3D-DXA Based Finite Element Modelling for Femur Strength Prediction: Evaluation Against QCT

Osteoporosis is characterised by the loss of bone density resulting in an increased risk of fragility fractures. The clinical gold standard for diagnosing osteoporosis is based on the areal bone mineral density (aBMD) used as a surrogate for bone strength, in combination with clinical risk factors. Finite element (FE) analyses based on quantitative computed tomography (QCT) have been shown to estimate bone strength better than aBMD. However, their application in the osteoporosis clinics is limited due to exposure of patients to increased X-rays radiation dose. Statistical modelling methods (3D-DXA) enabling the estimation of 3D femur shape and volumetric bone density from dual energy X-ray absorptiometry (DXA) scan have been shown to improve osteoporosis management. The current study used 3D-DXA based FE analyses to estimate femur strength from the routine clinical DXA scans and compared its results against 151 QCT based FE analyses, in a clinical cohort of 157 subjects. The linear regression between the femur strength predicted by QCT-FE and 3D-DXA-FE models correlated highly (coefficient of determination R2 = 0.86) with a root mean square error (RMSE) of 397 N. In conclusion, the current study presented a 3D-DXA-FE modelling tool providing accurate femur strength estimates noninvasively, compared to QCT-FE models.

Anisotropy, Anatomical Region, and Additional Variables Influence Young's Modulus of Bone: A Systematic Review and Meta-Analysis

The importance of finite element analysis (FEA) is growing in orthopedic research, especially in implant design. However, Young's modulus (E) values, one of the most fundamental parameters, can range across a wide scale. Therefore, our study aimed to identify factors influencing E values in human bone specimens. We report our systematic review and meta-analysis based on the recommendation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guideline. We conducted the analysis on November 21, 2021. We included studies investigating healthy human bone specimens and reported on E values regarding demographic data, specimen characteristics, and measurement specifics. In addition, we included study types reporting individual specimen measurements. From the acquired data, we created a cohort in which we performed an exploratory data analysis that included the explanatory variables selected by random forest and regression trees methods, and the comparison of groups using independent samples Welch's t test. A total of 756 entries were included from 48 articles. Eleven different bones of the human body were included in these articles. The range of E values is between 0.008 and 33.7 GPa. The E values were most heavily influenced by the cortical or cancellous type of bone tested. Measuring method (compression, tension, bending, and nanoindentation), the anatomical region within a bone, the position of the bone within the skeleton, and the bone specimen size had a decreasing impact on the E values. Bone anisotropy, specimen condition, patient age, and sex were selected as important variables considering the value of E. On the basis of our results, E values of a bone change with bone characteristics, measurement techniques, and demographic variables. Therefore, the evaluation of FEA should be performed after the standardization of in vitro measurement protocol. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

On the influence of computed tomography's slice thickness on computer tomography based finite element analyses results

BACKGROUND

Patient-specific autonomous finite element analyses of femurs, based on clinical computed tomography scans may be used to monitor the progression of bone-related diseases. Some CT scan protocols provide lower resolution (slice thickness of 3 mm) that affects the accuracy. To investigate the impact of low-resolution scans on the CT-based finite element analyses results, identical CT raw data were reconstructed twice to generate a 1 mm ("gold standard") and a 3 mm slice thickness scans.

METHODS

CT-based finite element analyses of twenty-four femurs (twelve patients) under stance and sideways fall loads were performed based on 1 and 3 mm slice thickness scans. Bone volume, load direction, and strains were extracted at different locations along the femurs and differences were evaluated.

FINDINGS

Average differences in bone volume were 1.0 ± 1.5%. The largest average difference in strains in stance position was in the neck region (11.0 ± 13.4%), whereas in other regions these were much smaller. For sidewise fall loading, the average differences were at most 9.2 ± 16.0%.

INTERPRETATION

Whole-body low dose CT scans (3 mm-slice thickness) are suboptimal for monitoring strain changes in patient's femurs but may allow longitudinal studies if larger than 5% in all areas and larger than 12% in the upper neck. CT-based finite element analyses with slice thickness of 3 mm may be used in clinical practice for patients with smoldering myeloma to associate changes in strains with progression to active myeloma if above ∼10%.

The influence of loading configurations on numerical evaluation of failure mechanisms in an uncemented femoral prosthesis

The clinical relevance of numerical predictions of failure mechanisms in femoral prosthesis could be impaired due to simplification of musculoskeletal loading. This study investigated the extent to which loading configurations affect the preclinical analysis of an uncemented femoral implant. Patient-specific, CT-scan based FE models of intact and implanted femurs were developed and analysed using three loading configurations, which comprised of load cases representing daily activities. First loading configuration consisted of two load cases, each of walking and stair climbing. The second consisted of more number of load cases for each of these activities. The third included load cases of additional activities of standing up and sitting down. Failure criteria included maximum principal strains, interface debonding, implant-bone relative displacement and adaptive bone remodelling. Simplified loading configurations led to a reduction (100-1500 με) around cortical principal strains. The area prone to interface debonding were observed in the proximo-medial part of implant and was maximum when all activities were considered. This area was reduced by 35%, when simplified loading configurations were chosen. Interfacial area of 88%-96% experienced implant-bone relative displacements below 40 μm; however maximum of 110 μm was observed at the calcar region. Lack of consideration of variety of activities overestimated (30%-50%) bone resorption around the lateral part of the implant; hence, these bone remodelling results were less clinically relevant. Considering a variety daily activities along with an adequate number of load cases for each activity seemed necessary for pre-clinical evaluations of reconstructed femur.

Image-based finite-element modeling of the human femur

Fracture is considered a critical clinical endpoint in skeletal pathologies including osteoporosis and bone metastases. However, current clinical guidelines are limited with respect to identifying cases at high risk of fracture, as they do not account for many mechanical determinants that contribute to bone fracture. Improving fracture risk assessment is an important area of research with clear clinical relevance. Patient-specific numerical musculoskeletal models generated from diagnostic images are widely used in biomechanics research and may provide the foundation for clinical tools used to quantify fracture risk. However, prior to clinical translation, in vitro validation of predictions generated from such numerical models is necessary. Despite adopting radically different models, in vitro validation of image-based finite element (FE) models of the proximal femur (predicting strains and failure loads) have shown very similar, encouraging levels of accuracy. The accuracy of such in vitro models has motivated their application to clinical studies of osteoporotic and metastatic fractures. Such models have demonstrated promising but heterogeneous results, which may be explained by the lack of a uniform strategy with respect to FE modeling of the human femur. This review aims to critically discuss the state of the art of image-based femoral FE modeling strategies, highlighting principal features and differences among current approaches. Quantitative results are also reported with respect to the level of accuracy achieved from in vitro evaluations and clinical applications and are used to motivate the adoption of a standardized approach/workflow for image-based FE modeling of the femur.

Finite element analyses for predicting anatomical neck fractures in the proximal humerus

BACKGROUND

Proximal humerus fractures which occur as a result of a fall on an outstretched arm are frequent among the elderly population. The necessity of stabilizing such fractures by surgical procedures is a controversial matter among surgeons. Validating a personalized FE analysis by ex-vivo experiments of humeri and mimicking such fractures by experiments is the first step along the path to determine the necessity of such surgeries.

METHODS

Four fresh frozen human humeri were loaded using a new simple experimental setting, so to fracture the humeri at the anatomical neck. Strains on humeri's surfaces predicted by the high order FE analyses (as in Dahan et al., 2016) were compared to the experimental observations to further enhance the validity of the FE analyses. A simplified yield criterion based on a linear elastic analysis and principal strains was used to predict the anatomical neck fracture as observed in the experiment.

FINDINGS

An excellent correlation between experimental measured and FE predicted strains was obtained (slope of 0.99 and R²=0.98). All humeri were fractured at the anatomical neck. The predicted yield load was within 10%-20% accuracy.

INTERPRETATION

High-order FE analyses reliably predict strains and yield loads in the humeri. Fractures induced by the experimental setting correspond to anatomical neck fractures noticed in practice and classified as AO C1.1-C1.3. Surgical neck fractures, which are most common in clinical practice, could not be realized in the proposed experiments, and a different experimental setting should be sought to obtain them ex-vivo.

Pathological fracture risk assessment in patients with femoral metastases using CT-based finite element methods. A retrospective clinical study

Physician recommendation for prophylactic surgical fixation of a femur with metastatic bone disease (MBD) is usually based on Mirels' criteria and clinical experience, both of which suffer from poor specificity. This may result in a significant number of these health compromised patients undergoing unnecessary surgery. CT-based finite element analyses (CTFEA) have been shown to accurately predict strength in femurs with metastatic tumors in an ex-vivo study. In order to assess the utility of CTFEA as a clinical tool to determine the need for fixation of patients with MBD of the femur, an ad hoc CTFEA was performed on a retrospective cohort of fifty patients. Patients with CT scans appropriate for CTFEA analysis were analyzed. Group 1 was composed of 5 MBD patients who presented with a pathologic femoral fracture and had a scan of their femurs just prior to fracture. Group 2 was composed of 45 MBD patients who were scheduled for a prophylactic surgery because of an impending femoral fracture. CTFEA models were constructed for both femurs for all patients, loaded with a hip contact force representing stance position loading accounting for the patient's weight and femur anatomy. CTFEA analysis of Group 1 patients revealed that they all had higher tumor associated strains compared to typical non-diseased femur bone strains at the same region (>45%). Based on analysis of the 5 patients in Group 1, the ratio between the absolute maximum principal strain in the vicinity of the tumor and the typical median strain in the region of the tumor of healthy bones (typical strain fold ratio) was found to be the 1.48. This was considered to be the predictive threshold for a pathological femoral fracture. Based on this typical strain fold ratio, twenty patients (44.4%) in Group 2 were at low risk of fracture and twenty-five patients (55.5%) high risk of fracture. Eleven patients in Group 2 choose not to have surgery and none fractured in the 5month follow-up period. CTFEA predicted that seven of these patients were below the pathological fracture threshold and four above, for a specificity of 63% Based on CTFEA, 39% of the patients with femoral MBD who were referred and underwent prophylactic stabilization may not have needed surgery. These results indicate that a prospective randomized clinical trial evaluating CTFEA as a criterion for determining the need for surgical stabilization in patients with MBD of the femur may be warranted.

A Validated Open-Source Multisolver Fourth-Generation Composite Femur Model

Synthetic biomechanical test specimens are frequently used for preclinical evaluation of implant performance, often in combination with numerical modeling, such as finite-element (FE) analysis. Commercial and freely available FE packages are widely used with three FE packages in particular gaining popularity: abaqus (Dassault Systèmes, Johnston, RI), ansys (ANSYS, Inc., Canonsburg, PA), and febio (University of Utah, Salt Lake City, UT). To the best of our knowledge, no study has yet made a comparison of these three commonly used solvers. Additionally, despite the femur being the most extensively studied bone in the body, no freely available validated model exists. The primary aim of the study was primarily to conduct a comparison of mesh convergence and strain prediction between the three solvers (abaqus, ansys, and febio) and to provide validated open-source models of a fourth-generation composite femur for use with all the three FE packages. Second, we evaluated the geometric variability around the femoral neck region of the composite femurs. Experimental testing was conducted using fourth-generation Sawbones® composite femurs instrumented with strain gauges at four locations. A generic FE model and four specimen-specific FE models were created from CT scans. The study found that the three solvers produced excellent agreement, with strain predictions being within an average of 3.0% for all the solvers (r2 > 0.99) and 1.4% for the two commercial codes. The average of the root mean squared error against the experimental results was 134.5% (r2 = 0.29) for the generic model and 13.8% (r2 = 0.96) for the specimen-specific models. It was found that composite femurs had variations in cortical thickness around the neck of the femur of up to 48.4%. For the first time, an experimentally validated, finite-element model of the femur is presented for use in three solvers. This model is freely available online along with all the supporting validation data.

Statistical analysis of the inter-individual variations of the bone shape, volume fraction and fabric and their correlations in the proximal femur

Including structural information of trabecular bone improves the prediction of bone strength and fracture risk. However, this information is available in clinical CT scans, only for peripheral bones. We hypothesized that a correlation exists between the shape of the bone, its volume fraction (BV/TV) and fabric, which could be characterized using statistical modeling. High-resolution peripheral computed tomography (HR-pQCT) images of 73 proximal femurs were used to build a combined statistical model of shape, BV/TV and fabric. The model was based on correspondence established by image registration and by morphing of a finite element mesh describing the spatial distribution of the bone properties. Results showed no correlation between the distribution of bone shape, BV/TV and fabric. Only the first mode of variation associated with density and orientation showed a strong relationship (R²>0.8). In addition, the model showed that the anisotropic information of the proximal femur does not vary significantly in a population of healthy, osteoporotic and osteopenic samples. In our dataset, the average anisotropy of the population was able to provide a close approximation of the patient-specific anisotropy. These results were confirmed by homogenized finite element (hFE) analyses, which showed that the biomechanical behavior of the proximal femur was not significantly different when the average anisotropic information of the population was used instead of patient-specific fabric extracted from HR-pQCT. Based on these findings, it can be assumed that the fabric information of the proximal femur follows a similar structure in an elderly population of healthy, osteopenic and osteoporotic proximal femurs.

Quantitative Computed Tomography (QCT) derived Bone Mineral Density (BMD) in finite element studies: a review of the literature

BACKGROUND

Finite element modeling of human bone provides a powerful tool to evaluate a wide variety of outcomes in a highly repeatable and parametric manner. These models are most often derived from computed tomography data, with mechanical properties related to bone mineral density (BMD) from the x-ray energy attenuation provided from this data. To increase accuracy, many researchers report the use of quantitative computed tomography (QCT), in which a calibration phantom is used during image acquisition to improve the estimation of BMD. Since model accuracy is dependent on the methods used in the calculation of BMD and density-mechanical property relationships, it is important to use relationships developed for the same anatomical location and using the same scanner settings, as these may impact model accuracy. The purpose of this literature review is to report the relationships used in the conversion of QCT equivalent density measures to ash, apparent, and/or tissue densities in recent finite element (FE) studies used in common density-modulus relationships. For studies reporting experimental validation, the validation metrics and results are presented.

RESULTS

Of the studies reviewed, 29% reported the use of a dipotassium phosphate (K2HPO4) phantom, 47% a hydroxyapatite (HA) phantom, 13% did not report phantom type, 7% reported use of both K2HPO4 and HA phantoms, and 4% alternate phantom types. Scanner type and/or settings were omitted or partially reported in 31% of studies. The majority of studies used densitometric and/or density-modulus relationships derived from different anatomical locations scanned in different scanners with different scanner settings. The methods used to derive various densitometric relationships are reported and recommendations are provided toward the standardization of reporting metrics.

CONCLUSIONS

This review assessed the current state of QCT-based FE modeling with use of clinical scanners. It was found that previously developed densitometric relationships vary by anatomical location, scanner type and settings. Reporting of all parameters used when referring to previously developed relationships, or in the development of new relationships, may increase the accuracy and repeatability of future FE models.

Patient-specific fracture risk assessment of vertebrae: A multiscale approach coupling X-ray physics and continuum micromechanics

While in clinical settings, bone mineral density measured by computed tomography (CT) remains the key indicator for bone fracture risk, there is an ongoing quest for more engineering mechanics-based approaches for safety analyses of the skeleton. This calls for determination of suitable material properties from respective CT data, where the traditional approach consists of regression analyses between attenuation-related grey values and mechanical properties. We here present a physics-oriented approach, considering that elasticity and strength of bone tissue originate from the material microstructure and the mechanical properties of its elementary components. Firstly, we reconstruct the linear relation between the clinically accessible grey values making up a CT, and the X-ray attenuation coefficients quantifying the intensity losses from which the image is actually reconstructed. Therefore, we combine X-ray attenuation averaging at different length scales and over different tissues, with recently identified 'universal' composition characteristics of the latter. This gives access to both the normally non-disclosed X-ray energy employed in the CT-device and to in vivo patient-specific and location-specific bone composition variables, such as voxel-specific mass density, as well as collagen and mineral contents. The latter feed an experimentally validated multiscale elastoplastic model based on the hierarchical organization of bone. Corresponding elasticity maps across the organ enter a finite element simulation of a typical load case, and the resulting stress states are increased in a proportional fashion, so as to check the safety against ultimate material failure. In the young patient investigated, even normal physiological loading is probable to already imply plastic events associated with the hydrated mineral crystals in the bone ultrastructure, while the safety factor against failure is still as high as five. Copyright © 2016 John Wiley & Sons, Ltd.

Patient-specific finite element estimated femur strength as a predictor of the risk of hip fracture: the effect of methodological determinants

A finite element modelling pipeline was adopted to predict femur strength in a retrospective cohort of 100 women. The effects of the imaging protocol and the meshing technique on the ability of the femur strength to classify the fracture and the control groups were analysed.

INTRODUCTION

The clinical standard to estimate the risk of osteoporotic hip fracture is based on the areal bone mineral density (aBMD). A few retrospective studies have concluded that finite element (FE)-based femoral strength is a better classifier of fracture and control groups than the aBMD, while others could not find significant differences. We investigated the effect of the imaging protocol and of the FE modelling techniques on the discriminatory power of femoral strength.

METHODS

A retrospective cohort of 100 post-menopausal women (50 with hip fracture, 50 controls) was examined. Each subject received a dual-energy absorptiometry (DXA) exam and a computed tomography (CT) scan of the proximal femur region. Each case was modelled a number of times, using different modelling pipelines, and the results were compared in terms of accuracy in discriminating the fracture and the control cases. The baseline pipeline involved local anatomical orientation and mesh morphing. Revised pipelines involved global anatomical orientation using a full-femur atlas registration and an optimised meshing algorithm. Minimum physiological (MPhyS) and pathological (MPatS) strengths were estimated for each subject. Area under the receiver operating characteristic (ROC) curve (AUC) was calculated to compare the ability of MPhyS, MPatS and aBMD to classify the control and the cases.

RESULTS

Differences in the modelling protocol were found to considerably affect the accuracy of the FE predictors. For the most optimised protocol, logistic regression showed aBMDNeck, MPhyS and MPatS to be significantly associated with the facture status, with AUC of 0.75, 0.75 and 0.79, respectively.

CONCLUSION

The study emphasized the necessity of modelling the whole femur anatomy to develop a robust FE-based tool for hip fracture risk assessment. FE-strength performed only slightly better than the aBMD in discriminating the fracture and control cases. Differences between the published studies can be explained in terms of differences in the modelling protocol and cohort design.

Biomechanical Role of Bone Anisotropy Estimated on Clinical CT Scans by Image Registration

Image-based modeling is a popular approach to perform patient-specific biomechanical simulations. Accurate modeling is critical for orthopedic application to evaluate implant design and surgical planning. It has been shown that bone strength can be estimated from the bone mineral density (BMD) and trabecular bone architecture. However, these findings cannot be directly and fully transferred to patient-specific modeling since only BMD can be derived from clinical CT. Therefore, the objective of this study was to propose a method to predict the trabecular bone structure using a µCT atlas and an image registration technique. The approach has been evaluated on femurs and patellae under physiological loading. The displacement and ultimate force for femurs loaded in stance position were predicted with an error of 2.5% and 3.7%, respectively, while predictions obtained with an isotropic material resulted in errors of 7.3% and 6.9%. Similar results were obtained for the patella, where the strain predicted using the registration approach resulted in an improved mean squared error compared to the isotropic model. We conclude that the registration of anisotropic information from of a single template bone enables more accurate patient-specific simulations from clinical image datasets than isotropic model.

Selecting boundary conditions in physiological strain analysis of the femur: Balanced loads, inertia relief method and follower load

Selection of boundary constraints may influence amount and distribution of loads. The purpose of this study is to analyze the potential of inertia relief and follower load to maintain the effects of musculoskeletal loads even under large deflections in patient specific finite element models of intact or fractured bone compared to empiric boundary constraints which have been shown to lead to physiological displacements and surface strains. The goal is to elucidate the use of boundary conditions in strain analyses of bones. Finite element models of the intact femur and a model of clinically relevant fracture stabilization by locking plate fixation were analyzed with normal walking loading conditions for different boundary conditions, specifically re-balanced loading, inertia relief and follower load. Peak principal cortex surface strains for different boundary conditions are consistent (maximum deviation 13.7%) except for inertia relief without force balancing (maximum deviation 108.4%). Influence of follower load on displacements increases with higher deflection in fracture model (from 3% to 7% for force balanced model). For load balanced models, follower load had only minor influence, though the effect increases strongly with higher deflection. Conventional constraints of fixed nodes in space should be carefully reconsidered because their type and position are challenging to justify and for their potential to introduce relevant non-physiological reaction forces. Inertia relief provides an alternative method which yields physiological strain results.

The influence of bone density and anisotropy in finite element models of distal radius fracture osteosynthesis: Evaluations and comparison to experiments

Continuum-level finite element (FE) models can be used to analyze and improve osteosynthesis procedures for distal radius fractures (DRF) from a biomechanical point of view. However, previous models oversimplified the bone material and lacked thorough experimental validation. The goal of this study was to assess the influence of local bone density and anisotropy in FE models of DRF osteosynthesis for predictions of axial stiffness, implant plate stresses, and screw loads. Experiments and FE analysis were conducted in 25 fresh frozen cadaveric radii with DRFs treated by volar locking plate osteosynthesis. Specimen specific geometries were captured using clinical quantitative CT (QCT) scans of the prepared samples. Local bone material properties were computed based on high resolution CT (HR-pQCT) scans of the intact radii. The axial stiffness and individual screw loads were evaluated in FE models, with (1) orthotropic inhomogeneous (OrthoInhom), (2) isotropic inhomogeneous (IsoInhom), and (3) isotropic homogeneous (IsoHom) bone material and compared to the experimental axial stiffness and screw-plate interface failures. FE simulated and experimental axial stiffness correlated significantly (p<0.0001) for all three model types. The coefficient of determination was similar for OrthoInhom (R(2)=0.807) and IsoInhom (R(2)=0.816) models but considerably lower for IsoHom models (R(2)=0.500). The peak screw loads were in qualitative agreement with experimental screw-plate interface failure. Individual loads and implant plate stresses of IsoHom models differed significantly (p<0.05) from OrthoInhom and IsoInhom models. In conclusion, including local bone density in FE models of DRF osteosynthesis is essential whereas local bone anisotropy hardly effects the models׳ predictive abilities.

Prediction of local proximal tibial subchondral bone structural stiffness using subject-specific finite element modeling: Effect of selected density-modulus relationship

BACKGROUND

Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain initiation. Calculation of bone elastic moduli from image data is a basic step when constructing finite element models. However, different relationships between elastic moduli and imaged density (known as density-modulus relationships) have been reported in the literature. The objective of this study was to apply seven different trabecular-specific and two cortical-specific density-modulus relationships from the literature to finite element models of proximal tibia subchondral bone, and identify the relationship(s) that best predicted experimentally measured local subchondral structural stiffness with highest explained variance and least error.

METHODS

Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using published density-modulus relationships and mapped to corresponding finite element models. Proximal tibial structural stiffness values were compared to experimentally measured stiffness values from in-situ macro-indentation testing directly on the subchondral bone surface (47 indentation points).

FINDINGS

Regression lines between experimentally measured and finite element calculated stiffness had R(2) values ranging from 0.56 to 0.77. Normalized root mean squared error varied from 16.6% to 337.6%.

INTERPRETATION

Of the 21 evaluated density-modulus relationships in this study, Goulet combined with Snyder and Schneider or Rho appeared most appropriate for finite element modeling of local subchondral bone structural stiffness. Though, further studies are needed to optimize density-modulus relationships and improve finite element estimates of local subchondral bone structural stiffness.

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.

QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling

Quantitative computed tomography-based finite element models of proximal femora must be validated with cadaveric experiments before using them to assess fracture risk in osteoporotic patients. During validation, it is essential to carefully assess whether the boundary condition (BC) modeling matches the experimental conditions. This study evaluated proximal femur stiffness results predicted by six different BC methods on a sample of 30 cadaveric femora and compared the predictions with experimental data. The average stiffness varied by 280% among the six BCs. Compared with experimental data, the predictions ranged from overestimating the average stiffness by 65% to underestimating it by 41%. In addition, we found that the BC that distributed the load to the contact surfaces similar to the expected contact mechanics predictions had the best agreement with experimental stiffness. We concluded that BC modeling introduced large variations in proximal femora stiffness predictions.

Patient-specific bone modeling and analysis: the role of integration and automation in clinical adoption

Patient-specific analysis of bones is considered an important tool for diagnosis and treatment of skeletal diseases and for clinical research aimed at understanding the etiology of skeletal diseases and the effects of different types of treatment on their progress. In this article, we discuss how integration of several important components enables accurate and cost-effective patient-specific bone analysis, focusing primarily on patient-specific finite element (FE) modeling of bones. First, the different components are briefly reviewed. Then, two important aspects of patient-specific FE modeling, namely integration of modeling components and automation of modeling approaches, are discussed. We conclude with a section on validation of patient-specific modeling results, possible applications of patient-specific modeling procedures, current limitations of the modeling approaches, and possible areas for future research.

Multiple loading conditions analysis can improve the association between finite element bone strength estimates and proximal femur fractures: a preliminary study in elderly women

This is a preliminary case-control study on osteopenic/osteoporotic elderly women, testing the association of proximal femur fracture with minimum femoral strength, as derived from finite element (FE) analysis in multiple loading conditions. Fracture cases (n=22) in acute conditions were enrolled among low-trauma fractures admitted in various hospitals in the Emilia Romagna Region, Italy. Women with no history of low-trauma fractures were enrolled as controls (n=33). Patients were imaged with DXA to obtain aBMD, and with a bilateral full femur CT scan. FE-strength was derived in stance and fall configurations: (i) as the minimum strength among those obtained for multiple loading conditions spanning a domain of plausible force directions, and (ii) as the strength associated to the most commonly used single loading conditions. The association of FE-strength and aBMD with fractures was tested with logistic regression models, deriving odds ratios (ORs) and area under the receiver operating characteristic curve (AUC). FE-strength from multiple loading conditions better classified fracture cases from controls (OR per SD change=9.6, 95% CI=3.0-31.3, AUC=0.87 in stance; OR=9.5, 95% CI=2.9-31.2, AUC=0.88 in fall) compared to aBMD (OR=3.6, 95% CI=1.6-8.2, AUC=0.79 for total femur aBMD), while FE-strength results from the most commonly used single loading conditions were similar to aBMD. Only FE-strength from multiple loading conditions remained significant in age- and aBMD-adjusted models (OR=10.5, 95% CI=1.8-61.3, AUC=0.95). In summary, we highlighted the importance of considering different loading conditions to identify bone weakness, and confirmed that femoral FE-strength estimates may add value to aBMD predictions in elderly osteopenic/osteoporotic women.

How accurately can we predict the fracture load of the proximal femur using finite element models?

BACKGROUND

Current clinical methods for fracture prediction rely on two-dimensional imaging methods such as dual-energy X-ray absorptiometry and have limited predictive value. Several researchers have tried to integrate three-dimensional imaging techniques with the finite element (FE) method to improve the accuracy of fracture predictions. Before FE models could be used in clinical settings, a thorough validation of their accuracy is required. In this paper, we try to evaluate the current state of accuracy of subject-specific FE models that are used for prediction of the fracture load of proximal femora.

METHODS

All the studies that have used FE for prediction of fracture load and have compared the predicted fracture load with experimentally measured fracture loads in vitro are identified through a systematic search of the literature. A quantitative analysis of the results of those studies has been carried out to determine the absolute prediction error, percentage error, and linear correlations between predicted and measured fracture loads.

FINDINGS

The reported coefficients of determination (R(2)) vary between 0.773 and 0.96 while the percentage error in prediction of fracture load varies between 5 and 46% with most studies reporting percentage errors between 10 and 20%.

INTERPRETATION

We conclude that FE models, which are currently used only experimentally, are in general more accurate than clinically used fracture risk assessment techniques. However, the accuracy of FE models depends on the details of their modeling methodologies. Therefore, modeling procedures need to be optimized and standardized before FE could be used in clinical settings.

Measurement of structural anisotropy in femoral trabecular bone using clinical-resolution CT images

Discrepancies in finite-element model predictions of bone strength may be attributed to the simplified modeling of bone as an isotropic structure due to the resolution limitations of clinical-level Computed Tomography (CT) data. The aim of this study is to calculate the preferential orientations of bone (the principal directions) and the extent to which bone is deposited more in one direction compared to another (degree of anisotropy). Using 100 femoral trabecular samples, the principal directions and degree of anisotropy were calculated with a Gradient Structure Tensor (GST) and a Sobel Structure Tensor (SST) using clinical-level CT. The results were compared against those calculated with the gold standard Mean-Intercept-Length (MIL) fabric tensor using micro-CT. There was no significant difference between the GST and SST in the calculation of the main principal direction (median error=28°), and the error was inversely correlated to the degree of transverse isotropy (r=-0.34, p<0.01). The degree of anisotropy measured using the structure tensors was weakly correlated with the MIL-based measurements (r=0.2, p<0.001). Combining the principal directions with the degree of anisotropy resulted in a significant increase in the correlation of the tensor distributions (r=0.79, p<0.001). Both structure tensors were robust against simulated noise, kernel sizes, and bone volume fraction. We recommend the use of the GST because of its computational efficiency and ease of implementation. This methodology has the promise to predict the structural anisotropy of bone in areas with a high degree of anisotropy, and may improve the in vivo characterization of bone.

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.