxel-based meshes could enable the transition since they are robust and can be highly automated. Therefore, the aim of this work was to bridge the modelling gap between the tetrahedral and voxel-based approach. Specifically, we validated a nonlinear voxel-based FE method relative to experimental data from 20 femurs with and without artificial metastases that had been mechanically loaded until failure. CT scans of the femurs were segmented and automatically converted into a voxel-based mesh with hexahedral elements. Nonlinear material properties were implemented in an open-source linear voxel-based FE solver by adding an additional loop to the routine such that the material properties could be adapted after each increment. Bone strength, quantified as the maximum force in the force-displacement curve, was evaluated. The results were compared to a previously established nonlinear tetrahedral FE approach as well as to the experimentally measured bone strength. The voxel-based FE model predicted the experimental bone strength very well both for healthy (R² = 0.90, RMSE = 0.88 kN) and metastatic femurs (R² = 0.93, RMSE = 0.64 kN). The model precision and accuracy were very similar to the ones obtained with the tetrahedral model (R² = 0.90/0.93, RMSE = 0.90/0.64 kN for intact/metastatic respectively). The more intuitive voxel-based meshes thus quantified macroscale femoral strength equally well as state-of-the-art tetrahedral models. The robustness, high level of automation and time-efficiency (< 30 min) of the implemented workflow offer great potential for developing FE models to improve fracture risk prediction in clinical practice.

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A nonlinear voxel-based FE model was evaluated to assess femoral bone strength

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Both healthy and metastatic femurs were evaluated

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The FE models predicted bone strength with high accuracy and precision

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Voxel-based and tetrahedral FE models showed similar accuracy and precision

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An iterative routine enabled material nonlinearity in a linear FE solver

Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey

This paper provides a starting point for researchers and practitioners from biology, medicine, physics and engineering who can benefit from an up-to-date literature survey on patient-specific bone fracture modelling, simulation and risk analysis. This survey hints at a framework for devising realistic patient-specific bone fracture simulations. This paper has 18 sections: Section 1 presents the main interested parties; Section 2 explains the organzation of the text; Section 3 motivates further work on patient-specific bone fracture simulation; Section 4 motivates this survey; Section 5 concerns the collection of bibliographical references; Section 6 motivates the physico-mathematical approach to bone fracture; Section 7 presents the modelling of bone as a continuum; Section 8 categorizes the surveyed literature into a continuum mechanics framework; Section 9 concerns the computational modelling of bone geometry; Section 10 concerns the estimation of bone mechanical properties; Section 11 concerns the selection of boundary conditions representative of bone trauma; Section 12 concerns bone fracture simulation; Section 13 presents the multiscale structure of bone; Section 14 concerns the multiscale mathematical modelling of bone; Section 15 concerns the experimental validation of bone fracture simulations; Section 16 concerns bone fracture risk assessment. Lastly, glossaries for symbols, acronyms, and physico-mathematical terms are provided.

Assessment of finite element models for prediction of osteoporotic fracture

With increasing life expectancy and mortality rates, the burden of osteoporotic hip fractures is continually on an upward trend. In terms of prevention, there are several osteoporosis treatment strategies such as anti-resorptive drug treatments, which attempt to retard the rate of bone resorption, while promoting the rate of formation. With respect to prediction, several studies have provided insights into obtaining bone strength by non-invasive means through the application of FE analysis. However, what valuable information can we obtain from FE studies that have focused on osteoporosis research, with respect to the prediction of osteoporotic fractures? This paper aims to fine studies that have used FE analysis to predict fractures in the proximal femur through a systematic search of literature using PUBMED, with the main objective of supporting the diagnosis of osteoporosis. The focus of these FE studies is first discussed, and the methodological aspects are summarized, by mainly comparing and contrasting their meshing properties, material properties, and boundary conditions. The implications of these methodological differences in FE modelling processes and propositions with the aim of consolidating or minimalizing these differences are further discussed. We proved that studies need to start converging in terms of their input parameters to make the FE method applicable to clinical settings. This, in turn, will decrease the time needed for in vitro tests. Current advancements in FE analysis need to be consolidated before any further steps can be taken to implement engineering analysis into the clinical scenario.

Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians?: Towards computational modelling in daily clinical practice

OBJECTIVES

In this prospective cohort study, we investigated whether patient-specific finite element (FE) models can identify patients at risk of a pathological femoral fracture resulting from metastatic bone disease, and compared these FE predictions with clinical assessments by experienced clinicians.

METHODS

A total of 39 patients with non-fractured femoral metastatic lesions who were irradiated for pain were included from three radiotherapy institutes. During follow-up, nine pathological fractures occurred in seven patients. Quantitative CT-based FE models were generated for all patients. Femoral failure load was calculated and compared between the fractured and non-fractured femurs. Due to inter-scanner differences, patients were analyzed separately for the three institutes. In addition, the FE-based predictions were compared with fracture risk assessments by experienced clinicians.

RESULTS

In institute 1, median failure load was significantly lower for patients who sustained a fracture than for patients with no fractures. In institutes 2 and 3, the number of patients with a fracture was too low to make a clear distinction. Fracture locations were well predicted by the FE model when compared with post-fracture radiographs. The FE model was more accurate in identifying patients with a high fracture risk compared with experienced clinicians, with a sensitivity of 89% versus 0% to 33% for clinical assessments. Specificity was 79% for the FE models versus 84% to 95% for clinical assessments.

CONCLUSION

FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease. Future work in a larger patient population should confirm the higher predictive power of FE models compared with current clinical guidelines.Cite this article: F. Eggermont, L. C. Derikx, N. Verdonschot, I. C. M. van der Geest, M. A. A. de Jong, A. Snyers, Y. M. van der Linden, E. Tanck. Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modelling in daily clinical practice. Bone Joint Res 2018;7:430-439. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2.

Study of stress variations in single-stance and sideways fall using image-based finite element analysis

Image-based finite element analysis (FEA) has been considered an effective computational tool to predict hip fracture risk. The patient specific FEA gives an insight into the inclusive effect of three-dimensional (3D) complex bone geometry, and the distribution of inhomogeneous isotropic material properties in conjunction with loading conditions. The neck region of a femur is primarily the weakest in which fracture is likely to happen, when someone falls. A sideways fall results in the development of greater tensile and compressive stresses, respectively, in the inferior and superior aspects of the femoral neck, whereas the state of stress is reversed in usual gait or stance configuration. Herein, the variations of stresses have been investigated at the femoral neck region considering both single-stance and sideways fall. Finite element models of ten human femora have been generated using Quantitative Computed Tomography (QCT) scan datasets and have been simulated with an equal magnitude of load applied to the aforementioned configurations. Fracture risk indicator, defined as the ratio of the maximum compressive or tensile stress computed at the superior and inferior surfaces to the corresponding yield stress, has been used in this work to measure the variations of fracture risk between single-stance and sideways fall. The average variations of the fracture risk indicators between the fall and stance are at least 24.3% and 8% at the superior and inferior surfaces, respectively. The differences may interpret why sideways fall is more dangerous for the elderly people, causing hip fracture.

Comparison of proximal femur and vertebral body strength improvements in the FREEDOM trial using an alternative finite element methodology

Denosumab reduced the incidence of new fractures in postmenopausal women with osteoporosis by 68% at the spine and 40% at the hip over 36 months compared with placebo in the FREEDOM study. This efficacy was supported by improvements from baseline in vertebral (18.2%) strength in axial compression and femoral (8.6%) strength in sideways fall configuration at 36 months, estimated in Newtons by an established voxel-based finite element (FE) methodology. Since FE analyses rely on the choice of meshes, material properties, and boundary conditions, the aim of this study was to independently confirm and compare the effects of denosumab on vertebral and femoral strength during the FREEDOM trial using an alternative smooth FE methodology. Unlike the previous FE study, effects on femoral strength in physiological stance configuration were also examined. QCT data for the proximal femur and two lumbar vertebrae were analyzed by smooth FE methodology at baseline, 12, 24, and 36 months for 51 treated (denosumab) and 47 control (placebo) subjects. QCT images were segmented and converted into smooth FE models to compute bone strength. L1 and L2 vertebral bodies were virtually loaded in axial compression and the proximal femora in both fall and stance configurations. Denosumab increased vertebral body strength by 10.8%, 14.0%, and 17.4% from baseline at 12, 24, and 36 months, respectively (p<0.0001). Denosumab also increased femoral strength in the fall configuration by 4.3%, 5.1%, and 7.2% from baseline at 12, 24, and 36 months, respectively (p<0.0001). Similar improvements were observed in the stance configuration with increases of 4.2%, 5.2%, and 5.2% from baseline (p≤0.0007). Differences between the increasing strengths with denosumab and the decreasing strengths with placebo were significant starting at 12 months (vertebral and femoral fall) or 24 months (femoral stance). Using an alternative smooth FE methodology, we confirmed the significant improvements in vertebral body and proximal femur strength previously observed with denosumab. Estimated increases in strength with denosumab and decreases with placebo were highly consistent between both FE techniques.

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.

Study of DXA-derived lateral-medial cortical bone thickness in assessing hip fracture risk

The currently available clinical tools have limited accuracy in predicting hip fracture risk in individuals. We investigated the possibility of using normalized cortical bone thickness (NCBT) estimated from the patient's hip DXA (dual energy X-ray absorptiometry) as an alternative predictor of hip fracture risk. Hip fracture risk index (HFRI) derived from subject-specific DXA-based finite element model was used as a guideline in constructing the mathematical expression of NCBT. We hypothesized that if NCBT has stronger correlations with HFRI than the single risk factors such as areal BMD (aBMD), then NCBT can be a better predictor. The hypothesis was studied using 210 clinical cases, including 60 hip fracture cases, obtained from the Manitoba Bone Mineral Density Database. The results showed that, in general HFRI has much stronger correlations with NCBT than any of the single risk factors; the strongest correlation was observed at the superior side of the narrowest femoral neck with r² = 0.81 (p < 0.001), which is much higher than the correlation with femoral aBMD, r² = 0.50 (p < 0.001). The capability of aBMD, NCBT, and HFRI in discriminating the hip fracture cases from the non-fracture ones, expressed as the area under the curve with 95% confidence interval, AUC (95% CI), is respectively 0.627 (0.593–0.657), 0.714 (0.644–0.784) and 0.839 (0.787–0.892). The short-term repeatability of aBMD, NCBT, and HFRI, measured by the coefficient of variation (CV, %), was found to be in the range of (0.64–1.22), (1.93–3.41), (3.10–4.16), respectively. We thus concluded that NCBT is potentially a better predictor of hip fracture risk.

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A new algorithm developed for estimating cortical bone thickness from clinical DXA images.

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Validation of the algorithm with QCT Pro, a commercial software for processing QCT scans.

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A more effective risk predictor constructed from finite element studies.

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The risk predictor can be readily integrated into the current clinical procedure.

3D scanning SAXS: a novel method for the assessment of bone ultrastructure orientation

The arrangement and orientation of the ultrastructure plays an important role for the mechanical properties of inhomogeneous and anisotropic materials, such as polymers, wood, or bone. However, there is a lack of techniques to spatially resolve and quantify the material's ultrastructure orientation in a macroscopic context. In this study, a new method is presented, which allows deriving the ultrastructural 3D orientation in a quantitative and spatially resolved manner. The proposed 3D scanning small-angle X-ray scattering (3D sSAXS) method was demonstrated on a thin trabecular bone specimen of a human vertebra. A micro-focus X-ray beam from a synchrotron radiation source was used to raster scan the sample for different rotation angles. Furthermore, a mathematical framework was developed, validated and employed to describe the relation between the SAXS data for the different rotation angles and the local 3D orientation and degree of orientation (DO) of the bone ultrastructure. The resulting local 3D orientation was visualized by a 3D orientation map using vector fields. Finally, by applying the proposed 3D scanning SAXS method on consecutive bone sections, a 3D map of the local orientation of a complete trabecular element could be reconstructed for the first time. The obtained 3D orientation map provided information on the bone ultrastructure organization and revealed links between trabecular bone microarchitecture and local bone ultrastructure. More specifically, we observed that trabecular bone ultrastructure is organized in orientation domains of tens of micrometers in size. In addition, it was observed that domains with a high DO were more likely to be found near the surface of the trabecular structure, and domains with lower DO (or transition zones) were located in-between the domains with high DO. The method reproducibility was validated by comparing the results obtained when scanning the sample under different sample tilt angles. 3D orientation maps such as the ones created using 3D scanning SAXS will help to quantify and understand structure-function relationships between bone ultrastructure and bone mechanics. Beyond that, the proposed method can also be used in other research fields such as material sciences, with the aim to locally determine the 3D orientation of material components.

Quantification of trabecular spatial orientation from low-resolution images

No accepted methodology exists to assess trabecular bone orientation from clinical CT scans. The aim of this study was to test the hypothesis that the distribution of grey values in clinical CT images is related to the underlying trabecular architecture and that this distribution can be used to identify the principal directions and local anisotropy of trabecular bone. Fourteen trabecular bone samples were extracted from high-resolution (30 μm) micro-CT scans of seven human femoral heads. Trabecular orientations and local anisotropy were calculated using grey-level deviation (GLD), a novel method providing a measure of the three-dimensional distribution of image grey values. This was repeated for different image resolutions down to 300 μm and for volumes of interest (VOIs) ranging from 1 to 7 mm. Outcomes were compared with the principal mechanical directions and with mean intercept length (MIL) as calculated for the segmented 30-μm images. For the 30-μm images, GLD predicted the mechanical principal directions equally well as MIL. For the 300-μm images, which are resolutions that can be obtained in vivo using clinical CT, only a small increase (3°-6°) in the deviation from the mechanical orientations was found. VOIs of 5 mm resulted in a robust quantification of the orientation. We conclude that GLD can quantify structural bone parameters from low-resolution CT images.

Patient-specific modelling of bone and bone-implant systems: the challenges

In the past three decades, finite element (FE) modelling has provided considerable understanding to the area of musculoskeletal biomechanics. However, most of this understanding has been generated using generic, standardised or idealised models. Patient-specific modelling (PSM) is almost never used for making clinical decisions. Imaging technologies have made it possible to create patient-specific geometries and FE meshes for modelling. While these have brought us closer to PSM, several challenges associated with the definition of material properties, loads, boundary conditions and interaction between components still need to be overcome. This study reviews the current status of PSM with respect to defining material behaviour and prescribing boundary conditions and interactions. With regard to the constitutive modelling of bone, it is seen that imaging is being increasingly used to define elastic properties (isotropic as well as anisotropic). However, the post-elastic and time-dependent behaviour, important for several modelling situations, is mostly obtained from in vitro experiments. Strain-based plasticity, not commonly available in FE codes, appears to have the potential of reducing an element of patient-specificity in modelling the yielding behaviour of bone. PSM of real boundary conditions that include muscles and ligaments continues to remain a challenge; many clinically relevant questions can be, however, answered without their inclusion. Simulation techniques to undertake PSM of interactions between bone and uncemented implants are available. Interference fit employed in both joint replacement fracture treatments induces considerable preload whose inclusion in models is important for the prediction of interface behaviour.

A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro

PURPOSE

Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios.

METHODS

Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared.

RESULTS

In both configurations, hvFE models predicted both stiffness (R(2)=0.82 for STANCE and R(2)=0.74 for SIDE) and femoral ultimate load (R(2)=0.80 for STANCE and R(2)=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head.

CONCLUSIONS

The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.

The assessment of the risk of fracture in femora with metastatic lesions

Previously, we showed that case-specific non-linear finite element (FE) models are better at predicting the load to failure of metastatic femora than experienced clinicians. In this study we improved our FE modelling and increased the number of femora and characteristics of the lesions. We retested the robustness of the FE predictions and assessed why clinicians have difficulty in estimating the load to failure of metastatic femora. A total of 20 femora with and without artificial metastases were mechanically loaded until failure. These experiments were simulated using case-specific FE models. Six clinicians ranked the femora on load to failure and reported their ranking strategies. The experimental load to failure for intact and metastatic femora was well predicted by the FE models (R2 = 0.90 and R2 = 0.93, respectively). Ranking metastatic femora on load to failure was well performed by the FE models (τ = 0.87), but not by the clinicians (0.11 < τ < 0.42). Both the FE models and the clinicians allowed for the characteristics of the lesions, but only the FE models incorporated the initial bone strength, which is essential for accurately predicting the risk of fracture. Accurate prediction of the risk of fracture should be made possible for clinicians by further developing FE models.

A preliminary dual-energy X-ray absorptiometry-based finite element model for assessing osteoporotic hip fracture risk

To more accurately assess osteoporotic hip fracture risk in a specific patient, a dual-energy X-ray absorptiometry (DXA)-based finite element model was constructed from the patient’s femur DXA image. The outermost contour of the femur bone segmented from the DXA image was used to generate a finite element mesh. Bone mechanical properties, such as Young’s modulus, are correlated with areal bone mineral density (BMD) captured in the DXA image. A quasi-static loading condition representing a sideway fall was applied to the finite element model. Three fracture risk indices were introduced and expressed as ratios of internal forces caused by impact forces occurring in sideway fall to bone ultimate cross-section strength at the three critical locations, i.e. the femoral neck, the intertrochanteric region, and the subtrochanteric region. The proposed finite element modelling procedure was validated against six representative clinical cases extracted from the Manitoba BMD database, where initial and follow-up DXA images have been taken to monitor longitudinal variation of areal BMD in individual patients. It was found from the clinical validation that variations in the proposed fracture risk indices have the same trends as those indicated by the conventional areal BMD and T-score. In addition, by the three proposed fracture risk indices it is possible to further identify the specific fracture location. It was also found that for the same subject, the variations in the three fracture risk indices have quite different magnitudes, with intertrochanteric region the largest and subtrochanteric region the smallest, which is probably owing to the different content of trabecular and cortical bones in the three regions. With further development, it is promising that the proposed DXA-based finite element model will be a useful tool for accurate assessment of osteoporosis development and for treatment monitoring.

Implementation of asymmetric yielding in case-specific finite element models improves the prediction of femoral fractures

Although asymmetric yielding in bone is widely shown in experimental studies, previous case-specific non-linear finite element (FE) studies have mainly adopted material behaviour using the Von Mises yield criterion (VMYC), assuming equal bone strength in tension and compression. In this study, it was verified that asymmetric yielding in FE models can be captured using the Drucker-Prager yield criterion (DPYC), and can provide better results than simulations using the VMYC. A sensitivity analysis on parameters defining the DPYC (i.e. the degree of yield asymmetry and the yield stress settings) was performed, focusing on the effect on bone failure. In this study, the implementation of a larger degree of yield asymmetry improved the prediction of the fracture location; variations in the yield stress mainly affected the predicted failure force. We conclude that the implementation of asymmetric yielding in case-specific FE models improves the prediction of femoral bone strength.

Anatomic variation in the elastic inhomogeneity and anisotropy of human femoral cortical bone tissue is consistent across multiple donors

Numerical models commonly account for elastic inhomogeneity in cortical bone using power-law scaling relationships with various measures of tissue density, but limited experimental data exists for anatomic variation in elastic anisotropy. A recent study revealed anatomic variation in the magnitude and anisotropy of elastic constants along the entire femoral diaphysis of a single human femur (Espinoza Orías et al., 2009). The objective of this study was to confirm these trends across multiple donors while also considering possible confounding effects of the anatomic quadrant, apparent tissue density, donor age, and gender. Cortical bone specimens were sampled from the whole femora of 9 human donors at 20%, 50%, and 80% of the total femur length. Elastic constants from the main diagonal of the reduced fourth-order tensor were measured on hydrated specimens using ultrasonic wave propagation. The tissue exhibited orthotropy overall and at each location along the length of the diaphysis (p < 0.0001). Elastic anisotropy increased from the mid-diaphysis toward the epiphyses (p < 0.05). The increased elastic anisotropy was primarily caused by a decreased radial elastic constant (C(11)) from the mid-diaphysis toward the epiphyses (p < 0.05), since differences in the circumferential (C(22)) and longitudinal (C(33)) elastic constants were not statistically significant (p > 0.29). Anatomic variation in intracortical porosity may account for these trends, but requires further investigation. The apparent tissue density was positively correlated with the magnitude of each elastic constant (p < 0.0001, R(2) > 0.46), as expected, but was only weakly correlated with C(33)/C(11) (p < 0.05, R(2) = 0.04) and not significantly correlated with C(33)/C(22) and C(11)/C(22).