3D Finite Element Models Reconstructed From 2D Dual-Energy X-Ray Absorptiometry (DXA) Images Improve Hip Fracture Prediction Compared to Areal BMD in Osteoporotic Fractures in Men (MrOS) Sweden Cohort.

Bone strength is an important contributor to fracture risk. Areal bone mineral density (aBMD) derived from dual-energy X-ray absorptiometry (DXA) is used as a surrogate for bone strength in fracture risk prediction tools. 3D finite element (FE) models predict bone strength better than aBMD, but their clinical use is limited by the need for 3D computed tomography and lack of automation. We have earlier developed a method to reconstruct the 3D hip anatomy from a 2D DXA image, followed by subject-specific FE-based prediction of proximal femoral strength. In the current study, we aim to evaluate the method's ability to predict incident hip fractures in a population-based cohort (Osteoporotic Fractures in Men [MrOS] Sweden). We defined two subcohorts: (i) hip fracture cases and controls cohort: 120 men with a hip fracture (<10 years from baseline) and two controls to each hip fracture case, matched by age, height, and body mass index; and (ii) fallers cohort: 86 men who had fallen the year before their hip DXA scan was acquired, 15 of which sustained a hip fracture during the following 10 years. For each participant, we reconstructed the 3D hip anatomy and predicted proximal femoral strength in 10 sideways fall configurations using FE analysis. The FE-predicted proximal femoral strength was a better predictor of incident hip fractures than aBMD for both hip fracture cases and controls (difference in area under the receiver operating characteristics curve, ΔAUROC = 0.06) and fallers (ΔAUROC = 0.22) cohorts. This is the first time that FE models outperformed aBMD in predicting incident hip fractures in a population-based prospectively followed cohort based on 3D FE models obtained from a 2D DXA scan. Our approach has potential to notably improve the accuracy of fracture risk predictions in a clinically feasible manner (only one single DXA image is needed) and without additional costs compared to the current clinical approach. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

The influence of foramina on femoral neck fractures and strains predicted with finite element analysis.

Hip fractures following a low-impact fall are common in the elderly. Finite element (FE) models of the proximal femur can improve the prediction of fracture risk over current clinical standards. Foramina in the femoral neck may influence its fracture mechanics, albeit the majority of FE modelling approaches do not consider them. This study aimed to show how foramina affect fracture propagation and FE strain predictions in the femoral neck. µCT images were taken of 10 cadaveric proximal femora before and after fracture, following quasi-static mechanical loading representing a sideways fall. The µCT images of the fractured femora were used to determine where the bones fractured in relation to the foramina. FE models were created based on µCT and clinical CT scans of the intact femora. The superolateral side of the femoral neck was modelled with high detail including foramina. Element-specific Young's moduli were assigned and the models were solved quasi-statically. The models predicted high strains inside foramina, agreeing with experimental strain measurements. However, these high strains inside foramina were often not related to the observed fracture location. µCT images also confirmed that the foramina mostly remained intact after fracture. Using a fracture criterion based on local strain averaging improved the accuracy of the predicted fracture location as well as the correlation between the FE predicted fracture forces and the experimentally measured peak forces. To conclude, the presence of foramina can influence the fracture pattern in femoral neck fractures and inclusion of foramina in FE models improves the prediction of local strain concentrations.

Fracture behavior of a composite of bone and calcium sulfate/hydroxyapatite.

Calcium sulfate/hydroxyapatite (CaS/HA) biomaterials have been investigated for use in several orthopedic applications. However, the mechanical interactions between the composite of CaS/HA and bone at the microscale are still unknown. The aim of this study was to determine if and how augmentation with CaS/HA alters the fracture behavior of bone. Eleven cylinders of trabecular bone were drilled from human femoral heads and cleaned from bone marrow. Among them, five cylinders were injected with CaS/HA to generate composite specimens, while the others were kept intact. One extra specimen of pure CaS/HA was prepared. All specimens were compressed in situ using synchrotron X-ray tomography and imaged at ∼2% strain intervals. Structural properties were calculated from the images in unloaded state and mechanical properties were determined from the load-curves. CaS/HA alone displayed the highest peak force and stiffness and the lowest strain at fracture. All composite specimens had a higher peak force than the pure bone specimens and the composite specimens had higher toughness than the pure CaS/HA specimen. Furthermore, the fracture behavior was analyzed further to characterize the local deformations. The pure bone specimens presented damage in multiple trabeculae and the CaS/HA specimen displayed sharp transition in strains, with low strain in one load step and large cracks in the next. The composite specimens deformed uniformly, with the CaS/HA preventing tissue damage and the bone preventing cracks in the CaS/HA from propagating through the specimen. In conclusion, using tomography with in situ loading, it was possible to show how CaS/HA can help prevent bone tissue damage before global failure.

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care.

PURPOSE OF REVIEW: Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation. RECENT FINDINGS: Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

Femoral strength and strains in sideways fall: Validation of finite element models against bilateral strain measurements.

Low impact falls to the side are the main cause of hip fractures in elderly. Finite element (FE) models of the proximal femur may help in the assessment of patients at high risk for a hip fracture. However, extensive validation is essential before these models can be used in a clinical setting. This study aims to use strain measurements from bilateral digital image correlation to validate an FE model against ex vivo experimental data of proximal femora under a sideways fall loading condition. For twelve subjects, full-field strain measurements were available on the medial and lateral side of the femoral neck. In this study, subject-specific FE models were generated based on a consolidated procedure previously validated for stance loading. The material description included strain rate dependency and separate yield and fracture strain limits in tension and compression. FE predicted fracture force and experimentally measured peak forces showed a strong correlation (R2 = 0.92). The FE simulations predicted the fracture initiation within 3 mm distance of the experimental fracture line for 8/12 subjects. The predicted and measured strains correlated well on both the medial side (R2 = 0.87) and the lateral side (R2 = 0.74). The lower correlation on the lateral side is attributed to the irregularity of the cortex and presence of vessel holes in this region. The combined validation against bilateral full-field strain measurements and peak forces has opened the door for a more elaborate qualitative and quantitative validation of FE models of femora under sideways fall loading.

Validation of 3D finite element models from simulated DXA images for biofidelic simulations of sideways fall impact to the hip.

Computed tomography (CT)-derived finite element (FE) models have been proposed as a tool to improve the current clinical assessment of osteoporosis and personalized hip fracture risk by providing an accurate estimate of femoral strength. However, this solution has two main drawbacks, namely: (i) 3D CT images are needed, whereas 2D dual-energy x-ray absorptiometry (DXA) images are more generally available, and (ii) quasi-static femoral strength is predicted as a surrogate for fracture risk, instead of predicting whether a fall would result in a fracture or not. The aim of this study was to combine a biofidelic fall simulation technique, based on 3D computed tomography (CT) data with an algorithm that reconstructs 3D femoral shape and BMD distribution from a 2D DXA image. This approach was evaluated on 11 pelvis-femur constructs for which CT scans, ex vivo sideways fall impact experiments and CT-derived biofidelic FE models were available. Simulated DXA images were used to reconstruct the 3D shape and bone mineral density (BMD) distribution of the left femurs by registering a projection of a statistical shape and appearance model with a genetic optimization algorithm. The 2D-to-3D reconstructed femurs were meshed, and the resulting FE models inserted into a biofidelic FE modeling pipeline for simulating a sideways fall. The median 2D-to-3D reconstruction error was 1.02 mm for the shape and 0.06 g/cm3 for BMD for the 11 specimens. FE models derived from simulated DXAs predicted the outcome of the falls in terms of fracture versus non-fracture with the same accuracy as the CT-derived FE models. This study represents a milestone towards improved assessment of hip fracture risk based on widely available clinical DXA images.

Subject-specific FE models of the human femur predict fracture path and bone strength under single-leg-stance loading.

Hip fractures are a major health problem with high socio-economic costs. Subject-specific finite element (FE) models have been suggested to improve the fracture risk assessment, as compared to clinical tools based on areal bone mineral density, by adding an estimate of bone strength. Typically, such FE models are limited to estimate bone strength and possibly the fracture onset, but do not model the fracture process itself. The aim of this study was to use a discrete damage approach to simulate the full fracture process in subject-specific femur models under stance loading conditions. A framework based on the partition of unity finite element method (PUFEM), also known as XFEM, was used. An existing PUFEM framework previously used on a homogeneous generic femur model was extended to include a heterogeneous material description together with a strain-based criterion for crack initiation. The model was tested on two femurs, previously mechanically tested in vitro. Our results illustrate the importance of implementing a subject-specific material distribution to capture the experimental fracture pattern under stance loading. Our models accurately predicted the fracture pattern and bone strength (1% and 5% error) in both investigated femurs. This is the first study to simulate complete fracture paths in subject-specific FE femur models and it demonstrated how discrete damage models can provide a more complete picture of fracture risk by considering both bone strength and fracture toughness in a subject-specific fashion.

Elucidating failure mechanisms in human femurs during a fall to the side using bilateral digital image correlation.

An improved understanding of the mechanical properties of human femurs is a milestone towards a more accurate assessment of fracture risk. Digital image correlation (DIC) has recently been adopted to provide full-field strain measurements during mechanical testing of femurs. However, it has typically been used to measure strains on the anterior side of the femur, whereas in both single-leg-stance and sideways fall loading conditions, the highest deformations result on the medial and lateral sides of the femoral neck. The goal of this study was to measure full-field deformations simultaneously on the medial and lateral side of the femoral neck in a configuration resembling a fall to the side. Twelve female cadaver femurs were prepared for DIC measurements and tested in sideways fall at 5 mm/s displacement rate. Two pairs of cameras recorded the medial and lateral side of the femoral neck, and deformations were calculated using DIC. The samples exhibited a two-stage failure: first, a compressive collapse on the superolateral side of the femoral neck in conjunction with peak force, followed by complete femoral neck fracture at the force drop following the post-elastic phase. DIC measurements corroborated this observation by reporting no tensile strains above yield limit for the medial side of the neck up to peak force. DIC measurements registered onto the bone micro-architecture showed strain localizations in proximity of cortical pores due to, for instance, blood vessels. This could explain previously reported discrepancies between simulations and experiments in regions rich with large pores, like the superolateral femoral neck.

Tuning Viscoelasticity with Minor Changes in Speed of Sound in an Ultrasound Phantom Material.

The acoustic properties of ultrasound phantom materials have always been important, but with new applications interrogating tissue mechanical properties, viscoelasticity has also become an interesting feature to consider. Along with Young's modulus, the viscous component of tissue is affected by certain diseases and can therefore be used as a biomarker. Furthermore, viscoelasticity varies between tissue types and individuals, and therefore it would be useful with a phantom material that reflects this physiological range. Here we describe a gel for ultrasound imaging with a range of mechanical properties given by mixing different ratios of two oil-based gels, clear ballistic and styrene-ethylene/butylene-styrene (SEBS). The gels were mixed in five different proportions, ranging from 0-100% of either gel. For each of the gel compositions, we measured time of flight to determine speed of sound, narrowband ultrasound transmission for attenuation, stress-relaxation for viscoelasticity, mass and volume. Analysis of the stress-relaxation data using the generalized Maxwell model suggests that the material can be described by five parameters, E0, E1, E2, η1 and η2, and that each of these parameters decreases as more SEBS is incorporated into the mixed material. Instantaneous Young's modulus (the sum of E0, E1 and E2 in our model) ranges between 49 and 117 kPa for the different ratios, similar to values reported for cancerous tissue. Despite the large span of obtainable mechanical properties, speed of sound is relatively constant regardless of composition, with mean value estimates (± 95 % CI) between 1438 ± 9 and 1455 ± 3 m/s for pure and mixed gels. This was attributed to a variation in density and Poisson's ratio, following from the relation linking them to speed of sound and elasticity. Furthermore, both speed of sound and attenuation were within a suitable range for ultrasound phantoms. Combining this ballistic gel with SEBS copolymer in oil allows for control of mechanical properties, both elastic and viscous as evaluated by the material model. Furthermore, it does so without compromising ease of use, longevity and safety of the pre-made gel.

Automated segmentation of cortical and trabecular bone to generate finite element models for femoral bone mechanics.

Finite element (FE) models based on quantitative computed tomography (CT) images are better predictors of bone strength than conventional areal bone mineral density measurements. However, FE models require manual segmentation of the femur, which is not clinically applicable. This study developed a method for automated FE analyses from clinical CT images. Clinical in-vivo CT images of 13 elderly female subjects were collected to evaluate the method. Secondly, proximal cadaver femurs were harvested and imaged with clinical CT (N = 17). Of these femurs, 14 were imaged with µCT and three had earlier been tested experimentally in stance-loading, while collecting surface deformations with digital image correlation. Femurs were segmented from clinical CT images using an automated method, based on the segmentation tool Stradwin. The method automatically distinguishes trabecular and cortical bone, corrects partial volume effect and generates input for FE analysis. The manual and automatic segmentations agreed within about one voxel for in-vivo subjects (0.99 ±â€¯0.23 mm) and cadaver femurs (0.21 ±â€¯0.07 mm). The strains from the FE predictions closely matched with the experimentally measured strains (R2 = 0.89). The method can automatically generate meshes suitable for FE analysis. The method may bring us one step closer to enable clinical usage of patient-specific FE analyses.

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

In the original publication of the article, Fig. 3 and Tables 2, 4 and 5 were published with errors. The issue was caused by an error in the code used to predict femoral strength in the finite element (FE) models.

Fracture strength of the proximal femur injected with a calcium sulfate/hydroxyapatite bone substitute.

BACKGROUND: Available interventions for preventing fragility hip fractures show limited efficacy. Injection of a biomaterial as bone substitute could increase the fracture strength of the hip. This study aimed to show the feasibility of injecting a calcium sulfate/hydroxyapatite based biomaterial in the femoral neck and to calculate the consequent change in strength using the finite element method. METHODS: Five patients were injected with 10 ml calcium sulfate/hydroxyapatite in their femoral neck. Quantitative CT scans were taken before and after injection. Five additional patients with fragility hip fractures were also scanned and the images from the non-fractured contralateral sides were used. Finite element models were created for all proximal femora with and without injection and the models were tested under stance and sideways fall loading until fracture. The change in fracture strength caused by the injection was calculated. Additionally, perturbations in volume, location, and stiffness of the injected material were created to investigate their contribution to the fracture strength increase. FINDINGS: The 10 ml injection succeeded in all patients. Baseline simulations showed theoretical fracture strength increases of 0-9%. Volume increase, change in location and increase in stiffness of the material led to increases in fracture strength of 1-27%, -8-26% and 0-17%, respectively. Altering the location of the injection to a more lateral position and increasing the stiffness of the material led to increases in fracture strength of up to 42%. INTERPRETATION: This study shows that an injection of calcium sulfate/hydroxyapatite is feasible and can theoretically increase the hip's fracture strength.

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

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

Strains caused by daily loading might be responsible for delayed healing of an incomplete atypical femoral fracture.

Atypical femoral fractures are insufficiency fractures in the lateral femoral diaphysis or subtrochanteric region that mainly affect older patients on bisphosphonate therapy. Delayed healing is often seen in patients with incomplete fractures (cracks), and histology of bone biopsies shows mainly necrotic material inside the crack. We hypothesized that the magnitude of the strains produced in the soft tissue inside the crack during normal walk exceeds the limit for new bone formation, and thereby inhibit healing. A patient specific finite element model was developed, based on clinical CT images and high resolution µCT images of a biopsy from the crack site. Strain distributions in the femur and inside the crack were calculated for load cases representing normal walk. The models predicted large strains inside the crack, with strain levels above 10% in more than three quarters of the crack volume. According to two different tissue differentiation theories, bone would only form in less than 1-5% of the crack volume. This can explain the impaired healing generally seen in incomplete atypical fractures. Furthermore, the microgeometry of the crack highly influenced the strain distributions. Hence, a realistic microgeometry needs to be considered when modeling the crack. Histology of the biopsy showed signs of remodeling in the bone tissue adjacent to the fracture line, while the crack itself contained mainly necrotic material and signs of healing only in portions that seemed to have been widened by resorption. In conclusion, the poor healing capacity of incomplete atypical femoral fractures can be explained by biomechanical factors, and daily low impact activities are enough to cause strain magnitudes that prohibit bone formation.

How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens. In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response.

Generation of 3D shape, density, cortical thickness and finite element mesh of proximal femur from a DXA image.

Areal bone mineral density (aBMD), as measured by dual-energy X-ray absorptiometry (DXA), predicts hip fracture risk only moderately. Simulation of bone mechanics based on DXA imaging of the proximal femur, may help to improve the prediction accuracy. Therefore, we collected three (1-3) image sets, including CT images and DXA images of 34 proximal cadaver femurs (set 1, including 30 males, 4 females), 35 clinical patient CT images of the hip (set 2, including 27 males, 8 females) and both CT and DXA images of clinical patients (set 3, including 12 female patients). All CT images were segmented manually and landmarks were placed on both femurs and pelvises. Two separate statistical appearance models (SAMs) were built using the CT images of the femurs and pelvises in sets 1 and 2, respectively. The 3D shape of the femur was reconstructed from the DXA image by matching the SAMs with the DXA images. The orientation and modes of variation of the SAMs were adjusted to minimize the sum of the absolute differences between the projection of the SAMs and a DXA image. The mesh quality and the location of the SAMs with respect to the manually placed control points on the DXA image were used as additional constraints. Then, finite element (FE) models were built from the reconstructed shapes. Mean point-to-surface distance between the reconstructed shape and CT image was 1.0 mm for cadaver femurs in set 1 (leave-one-out test) and 1.4 mm for clinical subjects in set 3. The reconstructed volumetric BMD showed a mean absolute difference of 140 and 185 mg/cm(3) for set 1 and set 3 respectively. The generation of the SAM and the limitation of using only one 2D image were found to be the most significant sources of errors in the shape reconstruction. The noise in the DXA images had only small effect on the accuracy of the shape reconstruction. DXA-based FE simulation was able to explain 85% of the CT-predicted strength of the femur in stance loading. The present method can be used to accurately reconstruct the 3D shape and internal density of the femur from 2D DXA images. This may help to derive new information from clinical DXA images by producing patient-specific FE models for mechanical simulation of femoral bone mechanics.

Extracting accurate strain measurements in bone mechanics: A critical review of current methods.

Osteoporosis related fractures are a social burden that advocates for more accurate fracture prediction methods. Mechanistic methods, e.g. finite element models, have been proposed as a tool to better predict bone mechanical behaviour and strength. However, there is little consensus about the optimal constitutive law to describe bone as a material. Extracting reliable and relevant strain data from experimental tests is of fundamental importance to better understand bone mechanical properties, and to validate numerical models. Several techniques have been used to measure strain in experimental mechanics, with substantial differences in terms of accuracy, precision, time- and length-scale. Each technique presents upsides and downsides that must be carefully evaluated when designing the experiment. Moreover, additional complexities are often encountered when applying such strain measurement techniques to bone, due to its complex composite structure. This review of literature examined the four most commonly adopted methods for strain measurements (strain gauges, fibre Bragg grating sensors, digital image correlation, and digital volume correlation), with a focus on studies with bone as a substrate material, at the organ and tissue level. For each of them the working principles, a summary of the main applications to bone mechanics at the organ- and tissue-level, and a list of pros and cons are provided.

Strain distribution in the proximal Human femur during in vitro simulated sideways fall.

This study assessed: (i) how the magnitude and direction of principal strains vary for different sideways fall loading directions; (ii) how the principal strains for a sideways fall differ from physiological loading directions; (iii) the fracture mechanism during a sideways fall. Eleven human femurs were instrumented with 16 triaxial strain gauges each. The femurs were non-destructively subjected to: (a) six loading configurations covering the range of physiological loading directions; (b) 12 configurations simulating sideways falls. The femurs were eventually fractured in a sideways fall configuration while high-speed cameras recorded the event. When the same force magnitude was applied, strains were significantly larger in a sideways fall than for physiological loading directions (principal compressive strain was 70% larger in a sideways fall). Also the compressive-to-tensile strain ratio was different: for physiological loading the largest compressive strain was only 30% larger than the largest tensile strain; but for the sideways fall, compressive strains were twice as large as the tensile strains. Principal strains during a sideways fall were nearly perpendicular to the direction of principal strains for physiological loading. In the most critical regions (medial part of the head-neck) the direction of principal strain varied by less than 9° between the different physiological loading conditions, whereas it varied by up to 17° between the sideways fall loading conditions. This was associated with a specific fracture mechanism during sideways fall, where failure initiated on the superior-lateral side (compression) followed by later failure of the medially (tension), often exhibiting a two-peak force-displacement curve.

To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations?

Proximal femur strength estimates from computed tomography (CT)-based finite element (FE) models are finding clinical application. Published models reached a high in-vitro accuracy, yet many of them rely on nonlinear methodologies or internal best-fitting of parameters. The aim of the present study is to verify to what extent a linear FE modelling procedure, fully based on independently determined parameters, can predict the failure characteristics of the proximal femur in stance and sideways fall loading configurations. Fourteen fresh-frozen cadaver femora were CT-scanned. Seven femora were tested to failure in stance loading conditions, and seven in fall. Fracture was monitored with high-speed videos. Linear FE models were built from CT images according to a procedure already validated in the prediction of strains. An asymmetric maximum principal strain criterion (0.73% tensile, 1.04% compressive limit) was used to define a node-based risk factor (RF). FE-predicted failure load, mode (tensile/compressive) and location were determined from the first node reaching RF=1. FE-predicted and measured failure loads were highly correlated (R(2)=0.89, SEE=814N). In all specimens, FE models correctly identified the failure mode (tensile in stance, compressive in fall) and the femoral region where fracture started (supero-lateral neck aspect). The location of failure onset was accurately predicted in eight specimens. In summary, a simple FE model, adaptable in the future to multiple loads (e.g. including muscles), was highly correlated with experimental failure in two loading conditions on specimens ranging from normal to osteoporotic. Thus, it can be suitable for use in clinical studies.