Calibration with or without phantom for fracture risk prediction in cancer patients with femoral bone metastases using CT-based finite element models

The Influence of Cup Orientation on the Primary Fixation of a Hemispherical Cementless Acetabular Cup: A Cohort Based Finite Element Study

Cup orientation has been investigated in detail with respect to risk of dislocation, however, the impact on the primary fixation of cementless cups is poorly understood. The aim of this study was to assess the influence acetabular component orientation on the primary fixation of cementless acetabular cups using an in silico clinical trial framework. Finite element models of 57 implanted hemi-pelves were generated from CT scans of a cohort of end stage osteoarthritis patients. Each hemi-pelvis was implanted with the with cup orientations that bounded the Lewinnek safe zone (mechanical alignment +/-10 degrees) and an approximation of the extreme orientations reported in the literature (mechanical alignment +/-20 degrees). Bone strain immediately adjacent to the implant and micromotions (gap and shear micromotions) were used to assess primary fixation. Analysis was performed at the levels of the individual subjects and the entire cohort. There was minimal variation in all metrics within the Lewinnek safe zone. Micromotion, particularly inferior gaping, was more sensitive to cup orientation than peri-prosthetic bone strain, tending to increase with inclination angle. Both the peri-prosthetic bone strains and micromotions were moderately correlated to the average bone modulus. Individuals with low bone modulus were shown to be more sensitive to changes in cup orientation for both peri-prosthetic bone strains and micromotions both within and outside the Lewinnek safe zone. This suggests that assessing bone quality should be routinely incorporated into the planning process, particularly when considering cup orientations outside of the Lewinnek safe zone.

Characterization of nonlinear stress relaxation of the femoral and tibial trabecular bone for computational modeling

Computational models of orthopedic reconstructions are reliant on bone material properties, but viscoelastic behavior of trabecular bone is often ignored in numerical simulations. The inclusion of stress relaxation could be of importance for the accuracy of models simulating the primary stability of cementless implants. In this study, a material model to describe the nonlinear viscoelastic behavior of human trabecular bone was constructed based on uniaxial stress relaxation experiments. The relationship of bone mineral density (BMD) and stress relaxation was explored, and the material model was implemented in sample-specific finite element (FE) simulations. Cylindrical trabecular human bone specimens, from the distal femur and proximal tibia, were subjected to stress relaxation tests, undergoing compression with strains from 0.2 % to 0.8 % for 30 min on four consecutive days. The experimental data were extrapolated to 24 h. Similar levels of stress relaxation were found for femoral and tibial specimens, with an average 54.4 % stress relaxation and a maximum level of 81.6 %. Using a modified superposition model, the specimen-specific nonlinear stress relaxation behavior was captured. However, when the samples were considered collectively, no correlation was found between applied strain, BMD and the viscoelastic response. Therefore, the average level of stress relaxation in combination with existing BMD-stiffness relationships were implemented in FE simulations for each individual specimen. While the FE models, on average, overestimated the overall stiffness by 64 %, they were able to adequately capture the stress relaxation response.

The effect of bone plasticity models on simulations of primary fixation in total knee arthroplasty

Predictions of primary fixation in total knee arthroplasty (TKA) can aid in implant design, optimizing long-term survival. Finite element (FE) simulations are commonly used to assess micromotions at the bone-implant interface during daily activities, requiring accurate computational models. A key factor is the material model used to simulate bone properties. This study evaluated two plastic material models-Isotropic Crushable Foam (ICF) and softening Von-Mises (sVM)-for predicting primary fixation in femoral TKA components. Mechanical tests on human femoral trabecular bone samples under cyclic loading were replicated using FE simulations with ICF and sVM models. These models were then applied to FE simulations of three femoral TKA reconstructions, representing patients aged 57, 73, and 90 years. The ICF model replicated the gradual plastic deformation observed in experiments, unlike the sVM model, and more closely matched the permanent deformation of bone samples. In primary fixation simulations, micromotions at the bone-implant interface averaged 27 µm with ICF and 17 µm with sVM. While both predictions fall within acceptable ranges, the ICF model, as a pressure-dependent material model, more accurately replicates experimental energy dissipation and plastic deformation patterns, closely mirroring human bone's plastic behavior. This makes it better suited for simulating implant-bone interface micromotions in primary TKA fixation.

Estimating temporal bone-implant stresses in patients with bone-anchored lower limbs

Bone-anchored limbs (BALs) are a transformative alternative for patients with lower-limb amputation who suffer from debilitating socket problems by eliminating the need for skin-to-prosthetic contact. Despite its successes, some individuals continue to face challenges with BALs, experiencing a loss of implant integration resulting in prosthetic loosening. A thorough understanding of biomechanical behavior at the residual limb and bone-implant interface is necessary to fully understand mechanical failure mechanisms. In addition, a deeper understanding of BAL biomechanical behavior would allow clinicians and researchers to predict and test different implant geometries, inform patient eligibility, rehabilitation strategies, and implantation methods in a safe and low-cost way. Thus, this study designed an innovative simulation method to quantify the temporal mechanical behavior of the residual limb in transfemoral and transtibial BALs by using subject-specific kinematics, musculoskeletal loads, and bone geometry and health. Our novel method was applied to two patients (one transtibial, one transfemoral) with similar BMI and age during level ground walking. Our results demonstrated a pattern of higher residual limb stresses in the transtibial model (26.80 MPa vs. 23.69 MPa). This study not only furthers our understanding of BAL biomechanics but introduces a versatile subject-specific methodology with direct applications in clinical practice. As we navigate the complexities of BAL implantation, this modeling platform lays the groundwork for more informed decision-making.

Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty

BACKGROUND

Reduced bone density is recognized as a predictor for potential complications in reverse shoulder arthroplasty (RSA). While humeral and glenoid planning based on preoperative computed tomography (CT) scans assist in implant selection and position, reproducible methods for quantifying the patients' bone density are currently not available. The purpose of this study was to perform bone density analyses including patient-specific calibration in an RSA cohort based on preoperative CT imaging. It was hypothesized that preoperative CT bone density measures would provide objective quantification of the patients' humeral bone quality.

METHODS

This study consisted of 3 parts, (1) analysis of a patient-specific calibration method in cadaveric CT scans, (2) retrospective application in a clinical RSA cohort, and (3) clustering and classification with machine learning (ML) models. Forty cadaveric shoulders were scanned in a clinical CT and compared regarding calibration with density phantoms, air muscle, and fat (patient-specific) or standard Hounsfield unit. Postscan patient-specific calibration was used to improve the extraction of 3-dimensional regions of interest for retrospective bone density analysis in a clinical RSA cohort (n = 345). ML models were used to improve the clustering (Hierarchical Ward) and classification (support vector machine) of low bone densities in the respective patients.

RESULTS

The patient-specific calibration method demonstrated improved accuracy with excellent intraclass correlation coefficients for cylindrical cancellous bone densities (intraclass correlation coefficient >0.75). Clustering partitioned the training data set into a high-density subgroup consisting of 96 patients and a low-density subgroup consisting of 146 patients, showing significant differences between these groups. The support vector machine showed optimized prediction accuracy of low and high bone densities compared to conventional statistics in the training (accuracy = 91.2%; area under curve = 0.967) and testing (accuracy = 90.5%; area under curve = 0.958) data set.

CONCLUSION

Preoperative CT scans can be used to quantify the proximal humeral bone quality in patients undergoing RSA. The use of ML models and patient-specific calibration on bone mineral density demonstrated that multiple three-dimensional bone density scores improved the accuracy of objective preoperative bone quality assessment. The trained model could provide preoperative information to surgeons treating patients with potentially poor bone quality.

Reverse Shoulder Arthroplasty Baseplate Stability Is Affected by Bone Density and the Type and Amount of Augmentation

OBJECTIVE

This study evaluated the effects of bony increased offset (BIO) and metallic augments (MAs) on primary reverse shoulder arthroplasty (RSA) baseplate stability in cadaveric specimens with variable bone densities.

METHODS

Thirty cadaveric specimens were analyzed in an imaging and biomechanical investigation. Computed tomography (CT) scans allowed for preoperative RSA planning and bone density analysis. Three correction methods of the glenoid were used: (1) corrective reaming with a standard baseplate, which served as the reference group (n = 10); (2) MA-RSA (n = 10); and (3) angled BIO-RSA (n = 10). Each augment group consisted of 10° (n = 5) and 20° (n = 5) corrections. Biomechanical testing included cyclic loading in an articulating setup, with optical pre- and post-cyclic micromotion measurements in a rocking horse setup.

RESULTS

There were no differences in bone density between groups based on CT scans (p > 0.126). The BIO-RSA group had higher variability in micromotion compared to the MA-RSA and reference groups (p = 0.013), and increased total micromotion compared to the reference group (p = 0.039). Both augmentations using 20° corrections had increased variance in rotational stability compared to the reference group (p = 0.043). Micromotion correlated with the subchondral bone density in the BIO-RSA group (r = -0.63, p = 0.036), but not in the MA-RSA (p > 0.178) or reference (p > 0.117) groups.

CONCLUSIONS

Time-zero baseplate implant fixation is more variable with BIO-RSA and correlates with bone density. Corrections of 20° with either augmentation approach increase variability in rotational micromotion. The preoperative quantification of bone density may be useful before utilizing 20° of correction, especially when adding a bone graft in BIO-RSAs.

Assessment of age-dependent sexual dimorphism in paediatric vertebral size and density using a statistical shape and statistical appearance modelling approach

This work focuses on the growth patterns of the human fourth lumbar vertebra (L4) in a paediatric population, with specific attention to sexual dimorphism. The study aims to understand morphological and density changes in the vertebrae through age-dependent statistical shape and statistical appearance models, which can describe full three-dimensional anatomy. Results show that the main growth patterns are associated with isotropic volumetric vertebral growth, a decrease in the relative size of the vertebral foramen, and an increase in the length of the transverse processes. Moreover, significant sexual dimorphism was demonstrated during puberty. We observe significant age and sex interaction in the anterior vertebral body height (P = 0.005), where females exhibited an earlier increase in rates of vertebral height evolution. Moreover, we also observe an increase in cross-sectional area (CSA) with age (P = 0.020), where the CSA is smaller in females than in males (significant sex effect P = 0.042). Finally, although no significant increase in trabecular bone density with age is observed (P = 0.363), a trend in the statistical appearance model suggests an increase in density with age.

Multi-site phantomless bone mineral density from clinical quantitative computed tomography in males

Volumetric bone mineral density (vBMD) is commonly assessed using QCT. Although standard vBMD calculation methods require phantom rods that may not be available, internal-reference phantomless (IPL) and direct measurements of Hounsfield units (HU) can be used to calculate vBMD in their absence. Yet, neither approach has been systemically assessed across skeletal sites, and HU need further validation as a vBMD proxy. This study evaluated the accuracy of phantomless methods, including IPL and regression-based phantomless (RPL) calibration using HU to calculate vBMD, compared to phantom-based (PB) methods. vBMD from QCT scans of 100 male post-mortem human subjects (PMHS) was calculated using site-specific PB calibration at multiple skeletal sites throughout the body. A development sample of 50/100 PMHS was used to determine site-specific reference material density for IPL calibration and RPL equations. Reference densities and equations from the development sample were used to calculate IPL and RPL vBMD on the remaining 50/100 PMHS for method validation. PB and IPL/RPL vBMD were not significantly different (p > .05). Univariate regressions between PB and IPL/RPL vBMD were universally significant (p < 0.05), except for IPL Rad-30 (p = 0.078), with a percent difference across all sites of 6.97% ± 5.95% and 5.22% ± 4.59% between PB and IPL/RPL vBMD, respectively. As vBMD increased, there were weaker relationships and larger differences between PB vBMD and IPL/RPL vBMD. IPL and RPL vBMD had strong relationships with PB vBMD across sites (R2 = 97.99, R2 = 99.17%, respectively), but larger residual differences were found for IPL vBMD. As the accuracy of IPL/RPL vBMD varied between sites, phantomless methods should be site-specific to provide values more comparable to PB vBMD. Overall, this study suggests that RPL calibration may better represent PB vBMD compared to IPL calibration, increases the utility of opportunistic QCT, and provides insight into bone quality and fracture risk.

Using a statistical shape model to estimate the knee landmarks for aligning femurs for femoral finite element models

BACKGROUND AND OBJECTIVE

The BOne Strength (BOS) score is a CT-based tool to assess fracture risk for patients with femoral bone metastases using finite element (FE) models. Until now, the knee joint center (KJC) and centers of the condyles (CoCs) were needed to create the FE model, hence BOS scores of incompletely scanned femurs could not be calculated. In this study, a statistical shape model (SSM) was used to align FE models of femurs with a removed knee anatomy. The aim was to determine the effect of using an SSM with different proximal femur fractions on KJC and CoC locations, and on the BOS score.

METHODS

QCT scans of 117 femurs were used to generate patient-specific FE models of the proximal femur. These models were aligned using the knee joint center (KJC), center of condyles (CoC) and femoral head center. The femurs were artificially shortened by removing 30 %, 50 % or 70 % of the femur. A recently developed SSM was used to reconstruct the distal femur. For each of the femur fractions, the difference between the original and SSM-reconstructed KJC and CoC were determined and the BOS scores were calculated.

RESULTS

Although the individual differences between the original and SSM-reconstructed KJC and CoC location could be large, the effect on the individual BOS scores was limited. The SSM-reconstructed BOS scores were highly correlated to the original BOS scores.

CONCLUSION

Using SSM to align femurs with a removed knee anatomy resulted in varying estimation of knee anatomy between patients but relatively accurate BOS scores.

Asynchronous calibration of a CT scanner for bone mineral density estimation: sources of error and correction

The estimation of BMD with CT scans requires a calibration method, usually based on a phantom. In asynchronous calibration, the phantom is scanned separately from the patient. A standardized acquisition protocol must be used to avoid variations between patient and phantom. However, variations can still be induced, for example, by temporal fluctuations or patient characteristics. Based on the further use of 739 forensic and 111 clinical CT scans, this study uses the proximal femur BMD value ("total hip") to assess asynchronous calibration accuracy, using in-scan calibration as ground truth. It identifies the parameters affecting the calibration accuracy and quantifies their impact. For time interval and table height, the impact was measured by calibrating the CT scan twice (once using the phantom scan with closest acquisition parameters and once using a phantom scan with standard values) and comparing the calibration accuracy. For other parameters such as body weight, the impact was measured by computing a linear regression between parameter values and calibration accuracy. Finally, this study proposes correction methods to reduce the effect of these parameters and improve the calibration accuracy. The BMD error of the asynchronous calibration, using the phantom scan with the closest acquisition parameters, was -1.2 ± 1.7% for the forensic and - 1.6 ± 3.5% for the clinical dataset. Among the parameters studied, time interval and body weight were identified as the main sources of error for asynchronous calibration, followed by table height and reconstruction kernel. Based on these results, a correction method was proposed to improve the calibration accuracy.

Evaluation of finite element modeling methods for predicting compression screw failure in a custom pelvic implant

Introduction: Three-dimensional (3D)-printed custom pelvic implants have become a clinically viable option for patients undergoing pelvic cancer surgery with resection of the hip joint. However, increased clinical utilization has also necessitated improved implant durability, especially with regard to the compression screws used to secure the implant to remaining pelvic bone. This study evaluated six different finite element (FE) screw modeling methods for predicting compression screw pullout and fatigue failure in a custom pelvic implant secured to bone using nine compression screws. Methods: Three modeling methods (tied constraints (TIE), bolt load with constant force (BL-CF), and bolt load with constant length (BL-CL)) generated screw axial forces using functionality built into Abaqus FE software; while the remaining three modeling methods (isotropic pseudo-thermal field (ISO), orthotropic pseudo-thermal field (ORT), and equal-and-opposite force field (FOR)) generated screw axial forces using iterative physics-based relationships that can be implemented in any FE software. The ability of all six modeling methods to match specified screw pretension forces and predict screw pullout and fatigue failure was evaluated using an FE model of a custom pelvic implant with total hip replacement. The applied hip contact forces in the FE model were estimated at two locations in a gait cycle. For each of the nine screws in the custom implant FE model, likelihood of screw pullout failure was predicted using maximum screw axial force, while likelihood of screw fatigue failure was predicted using maximum von Mises stress. Results: The three iterative physics-based modeling methods and the non-iterative Abaqus BL-CL method produced nearly identical predictions for likelihood of screw pullout and fatigue failure, while the other two built-in Abaqus modeling methods yielded vastly different predictions. However, the Abaqus BL-CL method required the least computation time, largely because an iterative process was not needed to induce specified screw pretension forces. Of the three iterative methods, FOR required the fewest iterations and thus the least computation time. Discussion: These findings suggest that the BL-CL screw modeling method is the best option when Abaqus is used for predicting screw pullout and fatigue failure in custom pelvis prostheses, while the iterative physics-based FOR method is the best option if FE software other than Abaqus is used.

The lack of EphB3 receptor prevents bone loss in mouse models of osteoporosis

Bone homeostasis is a complex process in which some Eph kinase receptors and their ephrin ligands appear to be involved. In the present study, we address this issue by examining, both in vitro and in vivo, the role of EphB2 and EphB3 in mesenchymal stromal/stem cell (MSC) differentiation into bone tissue. This was first evaluated by quantitative reverse transcription PCR (RT-qPCR) and histological staining in MSCs cultured in specific mediums revealing that although EphB2-/- MSCs mainly expressed pro-adipogenic transcription factors, EphB3-/- MSCs showed abundant osteogenic transcripts, such as Runx2, Msx2, and Sp7. To clarify the underlying molecular mechanisms, we found that the lack of EphB3 signaling alters the genetic profile of differentiating MSCs, reducing the expression of many inhibitory molecules and antagonists of the BMP signaling pathway, and increasing Bmp7 expression, a robust bone inductor. Then, to confirm the osteogenic role of EphB3 in vivo, we studied the condition of 2 mouse models of induced bone loss (ovariectomy or long-term glucocorticoid treatment). Interestingly, in both models, both WT and EphB2-/- mice equally developed the disease but EphB3-/- mice did not exhibit the typical bone loss, nor an increase in urine Ca2+ or blood serum CTX-1. This phenotype in EphB3-KO mice could be due to their significantly higher proportions of osteoprogenitor cells and preosteoblasts, and their lower number of osteoclasts, as compared with WT and EphB2-KO mice. Thus, we conclude that EphB3 acts as a negative regulator of the osteogenic differentiation, and its absence prevents bone loss in mice subjected to ovariectomy or dexamethasone treatment.

Assessing screw length impact on bone strain in proximal humerus fracture fixation via surrogate modelling

A high failure rate is associated with fracture plates in proximal humerus fractures. The causes of failure remain unclear due to the complexity of the problem including the number and position of the screws, their length and orientation in the space. Finite element (FE) analysis has been used for the analysis of plating of proximal humeral fractures, but due to computational costs is unable to fully explore all potential screw combinations. Surrogate modelling is a viable solution, having the potential to significantly reduce the computational cost whilst requiring a moderate number of training sets. This study aimed to develop adaptive neural network (ANN)-based surrogate models to predict the strain in the humeral bone as a result of changing the length of the screws. The ANN models were trained using data from FE simulations of a single humerus, and after defining the best training sample size, multiple and single-output models were developed. The best performing ANN model was used to predict all the possible screw length configurations. The ANN predictions were compared with the FE results of unseen data, showing a good correlation (R2 = 0.99) and low levels of error (RMSE = 0.51%-1.83% strain). The ANN predictions of all possible screw length configurations showed that the screw that provided the medial support was the most influential on the predicted strain. Overall, the ANN-based surrogate model accurately captured bone strains and has the potential to be used for more complex problems with a larger number of variables.

Preoperative 3-dimensional computed tomography bone density measures provide objective bone quality classifications for stemless anatomic total shoulder arthroplasty

BACKGROUND

Reproducible methods for determining adequate bone densities for stemless anatomic total shoulder arthroplasty (aTSA) are currently lacking. The purpose of this study was to evaluate the utility of preoperative computed tomography (CT) imaging for assessing the bone density of the proximal humerus for supportive differentiation in the decision making for stemless humeral component implantation. It was hypothesized that preoperative 3-dimensional (3-D) CT bone density measures provide objective classifications of the bone quality for stemless aTSA.

METHODS

A 3-part study was performed that included the analysis of cadaveric humerus CT scans followed by retrospective application to a clinical cohort and classification with a machine learning model. Thirty cadaveric humeri were evaluated with clinical CT and micro-CT (μCT) imaging. Phantom-calibrated CT data were used to extract 3-D regions of interest and defined radiographic scores. The final image processing script was applied retrospectively to a clinical cohort (n = 150) that had a preoperative CT and intraoperative bone density assessment using the "thumb test," followed by placement of an anatomic stemmed or stemless humeral component. Postscan patient-specific calibration was used to improve the functionality and accuracy of the density analysis. A machine learning model (Support vector machine [SVM]) was utilized to improve the classification of bone densities for a stemless humeral component.

RESULTS

The image processing of clinical CT images demonstrated good to excellent accuracy for cylindrical cancellous bone densities (metaphysis [ICC = 0.986] and epiphysis [ICC = 0.883]). Patient-specific internal calibration significantly reduced biases and unwanted variance compared with standard HU CT scans (P < .0001). The SVM showed optimized prediction accuracy compared with conventional statistics with an accuracy of 73.9% and an AUC of 0.83 based on the intraoperative decision of the surgeon. The SVM model based on density clusters increased the accuracy of the bone quality classification to 87.3% with an AUC of 0.93.

CONCLUSIONS

Preoperative CT imaging allows accurate evaluation of the bone densities in the proximal humerus. Three-dimensional regions of interest, rescaling using patient-specific calibration, and a machine learning model resulted in good to excellent prediction for objective bone quality classification. This approach may provide an objective tool extending preoperative selection criteria for stemless humeral component implantation.

Phantomless calibration of CT scans for hip fracture risk prediction in silico: Comparison with phantom-based calibration

Finite element models built from quantitative computed tomography images rely on element-wise mapping of material properties starting from Hounsfield Units (HU), which can be converted into mineral densities upon calibration. While calibration is preferably carried out by scanning a phantom with known-density components, conducting phantom-based calibration may not always be possible. In such cases, a phantomless procedure, where the scanned subject's tissues are used as a phantom, is an interesting alternative. The aim of this study was to compare a phantom-based and a phantomless calibration method on 41 postmenopausal women. The proposed phantomless calibration utilized air, adipose, and muscle tissues, with reference equivalent mineral density values of -797, -95, and 38 mg/cm3, extracted from a previously performed phantom-based calibration. A 9-slice volume of interest (VOI) centred between the femoral head and knee rotation centres was chosen. Reference HU values for air, adipose, and muscle tissues were extracted by identifying HU distribution peaks within the VOI, and patient-specific calibration was performed using linear regression. Comparison of FE models calibrated with the two methods showed average relative differences of 1.99% for Young's modulus1.30% for tensile and 1.34% for compressive principal strains. Excellent correlations (R2 > 0.99) were identified for superficial maximum tensile and minimum compressive strains. Maximum normalised root mean square relative error (RMSRE) values settled at 4.02% for Young's modulus, 2.99% for tensile, and 3.22% for compressive principal strains, respectively. The good agreement found between the two methods supports the adoption of the proposed methodology when phantomless calibration is needed.

Quantification of long-term nonlinear stress relaxation of bovine trabecular bone

The reliability of computational models in orthopedic biomechanics depends often on the accuracy of the bone material properties. It is widely recognized that the mechanical response of trabecular bone is time-dependent, yet it is often ignored for the sake of simplicity. Previous investigations into the viscoelastic properties of trabecular bone have not explored the relationship between nonlinear stress relaxation and bone mineral density. The inclusion of this behavior could enhance the accuracy of simulations of orthopedic interventions, such as of primary fixation of implants. Although methods to quantify the viscoelastic behavior are known, the time period during which the viscoelastic properties should be investigated to obtain reliable predictions is currently unclear. Therefore, this study aimed to: 1) Investigate the duration of stress relaxation in bovine trabecular bone; 2) construct a material model that describes the nonlinear viscoelastic behavior of uniaxial stress relaxation experiments on trabecular bone; and 3) implement bone density into this model. Uniaxial compressive stress relaxation experiments were performed with cylindrical bovine femoral trabecular bone samples (n = 16) with constant strain held for 24 h. Additionally, multiple stress relaxation experiments with four ascending strain levels with a holding time of 30 min, based on the results of the 24-h experiment, were executed on 18 bovine bone cores. The bone specimens used in this study had a mean diameter of 12.80 mm and a mean height of 28.70 mm. A Schapery and a Superposition model were used to capture the nonlinear stress relaxation behavior in terms of applied strain level and bone mineral density. While most stress relaxation happened in the first 10 min (up to 53 %) after initial compression, the stress relaxation continued even after 24 h. Up to 69 % of stress relaxation was observed at 24 h. Extrapolating the results of 30 min of experimental data to 24 h provided a good fit for accuracy with much improved experimental efficiency. The Schapery and Superposition model were both capable of fitting the repeated stress relaxation in a sample-by-sample approach. However, since bone mineral density did not influence the time-dependent behavior, only the Superposition model could be used for a group-based model fit. Although the sample-by-sample approach was more accurate for an individual specimen, the group based approach is considered a useful model for general application.

The effect of deep learning-based lesion segmentation on failure load calculations of metastatic femurs using finite element analysis

Bone ranks as the third most frequent tissue affected by cancer metastases, following the lung and liver. Bone metastases are often painful and may result in pathological fracture, which is a major cause of morbidity and mortality in cancer patients. To quantify fracture risk, finite element (FE) analysis has shown to be a promising tool, but metastatic lesions are typically not specifically segmented and therefore their mechanical properties may not be represented adequately. Deep learning methods potentially provide the opportunity to automatically segment these lesions and change the mechanical properties more adequately. In this study, our primary focus was to gain insight into the performance of an automatic segmentation algorithm for femoral metastatic lesions using deep learning methods and the subsequent effects on FE outcomes. The aims were to determine the similarity between manual segmentation and automatic segmentation; the differences in predicted failure load between FE models with automatically segmented osteolytic and mixed lesions and the models with CT-based lesion values (the gold standard); and the effect on the BOne Strength (BOS) score (failure load adjusted for body weight) and subsequent fracture risk assessments. From two patient cohorts, a total number of 50 femurs with osteolytic and mixed metastatic lesions were included in this study. The femurs were segmented from CT images and transferred into FE meshes. The material behavior was implemented as non-linear isotropic. These FE models were considered as gold standard (Finite Element no Segmented Lesion: FE-no-SL), whereby the local calcium equivalent density of both femur and metastatic lesion was extracted from CT-values. Lesions in the femur were manually segmented by two biomechanical experts after which final lesion segmentation for each femur was obtained based on consensus of opinions between two observers. Subsequently, a self-configuring variant of the popular deep learning model U-Net known as nnU-Net was used to automatically segment metastatic lesions within the femur. For these models with segmented lesions (Finite Element with Segmented Lesion: FE-with-SL), the calcium equivalent density within the metastatic lesions was set to zero after being segmented by the neural network, simulating absence of load-bearing capacity of these lesions. The models (either with or without automatically segmented lesions) were loaded incrementally in axial direction until failure was simulated. Dice coefficient was used to evaluate the similarity of the manual and automatic segmentation. Mean calcium equivalent density values within the automatically segmented lesions were calculated. Failure loads and patterns were determined. Furthermore, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for both groups by comparing the predictions to the occurrence or absence of actual fracture within the patient cohorts. The automatic segmentation algorithm performed in a none-robust manner. Dice coefficients describing the similarity between consented manual and automatic segmentations were relatively low (mean 0.45 ± standard deviation 0.33, median 0.54). Failure load difference between the FE-no-SL and FE-with-SL groups varied from 0 % to 48 % (mean 6.6 %). Correlation analysis of failure loads between the two groups showed a strong relationship (R2 > 0.9). From the 50 cases, four cases showed clear deviations for which models with automatic lesion segmentation (FE-with-SL) showed considerably lower failure loads. In the whole database including osteolytic and mixed lesions, sensitivity and NPV remained the same, but specificity and PPV decreased from 94 % to 83 %, and from 78 % to 54 % respectively from FE-no-SL to FE-with-SL. This study indicates that the nnU-Net yielded none-robust outcomes in femoral lesion segmentation and that other segmentation algorithms should be considered. However, the difference in failure pattern and failure load between FE models with automatically segmented osteolytic and mixed lesions were relatively small in most cases with a few exceptions. On the other hand, the accuracy of fracture risk assessment using the BOS score was lower compared to the FE-no-SL. In conclusion, this study showed that automatic lesion segmentation is a none-solved issue and therefore, quantifying lesion characteristics and the subsequent effect on the fracture risk using deep learning will remain challenging.

Corroboration of coupled musculoskeletal model and finite element predictions with in vivo RSA migration of an uncemented acetabular component

While finite element (FE) models have been used extensively in orthopedic studies, validation of their outcome metrics has been limited to comparison against ex vivo testing. The aim of this study was to validate FE model predictions of the initial cup mechanical environment against patient-matched in vivo measurements of acetabular cup migration using radiostereometric analysis (RSA). Tailored musculoskeletal and FE models were developed using a combination of three-dimensional (3D) motion capture data and clinical computerized tomography (CT) scans for a cohort of eight individuals who underwent primary total hip replacement and were prospectively enrolled in an RSA study. FE models were developed to calculate the mean modulus of cancellous bone, composite peak micromotion (CPM), composite peak strain (CPS) and percentage area of bone ingrowth. The RSA cup migration at 3 months was used to corroborate the FE output metrics. Qualitatively, all FE-predicted metrics followed a similar rank order as the in vivo RSA 3D migration data. The two cases with the lowest predicted CPM (<20 µm), lowest CPS (<0.0041), and high bone modulus (>917 MPa) were confirmed to have the lowest in vivo RSA 3D migration (<0.14 mm). The two cases with the largest predicted CPM (>80 µm), larger CPS (>0.0119) and lowest bone modulus (<472 MPa) were confirmed to have the largest in vivo RSA 3D migration (>0.78 mm). This study enabled the first corroboration between tailored musculoskeletal and FE model predictions with in vivo RSA cup migration. Investigation of additional patient-matched CT, gait, and RSA examinations may allow further development and validation of FE models.

The Effect of Patient-Related Factors on the Primary Fixation of PEEK and Titanium Tibial Components: A Population-Based FE Study

Polyetheretherketone (PEEK) is of interest as implant material for cementless tibial total knee arthroplasty (TKA) components due to its potential advantages. One main advantage is that the stiffness of PEEK closely resembles the stiffness of bone, potentially avoiding peri-prosthetic stress-shielding. When introducing a new implant material for cementless TKA designs, it is essential to study its effect on the primary fixation. The primary fixation may be influenced by patient factors such as age, gender, and body mass index (BMI). Therefore, the research objectives of this finite element (FE) study were to investigate the effect of material (PEEK vs. titanium) and patient characteristics on the primary fixation (i.e., micromotions) of a cementless tibial tray component. A total of 296 FE models of 74 tibiae were created with either PEEK or titanium material properties, under gait and squat loading conditions. Overall, the PEEK models generated larger peak micromotions than the titanium models. Differences were seen in the micromotion distributions between the PEEK and titanium models for both the gait and squat models. The micromotions of all tibial models significantly increased with BMI, while gender and age did not influence micromotions.

Vertebral Fracture Risk Thresholds from Phantom-Less Quantitative Computed Tomography-Based Finite Element Modeling Correlate to Phantom-Based Outcomes

INTRODUCTION

Osteoporosis indicates weakened bones and heightened fracture susceptibility due to diminished bone quality. Dual-energy x-ray absorptiometry is unable to assess bone strength. Volumetric bone mineral density (vBMD) from quantitative computed tomography (QCT) has been used to establish guidelines as equivalent measurements for osteoporosis. QCT-based finite element analysis (FEA) has been implemented using calibration phantoms to establish bone strength thresholds based on the established vBMD. The primary aim was to validate vertebral failure load thresholds using a phantom-less approach with previously established thresholds, advancing a phantom-free approach for fracture risk prediction.

METHODOLOGY

A controlled cohort of 108 subjects (68 females) was used to validate sex-specific vertebral fracture load thresholds for normal, osteopenic, and osteoporotic subjects, obtained using a QCT/FEA-based phantom-less calibration approach and two material equations.

RESULTS

There were strong prediction correlations between the phantom-less and phantom-based methods (R2: 0.95 and 0.97 for males, and R2: 0.96 and 0.98 for females) based on the two equations. Bland Altman plots and paired t-tests showed no significant differences between methods. Predictions for bone strengths and thresholds using the phantom-less method matched those obtained using the phantom calibration and those previously established, with ≤4500 N (fragile) and ≥6000 N (normal) bone strength in females, and ≤6500 N (fragile) and ≥8500 N (normal) bone strength in males.

CONCLUSION

Phantom-less QCT-based FEA can allow for prospective and retrospective studies evaluating incidental vertebral fracture risk along the spine and their association with spine curvature and/or fracture etiology. The findings of this study further supported the application of phantom-less QCT-based FEA modeling to predict vertebral strength, aiding in identifying individuals prone to fractures. This reinforces the rationale for adopting this method as a comprehensive approach in predicting and managing fracture risk.

Quantifying Bone Strength Deficits in Young Adults Born Extremely Preterm or Extremely Low Birth Weight

The long-term bone health of young adults born extremely preterm (EP; <28 weeks' gestation) or extremely low birth weight (ELBW; <1000 g birth weight) in the post-surfactant era (since the early 1990s) is unclear. This study investigated their bone structure and estimated bone strength using peripheral quantitative computed tomography (pQCT)-based finite element modeling (pQCT-FEM). Results using this technique have been associated with bone fragility in several clinical settings. Participants comprised 161 EP/ELBW survivors (46.0% male) and 122 contemporaneous term-born (44.3% male), normal birth weight controls born in Victoria, Australia, during 1991-1992. At age 25 years, participants underwent pQCT at 4% and 66% of tibia and radius length, which was analyzed using pQCT-FEM. Groups were compared using linear regression and adjusted for height and weight. An interaction term between group and sex was added to assess group differences between sexes. Parameters measured included compressive stiffness (kcomp ), torsional stiffness (ktorsion ), and bending stiffness (kbend ). EP/ELBW survivors were shorter than the controls, but their weights were similar. Several unadjusted tibial pQCT-FEM parameters were lower in the EP/ELBW group. Height- and weight-adjusted ktorsion at 66% tibia remained lower in EP/ELBW (mean difference [95% confidence interval] -180 [-352, -8] Nm/deg). The evidence for group differences in ktorsion and kbend at 66% tibia was stronger among males than females (pinteractions  <0.05). There was little evidence for group differences in adjusted radial models. Lower height- and weight-adjusted pQCT-FEM measures in EP/ELBW compared with controls suggest a clinically relevant increase in predicted long-term fracture risk in EP/ELBW survivors, particularly males. Future pQCT-FEM studies should utilize the tibial pQCT images because of the greater variability in the radius possibly related to lower measurement precision. © 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).

Opportunistic Screening With CT: Comparison of Phantomless BMD Calibration Methods

Opportunistic screening is a new promising technique to identify individuals at high risk for osteoporotic fracture using computed tomography (CT) scans originally acquired for an clinical purpose unrelated to osteoporosis. In these CT scans, a calibration phantom traditionally required to convert measured CT values to bone mineral density (BMD) is missing. As an alternative, phantomless calibration has been developed. This study aimed to review the principles of four existing phantomless calibration methods and to compare their performance against the gold standard of simultaneous calibration (ΔBMD). All methods were applied to a dataset of 350 females scanned with a highly standardized CT protocol (DS1) and to a second dataset of 114 patients (38 female) from clinical routine covering a large range of CT acquisition and reconstruction parameters (DS2). Three of the phantomless calibration methods must be precalibrated with a reference dataset containing a calibration phantom. Sixty scans from DS1 and 57 from DS2 were randomly selected for this precalibration. For each phantomless calibration method first the best combination of internal reference materials (IMs) was selected. These were either air and blood or subcutaneous adipose tissue, blood, and cortical bone. In addition, for phantomless calibration a fifth method based on average calibration parameters derived from the reference dataset was applied. For DS1, ΔBMD results (mean ± standard deviation) for the phantomless calibration methods requiring a precalibration ranged from 0.1 ± 2.7 mg/cm3 to 2.4 ± 3.5 mg/cm3 with similar means but significantly higher standard deviations for DS2. Performance of the phantomless calibration method, which does not require a precalibration was worse (ΔBMD DS1: 12.6 ± 13.2 mg/cm3 , DS2: 0.5 ± 8.8 mg/cm3 ). In conclusion, phantomless BMD calibration performs well if precalibrated with a reference dataset. © 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).

Nanocomposite orthopaedic bone cement combining long-acting dual antimicrobial drugs

Antibiotic loaded bone cements are widely used in total joint replacement (TJR); despite many limitations such as a burst release which leads to antibiotic concentration below inhibitory levels and possibly contributing to the selection of antibiotic resistant strains. In order to address such limitations and to simultaneously address antibiotic resistance and short-term antimicrobial activity, we developed a nanocomposite bone cement capable of providing a controlled release of antimicrobial agents from bone cement to act as prophylaxis or treatment against prosthetic joint infections (PJIs). Gentamicin and chlorhexidine were loaded in combination on silica nanoparticles surface using layer-by-layer coating technique (LbL) combining hydrolysable and non-hydrolysable polymers. The drug release from the nanocomposite continued for >50 days at concentrations higher than the commercial formulation containing the same amount of antimicrobial drugs, where burst release for few days were observed. Moreover, the nanocomposite bone cement showed superior antimicrobial inhibition without adversely affecting the mechanical properties or the ability of osteoblasts to grow. In vivo experiments with an infected bone lesion model along with mass-spectrometric analysis also provided further evidence of efficacy and safety of the implanted nanocomposite material as well as its prolonged drug eluting profile. The developed nanocomposite bone cement has the potential to reduce PJIs and enable treatment of resistant established infections; moreover, the newly developed LbL based nano-delivery system may also have wider applications in reducing the threat posed by antimicrobial resistance.

Addressing Challenges of Opportunistic Computed Tomography Bone Mineral Density Analysis

Computed tomography (CT) offers advanced biomedical imaging of the body and is broadly utilized for clinical diagnosis. Traditionally, clinical CT scans have not been used for volumetric bone mineral density (vBMD) assessment; however, computational advances can now leverage clinically obtained CT data for the secondary analysis of bone, known as opportunistic CT analysis. Initial applications focused on using clinically acquired CT scans for secondary osteoporosis screening, but opportunistic CT analysis can also be applied to answer research questions related to vBMD changes in response to various disease states. There are several considerations for opportunistic CT analysis, including scan acquisition, contrast enhancement, the internal calibration technique, and bone segmentation, but there remains no consensus on applying these methods. These factors may influence vBMD measures and therefore the robustness of the opportunistic CT analysis. Further research and standardization efforts are needed to establish a consensus and optimize the application of opportunistic CT analysis for accurate and reliable assessment of vBMD in clinical and research settings. This review summarizes the current state of opportunistic CT analysis, highlighting its potential and addressing the associated challenges.

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%.

Opportunistic Screening Techniques for Analysis of CT Scans

PURPOSE OF REVIEW

Opportunistic screening is a combination of techniques to identify subjects of high risk for osteoporotic fracture using routine clinical CT scans prescribed for diagnoses unrelated to osteoporosis. The two main components are automated detection of vertebral fractures and measurement of bone mineral density (BMD) in CT scans, in which a phantom for calibration of CT to BMD values is not used. This review describes the particular challenges of opportunistic screening and provides an overview and comparison of current techniques used for opportunistic screening. The review further outlines the performance of opportunistic screening.

RECENT FINDINGS

A wide range of technologies for the automatic detection of vertebral fractures have been developed and successfully validated. Most of them are based on artificial intelligence algorithms. The automated differentiation of osteoporotic from traumatic fractures and vertebral deformities unrelated to osteoporosis, the grading of vertebral fracture severity, and the detection of mild vertebral fractures is still problematic. The accuracy of automated fracture detection compared to classical radiological semi-quantitative Genant scoring is about 80%. Accuracy errors of alternative BMD calibration methods compared to simultaneous phantom-based calibration used in standard quantitative CT (QCT) range from below 5% to about 10%. The impact of contrast agents, frequently administered in clinical CT on the determination of BMD and on fracture risk determination is still controversial. Opportunistic screening, the identification of vertebral fracture and the measurement of BMD using clinical routine CT scans, is feasible but corresponding techniques still need to be integrated into the clinical workflow and further validated with respect to the prediction of fracture risk.

Finite element analysis of screw fixation durability under multiple boundary and loading conditions for a custom pelvic implant

Despite showing promising functional outcomes for pelvic reconstruction after sarcoma resection, custom-made pelvic implants continue to exhibit high complication rates due to fixation failures. Patient-specific finite element models have been utilized by researchers to evaluate implant durability. However, the effect of assumed boundary and loading conditions on failure analysis results of fixation screws remains unknown. In this study, the postoperative stress distributions in the fixation screws of a state-of-the-art custom-made pelvic implant were simulated, and the risk of failure was estimated under various combinations of two bone-implant interaction models (tied vs. frictional contact) and four load cases from level-ground walking and stair activities. The study found that the average weighted peak von Mises stress could increase by 22-fold when the bone-implant interactions were modeled with a frictional contact model instead of a tied model, and the likelihood of fatigue and pullout failure for each screw could change dramatically when different combinations of boundary and loading conditions were used. The inclusion of additional boundary and loading conditions led to a more reliable analysis of fixation durability. These findings demonstrated the importance of simulating multiple boundary conditions and load cases for comprehensive implant design evaluation using finite element analysis.

Fracture risk assessment and evaluation of femoroplasty in metastatic proximal femurs. An in vivo CT-based finite element study

The goal of this study was twofold. First, we aimed to evaluate the accuracy of a finite element (FE) model to predict bone fracture in cancer patients with proximal femoral bone metastases. Second, we evaluated whether femoroplasty could effectively reduce fracture risk. A total of 89 patients were included, with 101 proximal femurs affected with bone metastases. The accuracy of the model to predict fracture was evaluated by comparing the FE failure load, normalized for body weight, against the actual occurrence of fracture during a 6-month follow-up. Using a critical threshold, the model could identify whether femurs underwent fracture with a sensitivity of 92% and a specificity of 66%. A virtual treatment with femoroplasty was simulated in a subset of 34 out of the 101 femurs; only femurs with one or more well-defined lytic lesions were considered eligible for femoroplasty. We modeled their lesions, as well as the surrounding 4 mm of trabecular bone, to be augmented with bone cement. The simulation of femoroplasty increased the median failure load of the FE model by 57% for lesions located in the head/neck of the femur. At this lesion location, all high risk femurs that had fractured during follow-up effectively moved from a failure load below the critical threshold to a value above. For lesions located in the trochanteric region, no definite improvement in failure load was found. Although additional validation studies are required, our results suggest that femoroplasty can effectively reduce fracture risk for several osteolytic lesions in the femoral head/neck.

A Patient-Specific Fracture Risk Assessment Tool for Femoral Bone Metastases: Using the Bone Strength (BOS) Score in Clinical Practice

Patients with femoral metastases are at risk of fracturing bones. It is important to prevent fractures in order to maintain mobility and quality of life. The BOne Strength (BOS) score is based on a computed tomography (CT)-based patient-specific finite element (FE) computer model that objectively calculates bone strength. In this pilot study, the added clinical value of the BOS score towards treatment-related decision making was assessed. In December 2019, the BOS score was implemented in four radiotherapy centers. The BOS scores and fracture risks of individual patients were calculated and returned to the physician to assist in treatment decisions. The physicians filled out a questionnaire, which was qualitatively analyzed. A follow-up to identify fractures and/or death was performed after six months. Until June 2021, 42 BOS scores were delivered (20 high, 9 moderate, and 13 low fracture risk). In 48%, the BOS score led to an adaptation of treatment plans. Physicians indicated that the BOS score provided objective insight into fracture risk, was reassuring for physicians and patients, and improved multidisciplinary discussions and shared decision making. In conclusion, the BOS score is an objective tool to assess fracture risk in femoral bone metastases and aids physicians and patients in making a more informed decision regarding the most appropriate treatment.

Assigning trabecular bone material properties in finite element models simulating the pelvis before and after the development of peri-prosthetic osteolytic lesions

Estimating strain distribution in the acetabulum before and after the development of peri-prosthetic osteolytic lesions secondary to total hip arthroplasty may assist with understanding the pathogenesis of this condition. This could be achieved by performing patient-specific finite element analysis of (1) total hip arthroplasty recipients with developed acetabular osteolytic lesions, and (2) models simulating the patient's pelvis and implant immediately after primary surgery. State of the art patient-specific total hip arthroplasty finite element analysis simulations obtain trabecular bone material properties from Hounsfield units within computed tomography (CT) scans of patients. However, this is not feasible when an implant is already in situ due to metal artefact disruption and, in turn, incorrectly reproduced Hounsfield units. Therefore, alternative methods of assigning trabecular bone material properties within such models were tested and strain results compared. It was found that assigning set material properties throughout the trabecular bone geometry was sufficient for the desired application. Simulating the primary implant and pelvis requires geometric and material based assumptions. Therefore, comparisons were made between strain values obtained from simulated primary models, from state of the art methods using material properties obtained from intact bone within a CT scan, and from models with osteolytic lesions. Strain values found using the finite element models simulating the pelvis before osteolytic lesion developed were considerably closer to those found using state of the art methods than those found for the bone loss models. These models could be used to determine relationships between strain distribution and factors such as bone loss.

Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure

Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.

A Three-Dimensional Cement Quantification Method for Decision Prediction of Vertebral Recompression after Vertebroplasty

Objective

Proposing parameters to quantify cement distribution and increasing accuracy for decision prediction of vertebroplasty postoperative complication.

Methods

Finite element analysis was used to biomechanically assess vertebral mechanics (n = 51) after percutaneous vertebroplasty (PVP) or kyphoplasty (PKP). The vertebral space was divided into 27 portions. The numbers of cement occupied portions and numbers of cement-endplate contact portions were defined as overall distribution number (oDN) and overall endplate contact number (oEP), respectively. And cement distribution was parametrized by oDN and oEP. The determination coefficients of vertebral mechanics and parameters (R 2) can validate the correlation of proposed parameters with vertebral mechanics.

Results

oDN and oEP were mainly correlated with failure load (R 2 = 0.729) and stiffness (R 2 = 0.684), respectively. oDN, oEP, failure load, and stiffness had obvious difference between the PVP group and the PKP group (P < 0.05). The regional endplate contact number in the front column is most correlated with vertebral stiffness (R 2 = 0.59) among all regional parameters. Cement volume and volume fraction are not dominant factors of vertebral augmentation, and they are not suitable for postoperative fracture risk prediction.

Conclusions

Proposed parameters with high correlation on vertebral mechanics are promising for clinical utility. The oDN and oEP can strongly affect augmented vertebral mechanics thus is suitable for postoperative fracture risk prediction. The parameters are beneficial for decision-making process of revision surgery necessity. Parametrized methods are also favorable for surgeon's preoperative planning. The methods can be inspirational for clinical image recognition development and auxiliary diagnosis.

BMD accuracy errors specific to phantomless calibration of CT scans of the lumbar spine

Opportunistic screening using existing CT images may be a new strategy to identify subjects at increased risk for osteoporotic fracture. Low bone mineral density (BMD) is a key parameter but routine clinical CT scans do not include a calibration phantom to calculate BMD from the measured CT values. An alternative is internal or phantomless calibration, which is based on the CT values of air and of internal tissues of the subject such as blood, muscle or adipose tissue. However, the composition and as a consequence the CT values of these so-called internal calibration materials vary among subjects, which introduces additional BMD accuracy errors compared to phantom based calibration. The objective of this study was to quantify these accuracy errors and to identify optimum combinations of internal calibration materials (IM) for BMD assessments in opportunistic screening. Based on the base material decomposition theory we demonstrate how BMD can be derived from the CT values of the internal calibration materials. 121 CT datasets of the lumbar spine form postmenopausal women were used to determine the population variance of blood assessed in the aorta or the inferior vena cava, skeletal muscle of the erector spinae or psoas, subcutaneous adipose tissue (SAT) and air. The corresponding standard deviations were used for error propagation to determine phantomless calibration related BMD accuracy errors. Using a CT value of 150 HU, a typical value of trabecular bone, simulated BMD accuracy errors for most IM combinations containing air as one of the two base materials were below 5% or 6 mg/cm³. The lowest errors were determined for the combination of blood and air (<2 mg/cm³). The combination of blood and skeletal muscle resulted in higher errors (>10.5% or >12 mg/cm³) and is not recommended. Due to possible age-related differences in tissue composition, the selection of IMs is suggested to be adapted according to the measured subject. In younger subjects without significant aortic calcifications, air and blood of the aorta may be the best combination whereas in elderly subjects, air and SAT (error of 4%) may be preferable. The use of skeletal muscle as one of the two IMs is discouraged, in particular in elderly subjects because of varying fatty infiltration. A practical implementation of the internal calibration with different IM pairs confirmed the theoretical results. In summary, compared to a phantom based calibration the phantomless approach used for opportunistic screening creates additional BMD accuracy errors of 2% or more, dependent on the used internal reference tissues. The impact on fracture prediction still must be evaluated.

The effect of variations in CT scan protocol on femoral finite element failure load assessment using phantomless calibration

Recently, it was shown that fracture risk assessment in patients with femoral bone metastases using Finite Element (FE) modeling can be performed using a calibration phantom or air-fat-muscle calibration and that non-patient-specific calibration was less favorable. The purpose of this study was to investigate if phantomless calibration can be used instead of phantom calibration when different CT protocols are used. Differences in effect of CT protocols on Hounsfield units (HU), calculated bone mineral density (BMD) and FE failure loads between phantom and two methods of phantomless calibrations were studied. Five human cadaver lower limbs were scanned atop a calibration phantom according to a standard scanning protocol and seven additional commonly deviating protocols including current, peak kilovoltage (kVp), slice thickness, rotation time, field of view, reconstruction kernel, and reconstruction algorithm. The HUs of the scans were calibrated to BMD (in mg/cm³) using the calibration phantom as well as using air-fat-muscle and non-patient-specific calibration, resulting in three models for each scan. FE models were created, and failure loads were calculated by simulating an axial load on the femur. HU, calculated BMD and failure load of all protocols were compared between the three calibration methods. The different protocols showed little variation in HU, BMD and failure load. However, compared to phantom calibration, changing the kVp resulted in a relatively large decrease of approximately 10% in mean HU and BMD of the trabecular and cortical region of interest (ROI), resulting in a 13.8% and 13.4% lower failure load when air-fat-muscle and non-patient-specific calibrations were used, respectively. In conclusion, while we observed significant correlations between air-fat-muscle calibration and phantom calibration as well as between non-patient-specific calibration and phantom calibration, our sample size was too small to prove that either of these calibration approaches was superior. Further studies are necessary to test whether air-fat-muscle or non-patient-specific calibration could replace phantom calibration in case of different scanning protocols.

Polka dot cementless talar component in enhancing total ankle replacement fixation: A parametric study using the finite element analysis approach

The primary stability of a total ankle replacement (TAR) is essential in preventing long-term aseptic loosening failure and could be quantified based on micromotion at the bone-prosthesis interface subjected to physiological loading during the normal walking. A 3D finite element analysis was conducted to investigate the current commercial STAR™ Ankle TAR bone-prosthesis interface relative micromotion (BPIRM) with addition of the talus bone minimum principal bone stresses (MPBS). Comparison was made to the proposed polka dot designs with the hemispheric feature that was demonstrated to enhance BPIRM. Parametric studies were conducted on the hemispheric features with changes in its diameter, length and shape. The FE results indicated high BPIRM at the talar component was primarily contributed by de-bonding (in the normal direction) between the talus bone and talar component. The MPBS were found to be most significant in the superior anterior and superior medial regions of the talus bone. When the pin length was increased from 1.5 to 3 mm, the BPIRM was predicted to fall below 50 μm in favour of bone in-growth. Based on the practicality of the prosthesis implantation during the surgical procedure, the final design that incorporated both the initial polka dot and 3 mm pin length in a crisscross manner was deemed to be a favorable design with reduced BPIRM and MPBS hence lowering the risk of long-term aseptic loosening.

Sources of error in bone mineral density estimates from quantitative CT

Bone mineral density (BMD) estimates from quantitative computed tomography (QCT) have proven useful for opportunistic screening of osteoporosis, treatment monitoring, and bone strength measurement. These estimates are subject to bias and variance from a variety of sources related to the imaging equipment, methods applied in the estimation procedure, and the patients themselves. In this article, we review the literature to describe the sources and sizes of error in spine and hip BMD estimates from single-energy QCT that can result from factors related to the scanner, imaging techniques, imaging subject, calibration phantom, and calibration approach. We also describe the baseline variance that can be expected based on repeatability and reproducibility studies. Though reproducible BMD estimates may be achievable with QCT, a thorough understanding of the potential sources of error and their size relative to the diagnostic task is essential to their appropriate and meaningful interpretation.

Computational tibial bone remodeling over a population after total knee arthroplasty: A comparative study

Periprosthetic bone loss is an important factor in tibial implant failure mechanisms in total knee arthroplasty (TKA). The purpose of this study was to validate computational postoperative bone response using longitudinal clinical DEXA densities. Computational remodeling outcome over a population was obtained by incorporating the strain‐adaptive remodeling theory in finite element (FE) simulations of 26 different tibiae. Physiological loading conditions were applied, and bone mineral density (BMD) in three different regions of interest (ROIs) was considered over a postoperative time of 15 years. BMD outcome was compared directly to previously reported clinical BMD data of a comparable TKA cohort. Similar trends between computational and clinical bone remodeling over time were observed in the two proximal ROIs, with most rapid bone loss taking place in the initial months after TKA and BMD starting to level in the following years. The extent of absolute proximal BMD change was underestimated in the FE population compared with the clinical subject group, which might be the result of significantly higher initial clinical baseline BMD values. Large differences in remodeling response were found in the distal ROI, in which resorption was measured clinically, but a large BMD increase was predicted by the FE models. Multiple computational limitations, related to the FE mesh, loading conditions, and strain‐adaptive algorithm, likely contributed to the extensive local bone formation. Further research incorporating subject‐specific comparisons using follow‐up CT scans and more extensive physiological knee loading is recommended to optimize bone remodeling more distal to the tibial baseplate.

Heterogeneous material mapping methods for patient-specific finite element models of pelvic trabecular bone: A convergence study

Patient-specific finite element (FE) models of bone require the assignment of heterogeneous material properties extracted from the subject's computed tomography (CT) images. Though node-based (NB) and element-based (EB) material mapping methods (MMMs) have been proposed, the sensitivity and convergence of FE models to MMM for varying mesh sizes are not well understood. In this work, CT-derived and synthetic bone material data were used to evaluate the effect of MMM on results from FE analyses. Pelvic trabecular bone data was extracted from CT images of six subjects, while synthetic data were created to resemble trabecular bone properties. The numerical convergence of FE bone models using different MMMs were evaluated for strain energy, von-Mises stress, and strain. NB and EB MMMs both demonstrated good convergence regarding total strain energy, with the EB method having a slight edge over the NB. However, at the local level (e.g., maximum stress and strain), FE results were sensitive to the field type, MMM, and the FE mesh size. The EB method exhibited superior performance in finer meshes relative to the voxel size. The NB method converged better than did the EB method for coarser meshes. These findings may lead to higher-fidelity patient-specific FE bone models.

Development of a crushable foam model for human trabecular bone

Finite element (FE) simulations can be used to evaluate the mechanical behavior of human bone and allow for quantitative prediction of press-fit implant fixation. An adequate material model that captures post-yield behavior is essential for a realistic simulation. The crushable foam (CF) model is a constitutive model that has recently been proposed in this regard. Compression tests under uniaxial and confined loading conditions were performed on 59 human trabecular bone specimens. Three essential material parameters were obtained as a function of bone mineral density (BMD) to develop the isotropic CF model. The related constitutive rule was implemented in FE models and the results were compared to the experimental data. The CF model provided an accurate simulation of uniaxial compression tests and the post-yield behavior of the stress-strain was well-matched with the experimental results. The model was able to reproduce the confined response of the bone up to 15% of strain. This model allows for simulation of the mechanical behavior of the cellular structure of human bone and adequately predicts the post-yield response of trabecular bone, particularly under uniaxial loading conditions. The model can be further improved to simulate bone collapse due to local overload around orthopaedic implants.

Fracture Risk of Long Bone Metastases: A Review of Current and New Decision-Making Tools for Prophylactic Surgery

Simple Summary

Long bone metastases are frequently a pivotal point in the oncological history of patients. Weakening of the bone results in pathologic fractures that not only compromise patient function but also their survival. Therefore, the main issue for tumor boards remains timely assessment of the risk of fracture, as this is a key consideration in providing preventive surgery while also avoiding overtreatment. As the Mirels scoring system takes into account both the radiological and the clinical criteria, it has been used worldwide since the 1990s. However, due to increasing concern regarding the lack of accuracy, new thresholds have been defined for the identification of impending fractures that require prophylactic surgery, on the basis of axial cortical involvement and biomechanical models involving quantitative computed tomography. The aim of this review is to establish a state-of-the-art of the risk assessment of long bone metastases fractures, from simple radiologic scores to more complex multidimensional bone models, in order to define new decision-making tools.

Abstract

Long bone pathological fractures very much reflect bone metastases morbidity in many types of cancer. Bearing in mind that they not only compromise patient function but also survival, identifying impending fractures before the actual event is one of the main concerns for tumor boards. Indeed, timely prophylactic surgery has been demonstrated to increase patient quality of life as well as survival. However, early surgery for long bone metastases remains controversial as the current fracture risk assessment tools lack accuracy. This review first focuses on the gold standard Mirels rating system. It then explores other unique imaging thresholds such as axial or circumferential cortical involvement and the merits of nuclear imaging tools. To overcome the lack of specificity, other fracture prediction strategies have focused on biomechanical models based on quantitative computed tomography (CT): computed tomography rigidity analysis (CT-RA) and finite element analysis (CT-FEA). Despite their higher specificities in impending fracture assessment, their limited availability, along with a need for standardization, have limited their use in everyday practice. Currently, the prediction of long bone pathologic fractures is a multifactorial process. In this regard, machine learning could potentially be of value by taking into account clinical survival prediction as well as clinical and improved CT-RA/FEA data.

Opportunistic application of phantom-less calibration methods for fracture risk prediction using QCT/FEA

OBJECTIVES

Quantitative computed tomography (QCT)-based finite element analysis (FEA) implements a calibration phantom to estimate bone mineral density (BMD) and assign material properties to the models. The objectives of this study were to (1) propose robust phantom-less calibration methods, using subject-specific tissues, to obtain vertebral fracture properties estimations using QCT/FEA; and (2) correlate QCT/FEA predictions to DXA values of areal BMD.

METHODS

Eighty of a cohort of 111 clinical QCT scans were used to obtain subject-specific parameters using a phantom calibration approach and for the development of the phantom-less calibration equations. Equations were developed based on the HU measured from various soft tissues and regions, and using multiple linear regression analyses. Thirty-one additional QCT scans were used for cross-validation of QCT/FEA estimated fracture loads from the L₃ vertebrae based on the phantom and phantom-less equations. Finally, QCT/FEA-predicted fracture loads were correlated with aBMD obtained from DXA.

RESULTS

Overall, 217 QCT/FEA models from 31 subjects (20 females, 11 men) with mean ages of 69.6 (13.1) and 67.3 (14) were used to cross-validate the phantom-less equations and assess bone strength. The proposed phantom-less equations showed high correlations with phantom-based estimates of BMD (99%). Cross-validation of QCT/FEA-predicted fracture loads from phantom-less equations and phantom-specific outcomes resulted in high correlations for all proposed methods (0.94-0.99). QCT/FEA correlation outcomes from the phantom-less equations and DXA-aBMD were moderately high (0.64-0.68).

CONCLUSIONS

The proposed QCT/FEA subject-specific phantom-less calibration methods demonstrated the potential to be applied to both prospective and retrospective applications in the clinical setting.

KEY POINTS

• QCT/FEA overcomes the disadvantages of DXA and improves fracture properties predictions of vertebrae. • QCT/FEA fracture estimates using the phantom-less approach highly correlated to values obtained using a calibration phantom. • QCT/FEA prediction using a phantom-less approach is an accurate alternative over phantom-based methods.

Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses

Osteoporosis affects an increasing number of people every year and patient specific finite element analysis of the femur has been proposed to identify patients that could benefit from preventative treatment. The aim of this study was to demonstrate, verify, and validate an objective process for selecting tissues for use as the basis of phantomless calibration to enable patient specific finite element analysis derived hip fracture risk prediction. Retrospective reanalysis of patient computed tomography (CT) scans has the potential to yield insights into more accurate prediction of osteoporotic fracture. Bone mineral density (BMD) specific calibration scans are not typically captured during routine clinical practice. Tissue-based BMD calibration can therefore empower the retrospective study of patient CT scans captured during routine clinical practice. Together the method for selecting tissues as the basis for phantomless calibration coupled with the post-processing steps for deriving a calibration equation using the selected tissues provide an estimation of quantitative equivalent density results derived using calibration phantoms. Patient tissues from a retrospective cohort of 211 patients were evaluated. The best phantomless calibration resulted in a femoral strength (FS) [N] bias of 0.069 ± 0.07% over FS derived from inline calibration and a BMD [kg/cm³] bias of 0.038 ± 0.037% over BMD derived from inline calibration. The phantomless calibration slope for the best method presented was within the range of patient specific calibration curves available for comparison and demonstrated a small bias of 0.028 ± 0.054 HU/(mg/cm³), assuming the Mindways Model 3 BMD inline calibration phantom as the gold standard. The presented method of estimating a calibration equation from tissues showed promise for CT-based femoral fracture analyses of retrospective cohorts without readily available calibration data.

Effect of CT imaging on the accuracy of the finite element modelling in bone

The finite element (FE) analysis is a highly promising tool to simulate the behaviour of bone. Skeletal FE models in clinical routine rely on the information about the geometry and bone mineral density distribution from quantitative computed tomography (CT) imaging systems. Several parameters in CT imaging have been reported to affect the accuracy of FE models. FE models of bone are exclusively developed in vitro under scanning conditions deviating from the clinical setting, resulting in variability of FE results (< 10%). Slice thickness and field of view had little effect on FE predicted bone behaviour (≤ 4%), while the reconstruction kernels showed to have a larger effect (≤ 20%). Due to large interscanner variations (≤ 20%), the translation from an experimental model into clinical reality is a critical step. Those variations are assumed to be mostly caused by different “black box” reconstruction kernels and the varying frequency of higher density voxels, representing cortical bone. Considering the low number of studies together with the significant effect of CT imaging on the finite element model outcome leading to high variability in the predicted behaviour, we propose further systematic research and validation studies, ideally preceding multicentre and longitudinal studies.

Population-based effect of total knee arthroplasty alignment on simulated tibial bone remodeling

Periprosthetic bone loss is an important factor in tibial implant failure mechanisms in total knee arthroplasty (TKA). The purpose of this study was to determine the effect of postoperative knee alignment and population variation on tibial bone remodeling, to assess long-term stability of a knee replacement. Strain-adaptive finite element (FE) remodeling simulations were conducted following kinematic and mechanical alignment of a cemented fixed-bearing implant after TKA; kinematic TKA alignment was assumed to be more consistent with the preoperative varus alignment, while mechanical alignment was defined according to the neutral mechanical axes. To account for the effect of tibial variation on the outcome, bone remodeling was considered over a population of 47 subjects. Bone mineral density (BMD) was analyzed over three regions of interest (ROIs); medial, lateral and distal. The two proximal ROIs showed an average decrease in BMD in both alignments after two years. Greater overall proximal bone loss was found in the mechanical postoperative knees in comparison with kinematically aligned implants. Bone resorption was also concentrated more medially in mechanical alignment: increased medial ROI bone loss was found in every subject compared to kinematic alignment; while in the lateral ROI, higher regional two-year BMD was found in 39 of the 47 cases (82.9%) following mechanical alignment. Two distinct remodeling pathways were identified over both alignments, based on the variance in density change over the population; displaying predominant bone apposition either around the distal tip of the keel or at the lateral cortex. This study demonstrates that correction of native varus alignment to neutral mechanical alignment leads to an increase in medial bone resorption. Large variation between specimens illustrates the benefit of population-based FE analyses over single model studies.

CT Phantom Evaluation of 67,392 American College of Radiology Accreditation Examinations: Implications for Opportunistic Screening of Osteoporosis Using CT

OBJECTIVE. The purpose of this study was to investigate whether systematic bias in attenuation measurements occurs among CT scanners made by four major manufacturers and the relevance of this bias regarding opportunistic screening for osteoporosis. MATERIALS AND METHODS. Data on attenuation measurement accuracy were acquired using the American College of Radiology (ACR) accreditation phantom and were evaluated in a blinded fashion for four CT manufacturers (8500 accreditation submissions for manufacturer A; 18,575 for manufacturer B; 8278 for manufacturer C; and 32,039 for manufacturer D). The attenuation value for water, acrylic (surrogate for trabecular bone), and Teflon (surrogate for cortical bone; Chemours) materials for an adult abdominal CT technique (120 kV, 240 mA, standard reconstruction algorithm) was used in the analysis. Differences in attenuation value across all manufacturers were assessed using the Kruskal-Wallis test followed by a post hoc test for pairwise comparisons. RESULTS. The mean attenuation value for water ranged from -0.3 to 2.7 HU, with highly significant differences among all manufacturers (p < 0.001). For the trabecular bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 120.9 (SD, 3.5), 124.6 (3.3), 126.9 (4.4), and 123.9 (3.4) HU for manufacturers A, B, C, and D, respectively. For the cortical bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 939.0 (14.2), 874.3 (13.3), 897.6 (11.3), and 912.7 (13.4) HU for manufacturers A, B, C, and D, respectively. CONCLUSION. CT scanners made by different manufacturers show systematic offsets in attenuation measurement when compared with each other. Knowledge of these off-sets is useful for optimizing the accuracy of opportunistic diagnosis of osteoporosis.

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.

Fracture risk assessment and clinical decision making for patients with metastatic bone disease

Metastatic breast, prostate, lung, and other cancers often affect bone, causing pain, increasing fracture risk, and decreasing function. Management of metastatic bone disease (MBD) is clinically challenging when there is potential but uncertain risk of pathological fracture. Management of MBD has become a major focus within orthopedic oncology with respect to fracture and impending fracture care. If impending skeletal-related events (SREs), particularly pathologic fracture, could be predicted, increasing evidence suggests that prophylactic surgical treatment improves patient outcomes. However, current fracture risk assessment and radiographic metrics do not have high accuracy and have not been combined with relevant patient survival tools. This review first explores the prevalence, incidence, and morbidity of MBD and associated SREs for different cancer types. Strengths and limitations of current fracture risk scoring systems for spinal stability and long bone fracture are highlighted. More recent computed tomography (CT)-based structural rigidity analysis (CTRA) and finite element (FE) analysis methods offer advantages of increased specificity (true negative rate), but are limited in availability. Other fracture prediction approaches including parametric response mapping and positron emission tomography/computed tomography measures show early promise. Substantial new information to inform clinical decision-making includes measures of survival, clinical benefits, and economic analysis of prophylactic treatment compared to after-fracture stabilization. Areas of future research include use of big data and machine learning to predict SREs, greater access and refinement of CTRA/FE approaches, combination of clinical survival prediction tools with radiographically based fracture risk assessment, and net benefit analysis for fracture risk assessment and prophylactic treatment.

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.

Patient-specific finite element computer models improve fracture risk assessments in cancer patients with femoral bone metastases compared to clinical guidelines

PURPOSE

To determine whether patient-specific finite element (FE) computer models are better at assessing fracture risk for femoral bone metastases compared to clinical assessments based on axial cortical involvement on conventional radiographs, as described in current clinical guidelines.

METHODS

Forty-five patients with 50 femoral bone metastases, who were treated with palliative radiotherapy for pain, were included (64% single fraction (8Gy), 36% multiple fractions (5 or 6x4Gy)) and were followed for six months to determine whether they developed a pathological femoral fracture. All plain radiographs available within a two month period prior to radiotherapy were obtained. Patient-specific FE models were constructed based on the geometry and bone density obtained from the baseline quantitative CT scans used for radiotherapy planning. Femoral failure loads normalized for body weight (BW) were calculated. Patients with a failure load of 7.5 x BW or lower were identified as having high fracture risk, whereas patients with a failure load higher than 7.5 x BW were classified as low fracture risk. Experienced assessors measured axial cortical involvement on conventional radiographs. Following clinical guidelines, patients with lesions larger than 30mm were identified as having a high fracture risk. FE predictions were compared to clinical assessments by means of diagnostic accuracy values (sensitivity, specificity and positive (PPV) and negative predictive values (NPV)).

RESULTS

Seven femurs (14%) fractured during follow-up. Median time to fracture was 8 weeks. FE models were better at assessing fracture risk in comparison to axial cortical involvement (sensitivity 100% vs. 86%, specificity 74% vs. 42%, PPV 39% vs. 19%, and NPV 100% vs. 95%, for the FE computer model vs. axial cortical involvement, respectively).

CONCLUSIONS

Patient-specific FE computer models improve fracture risk assessments of femoral bone metastases in advanced cancer patients compared to clinical assessments based on axial cortical involvement, which is currently used in clinical guidelines.