Study of the significance of parameters and their interaction on assessing femoral fracture risk by quantitative statistical analysis

Early assessment of hip fracture helps develop therapeutic and preventive mechanisms that may reduce the occurrence of hip fracture. An accurate assessment of hip fracture risk requires proper consideration of the loads, the physiological and morphological parameters, and the interactions between these parameters. Hence, this study aims at analyzing the significance of parameters and their interactions by conducting a quantitative statistical analysis. A multiple regression model was developed considering different loading directions during a sideways fall (angle [Formula: see text] and [Formula: see text] on the coronal and transverse planes, respectively), age, gender, patient weight, height, and femur morphology as independent parameters and Fracture Risk Index (FRI) as a dependent parameter. Strain-based criteria were used for the calculation of FRI with the maximum principal strain obtained from quantitative computed tomography-based finite element analysis. The statistical result shows that [Formula: see text] [Formula: see text], age [Formula: see text], true moment length [Formula: see text], gender [Formula: see text], FNA [Formula: see text], height [Formula: see text], and FSL [Formula: see text] significantly affect FRI where [Formula: see text] is the most influential parameter. The significance of two-level interaction [Formula: see text] and three-level interaction [Formula: see text] shows that the effect of parameters is dissimilar and depends on other parameters suggesting the variability of FRI from person to person.

Short-Term Precision Error of Bone Strain Index, a New DXA-Based Finite Element Analysis Software for Assessing Hip Strength

Bone Strain Index (BSI) is a new finite element analysis tool applied to hip dual energy X-ray absorptiometry scans. The aim of this study was to assess the short-term precision error of BSI on the proximal femur, both on a phantom and patients. The International Society for Clinical Densitometry guidelines were followed for short-term precision error assessment. Dual energy X-ray absorptiometry measurements were performed on an anthropomorphic femur phantom that was scanned twice for 30 times, for a total of 60 scans. For the in vivo part, 30 subjects were scanned twice. BSI precision error was compared to that of bone mineral density (BMD). Both for the phantom and the in vivo study BSI reproducibility was lower compared to that of BMD, as the precision error of BSI resulted 3 times higher compared to that BMD. For phantom measurements, the highest precision value was that of total femur (TF) BMD (coefficient of variation [CoV] = 0.63%, reproducibility = 98.24%), while the lowest precision was the femoral neck (FN) BSI (CoV = 3.08%, reproducibility = 91.48%). Similarly, for the in vivo study, the highest precision was found at TF BMD (CoV = 1.36%, reproducibility = 96.22%), while the lowest value of precision was found for FN BSI (CoV = 4.17%, reproducibility = 88.46%). Reproducibility at TF was always better compared to that of the FN. BSI precision error was about 3 times higher compared to BMD, confirming previous results of lumbar spine BSI. The main source of variability of this new software is related to patient positioning.

Beyond Bone Mineral Density: A New Dual X-Ray Absorptiometry Index of Bone Strength to Predict Fragility Fractures, the Bone Strain Index

For a proper assessment of osteoporotic fragility fracture prediction, all aspects regarding bone mineral density, bone texture, geometry and information about strength are necessary, particularly in endocrinological and rheumatological diseases, where bone quality impairment is relevant. Data regarding bone quantity (density) and, partially, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA). Data about bone strength are not yet readily available. To evaluate bone resistance to strain, a new DXA-derived index based on the Finite Element Analysis (FEA) of a greyscale of density distribution measured on spine and femoral scan, namely Bone Strain Index (BSI), has recently been developed. Bone Strain Index includes local information on density distribution, bone geometry and loadings and it differs from bone mineral density (BMD) and other variables of bone quality like trabecular bone score (TBS), which are all based on the quantification of bone mass and distribution averaged over the scanned region. This state of the art review illustrates the methodology of BSI calculation, the findings of its in reproducibility and the preliminary data about its capability to predict fragility fracture and to monitor the follow up of the pharmacological treatment for osteoporosis.

Improving the Hip Fracture Risk Prediction Through 2D Finite Element Models From DXA Images: Validation Against 3D Models

Osteoporotic fracture incidence represents a major social and economic concern in the modern society, where the progressive graying of the population involves an highly increased fracture occurrence. Although the gold standard to diagnose osteoporosis is represented by the T-score measurement, estimated from the Bone Mineral Density (BMD) using Dual-energy X-ray Absorptiometry (DXA), the identification of the subjects at high risk of fracture still remains an issue. From this perspective, the purpose of this work is to investigate the role that DXA-based two-dimensional patient-specific finite element (FE) models of the proximal femur, in combination with T-score, could play in enhancing the risk of fracture estimation. With this aim, 2D FE models were built from DXA images of the 28 post-menopausal female subjects involved. A sideways fall condition was reproduced and a Risk of Fracture (RF^) was computed on the basis of principal strains criteria. The identified RF^ was then compared to that derived from the CT-based models developed in a previous study. The 2D and 3D RF^ turned out to be significantly correlated (Spearman's ρ = 0.66, p < 0.001), highlighting the same patients as those at higher risk. Moreover, the 2D RF^ resulted significantly correlated with the T-score (Spearman's ρ = −0.69, p < 0.001), and managed to better differentiate osteopenic patients, drawing the attention to some of them. The Hip Structural Analysis (HSA) variables explaining the majority of the variance of the 2D and 3D fracture risk were the same as well, i.e., neck-shaft angle and narrow neck buckling ratio. In conclusion, DXA-based FE models, developable from currently available clinical data, appear promising in supporting and integrating the present diagnostic procedure.

Fracture Risk Indices From DXA-Based Finite Element Analysis Predict Incident Fractures Independently From FRAX: The Manitoba BMD Registry

OBJECTIVE

Finite element analysis (FEA) is a computational method to predict the behavior of materials under applied loading. We developed a software tool that automatically performs FEA on dual-energy X-ray absorptiometry hip scans to generate site-specific fracture risk indices (FRIs) that reflect the likelihood of hip fracture from a sideways fall. This longitudinal study examined associations between FRIs and incident fractures.

METHODS

Using the Manitoba Bone Mineral Density (BMD) Registry, femoral neck (FN), intertrochanter (IT), and subtrochanter (ST) FRIs were automatically derived from 13,978 anonymized dual-energy X-ray absorptiometry scans (Prodigy, GE Healthcare) in women and men aged 50 yr or older (mean age 65 yr). Baseline covariates and incident fractures were assessed from population-based data. We compared c-statistics for FRIs vs FN BMD alone and fracture risk assessment (FRAX) probability computed with BMD. Cox regression was used to estimate hazard ratios and 95% confidence intervals (95% CIs) for incident hip, major osteoporotic fracture (MOF) and non-hip MOF adjusted for relevant covariates including age, sex, FN BMD, FRAX probability, FRAX risk factors, and hip axis length (HAL).

RESULTS

During mean follow-up of 6 yr, there were 268 subjects with incident hip fractures, 1003 with incident MOF, and 787 with incident non-hip MOF. All FRIs gave significant stratification for hip fracture (c-statistics FN-FRI: 0.76, 95% CI 0.73-0.79, IT-FRI 0.74, 0.71-0.77; ST-FRI 0.72, 0.69-0.75). FRIs continued to predict hip fracture risk even after adjustment for age and sex (hazard ratio per standard deviation FN-FRI 1.89, 95% CI 1.66-2.16); age, sex, and BMD (1.26, 1.07-1.48); FRAX probability (1.30, 1.11-1.52); FRAX probability with HAL (1.26, 1.05-1.51); and individual FRAX risk factors (1.32, 1.09-1.59). FRIs also predicted MOF and non-hip MOF, but the prediction was not as strong as for hip fracture.

SUMMARY

Automatically-derived FN, IT, and ST FRIs are associated with incident hip fracture independent of multiple covariates, including FN BMD, FRAX probability and risk factors, and HAL.

3D patient-specific finite element models of the proximal femur based on DXA towards the classification of fracture and non-fracture cases

Osteoporotic bone fractures reduce quality of life and drastically increase mortality. Minimally irradiating imaging techniques such as dual-energy X-ray absorptiometry (DXA) allow assessment of bone loss through the use of bone mineral density (BMD) as descriptor. Yet, the accuracy of fracture risk predictions remains limited. Recently, DXA-based 3D modelling algorithms were proposed to analyse the geometry and BMD spatial distribution of the proximal femur. This study hypothesizes that such approaches can benefit from finite element (FE)-based biomechanical analyses to improve fracture risk prediction. One hundred and eleven subjects were included in this study and stratified in two groups: (a) 62 fracture cases, and (b) 49 non-fracture controls. Side fall was simulated using a static peak load that depended on patient mass and height. Local mechanical fields were calculated based on relationships between tissue stiffness and BMD. The area under the curve (AUC) of the receiver operating characteristic method evaluated the ability of calculated biomechanical descriptors to discriminate fracture and control cases. The results showed that the major principal stress was better discriminator (AUC > 0.80) than the volumetric BMD (AUC ≤ 0.70). High discrimination capacity was achieved when the analysis was performed by bone type, zone of fracture and gender/sex (AUC of 0.91 for women, trabecular bone and trochanter area), and outcomes suggested that the trabecular bone is critical for fracture discrimination. In conclusion, 3D FE models derived from DXA scans might significantly improve the prediction of hip fracture risk; providing a new insight for clinicians to use FE simulations in clinical practice for osteoporosis management.

Assessment of hip fracture risk by cross-sectional strain-energy derived from image-based beam model

BACKGROUND

Clinicians have been looking for a simple and effective biomechanical tool for the assessment of hip fracture risk. Dual-energy X-ray absorptiometry (DXA) is currently the primary bone imaging modality in clinic, and the engineering beam is the simplest model for a mechanical analysis. Therefore, we developed a DXA-based beam model for the above purpose.

METHODS

A beam model of the proximal femur was constructed from the subject's hip DXA image and denoted DXA-beam. Femur stiffness was calculated at cross-sections of interest using areal bone-mineral-density profile. Impact force induced in a sideways fall was applied as a critical loading. Fracture risk index at a cross-section was defined as the ratio of strain-energy induced by the impact force to the allowable strain-energy. A clinic cohort was used to study the discriminability of DXA-beam, which was measured by the area under the curve and odds ratio, both with 95% confidential interval.

FINDINGS

Fracture risk measured by DXA-beam model at the femoral neck [odds ratio 2.23, 95% confidence interval (1.83, 2.57)], inter-trochanter [2.49, (2.14, 3.25)] and sub-trochanter [2.82, (2.38, 3.51)] were strongly associated with hip fracture. The area under the curve by DXA-beam at the femoral neck [0.74, 95% confidence interval (0.70, 0.76)], inter-trochanter [0.77, (0.75, 0.82)] and sub-trochanter [0.76, (0.74, 0.81)] were higher than that by femoral neck bone mineral density [0.71, (0.65, 0.78)].

INTERPRETATION

The DXA-beam model is a simple and yet effective mechanical model. It had promising performance in discrimination of fracture cases from controls.

Lean mass and lower limb muscle function in relation to hip strength, geometry and fracture risk indices in community-dwelling older women

In a population-based sample of British women aged over 70 years old, lean mass and peak lower limb muscle force were both independently associated with hip strength and fracture risk indices, thereby suggesting a potential benefit of promoting leg muscle strengthening exercise for the prevention of hip fractures in postmenopausal women.

INTRODUCTION

To investigate cross-sectional associations of lean mass and physical performance, including lower limb muscle function, with hip strength, geometry and fracture risk indices (FRIs) in postmenopausal women.

METHODS

Data were from the Cohort of Skeletal Health in Bristol and Avon. Total hip (TH) and femoral neck (FN) bone mineral density (BMD), hip geometry and total body lean mass (TBLM) were assessed by dual x-ray absorptiometry (DXA). Finite element analysis of hip DXA was used to derive FN, intertrochanteric and subtrochanteric FRIs. Grip strength, gait speed and chair rise time were measured objectively. Lower limb peak muscle force and muscle power were assessed by jumping mechanography.

RESULTS

In total, 241 women were included (age = 76.4; SD = 2.6 years). After adjustment for age, height, weight/fat mass and comorbidities, TBLM was positively associated with hip BMD (β_{TH BMD} = 0.36, P ≤ 0.001; β_{FN BMD} = 0.26, P = 0.01) and cross-section moment of inertia (0.24, P ≤ 0.001) and inversely associated with FN FRI (- 0.21, P = 0.03) and intertrochanteric FRI (- 0.11, P = 0.05) (estimates represent SD difference in bone measures per SD difference in TBLM). Lower limb peak muscle force was positively associated with hip BMD (β_{TH BMD} = 0.28, P ≤ 0.001; β_{FN BMD} = 0.23, P = 0.008) and inversely associated with FN FRI (- 0.17, P = 0.04) and subtrochanteric FRI (- 0.18, P = 0.04). Associations of grip strength, gait speed, chair rise time and peak muscle power with hip parameters were close to the null.

CONCLUSIONS

Lean mass and lower limb peak muscle force were associated with hip BMD and geometrical FRIs in postmenopausal women. Leg muscle strengthening exercises may therefore help prevent hip fractures in older women.

Comparison of femoral strength and fracture risk index derived from DXA-based finite element analysis for stratifying hip fracture risk: A cross-sectional study

BACKGROUND

Dual-energy X-ray absorptiometry (DXA)-based finite element analysis (FEA) has been studied for assessment of hip fracture risk. Femoral strength (FS) is the maximum force that the femur can sustain before its weakest region reaches the yielding limit. Fracture risk index (FRI), which also considers subject-specific impact force, is defined as the ratio of von Mises stress induced by a sideways fall to the bone yield stress over the proximal femur. We compared risk stratification for prior hip fracture using FS and FRI derived from DXA-based FEA.

METHODS

The study cohort included women aged ≥65years undergoing baseline hip DXA, with femoral neck T-scores <-1 and no osteoporosis treatment; 324 cases had prior hip fracture and 655 controls had no prior fracture. Using anonymized DXA hip scans, we measured FS and FRI. Separate multivariable logistic regression models were used to estimate odds ratios (ORs), c-statistics and their 95% confidence intervals (95% CIs) for the association of hip fracture with FS and FRI.

RESULTS

Increased hip fracture risk was associated with lower FS (OR per SD 1.36, 95% CI: 1.15, 1.62) and higher FRI (OR per SD 1.99, 95% CI: 1.63, 2.43) after adjusting for Fracture Risk Assessment Tool (FRAX) hip fracture probability computed with bone mineral density (BMD). The c-statistic for the model containing FS (0.69; 95% CI: 0.65, 0.72) was lower than the c-statistic for the model with FRI (0.77; 95% CI: 0.74, 0.80) or femoral neck BMD (0.74; 95% CI: 0.71, 0.77; all P<0.05).

CONCLUSIONS

FS and FRI were independently associated with hip fracture, but there were differences in performance characteristics.

Association of incident hip fracture with the estimated femoral strength by finite element analysis of DXA scans in the Osteoporotic Fractures in Men (MrOS) study

Finite element model can estimate bone strength better than BMD. This study used such a model to determine its association with hip fracture risk and found that the strength estimate provided limited improvement over the hip BMDs in predicting femoral neck (FN) fracture risk only.

INTRODUCTION

Bone fractures occur only when it is loaded beyond its ultimate strength. The goal of this study was to determine the association of femoral strength, as estimated by finite element (FE) analysis of DXA scans, with incident hip fracture as a single condition or with femoral neck (FN) and trochanter (TR) fractures separately in older men.

METHODS

This prospective case-cohort study included 91 FN and 64 TR fracture cases and a random sample of 500 men (14 had a hip fracture) from the Osteoporotic Fractures in Men study during a mean ± SD follow-up of 7.7 ± 2.2 years. We analysed the baseline DXA scans of the hip using a validated plane-stress, linear-elastic FE model of the proximal femur and estimated the femoral strength during a sideways fall.

RESULTS

The estimated strength was significantly (P < 0.05) associated with hip fracture independent of the TR and total hip (TH) BMDs but not FN BMD, and combining the strength with BMD did not improve the hip fracture prediction. The strength estimate was associated with FN fractures independent of the FN, TR and TH BMDs; the age-BMI-BMD adjusted hazard ratio (95% CI) per SD decrease of the strength was 1.68 (1.07-2.64), 2.38 (1.57, 3.61) and 2.04 (1.34, 3.11), respectively. This association with FN fracture was as strong as FN BMD (Harrell's C index for the strength 0.81 vs. FN BMD 0.81) and stronger than TR and TH BMDs (0.8 vs. 0.78 and 0.81 vs. 0.79). The strength's association with TR fracture was not independent of hip BMD.

CONCLUSIONS

Although the strength estimate provided additional information over the hip BMDs, its improvement in predictive ability over the hip BMDs was confined to FN fracture only and limited.

Automated DXA-based finite element analysis for hip fracture risk stratification: a cross-sectional study

Fracture risk indices (FRIs) generated from DXA-based finite element analysis were associated with hip fracture independent of FRAX score computed with femoral neck bone mineral density (BMD). Prospective studies are warranted to determine whether FRIs represent an improvement over BMD for predicting incident hip fractures.

INTRODUCTION

The study aims to examine the association between prior hip fracture and FRIs derived from automated finite element analysis (FEA) of DXA hip scans. Femoral neck, intertrochanteric, and subtrochanteric FRIs were calculated as the von Mises stress induced by a sideways fall divided by the bone yield stress over the specified region of interest (ROI).

METHODS

Using the Manitoba Bone Mineral Density Database, we selected women age ≥ 65 years with femoral neck T-scores below - 1 and no osteoporosis treatment. From this population, we identified 324 older women with hip fracture before DXA testing and a random sample of 658 non-fracture controls. FRIs were derived from the anonymized DXA scans. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the associations between FRIs (per SD increase) and hip fracture.

RESULTS

After adjusting for FRAX score (hip fracture with BMD), femoral neck FRI (OR 1.36, 95% CI 1.13, 1.64), intertrochanteric FRI (OR 1.81, 95% CI 1.44, 2.27), and subtrochanteric FRI (OR 2.09, 95% CI 1.68, 2.60) were associated with hip fracture. Intertrochanteric and subtrochanteric FRIs gave significantly higher c-statistics (all P ≤ 0.05) than femoral neck BMD. Subgroup analyses showed that all FRIs were more strongly associated with hip fracture in women who were younger and had higher body mass index (BMI) or non-osteoporotic BMD (all P _interaction < 0.1).

CONCLUSIONS

FRIs derived from DXA-based FEA were independently associated with prior hip fracture, suggesting that they could potentially improve hip fracture risk assessment.

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

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

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Osteoporotic fracture has been found associated with many clinical risk factors, and the associations have been explored dominantly by evidence-based and case-control approaches. The major challenges emerging from the studies are the large number of the risk factors, the difficulty in quantification, the incomplete list, and the interdependence of the risk factors. A biomechanical sorting of the risk factors may shed lights on resolving the above issues. Based on the definition of load-strength ratio (LSR), we first identified the four biomechanical variables determining fracture risk, i.e., the risk of fall, impact force, bone quality, and bone geometry. Then, we explored the links between the FRAX clinical risk factors and the biomechanical variables by looking for evidences in the literature. To accurately assess fracture risk, none of the four biomechanical variables can be ignored and their values must be subject-specific. A clinical risk factor contributes to osteoporotic fracture by affecting one or more of the biomechanical variables. A biomechanical variable represents the integral effect from all the clinical risk factors linked to the variable. The clinical risk factors in FRAX mostly stand for bone quality. The other three biomechanical variables are not adequately represented by the clinical risk factors. From the biomechanical viewpoint, most clinical risk factors are interdependent to each other as they affect the same biomechanical variable(s). As biomechanical variables must be expressed in numbers before their use in calculating LSR, the numerical value of a biomechanical variable can be used as a gauge of the linked clinical risk factors to measure their integral effect on fracture risk, which may be more efficient than to study each individual risk factor.

Assessment of Hip Fracture Risk Using Cross-Section Strain Energy Determined by QCT-Based Finite Element Modeling

Accurate assessment of hip fracture risk is very important to prevent hip fracture and to monitor the effect of a treatment. A subject-specific QCT-based finite element model was constructed to assess hip fracture risk at the critical locations of femur during the single-leg stance and the sideways fall. The aim of this study was to improve the prediction of hip fracture risk by introducing a novel failure criterion to more accurately describe bone failure mechanism. Hip fracture risk index was defined using cross-section strain energy, which is able to integrate information of stresses, strains, and material properties affecting bone failure. It was found that the femoral neck and the intertrochanteric region have higher fracture risk than other parts of the femur, probably owing to the larger content of cancellous bone in these regions. The study results also suggested that women are more prone to hip fracture than men. The findings in this study have a good agreement with those clinical observations reported in the literature. The proposed hip fracture risk index based on strain energy has the potential of more accurate assessment of hip fracture risk. However, experimental validation should be conducted before its clinical applications.

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

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

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

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

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A more effective risk predictor constructed from finite element studies.

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

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

Use of DXA-based finite element analysis of the proximal femur in a longitudinal study of hip fracture

Bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is used for clinical assessment of fracture risk; however, measurements that incorporate bone strength could improve predictive ability. The aim of this study was to determine whether bone strength derived from finite element (FE) analysis was associated with hip fracture risk in a longitudinal study. We studied 728 women (mean age 82 years), 182 with subsequent hip fracture. FE models were generated from baseline DXA scans of the hip to determine femoral bone strength and load-to-strength ratio (LSR). The baseline LSR was significantly higher in fracture cases (median 1.1) compared with controls (0.7, p < 0.0001). Femoral strength and BMD were also significantly lower in cases (median 1820 N, 0.557 g/cm(2)) compared with controls (2614 N, 0.618 g/cm(2) ) both p < 0.0001. Fracture risk increased per standard deviation decrease in femoral strength (odds ratio [OR] = 2.2, 95% confidence interval [CI] 1.8-2.8); femoral neck (FN) BMD (OR = 2.1, 95% CI 1.7-2.6); total hip BMD (OR = 1.8, 95% CI 1.5-2.1); and per SD increase in LSR (OR = 1.8, 95% CI 1.5-2.1). After adjusting for FN BMD, the odds ratio for femoral strength (OR = 1.7, 95% CI 1.2-2.4) and LSR (OR = 1.4, 95% CI 1.1-1.7) remained significantly greater than 1. The area under the curve (AUC) for LSR combined with FN BMD (AUC 0.69, 95% CI 0.64-0.73) was significantly greater than FN BMD alone (AUC 0.66, 95% CI 0.62-0.71, p = 0.004). Strength and LSR remained significant when adjusted for prevalent fragility fracture, VFA, and FRAX score. In conclusion, the DXA-based FE model was able to discriminate incident hip fracture cases from controls in this longitudinal study independently from FN BMD, prior fracture, VFA, and FRAX score. Such an approach may provide a useful tool for better assessment of bone strength to identify patients at high risk of hip fracture who may benefit from treatment to reduce fracture risk.

Precision study of DXA-based patient-specific finite element modeling for assessing hip fracture risk

Finite element (FE) modeling based on a patient's hip dual energy X-ray absorptiometry (DXA) image is a promising tool for more accurately assessing hip fracture risk, as it is able to comprehensively consider effects from all the mechanical parameters affecting hip fracture. However, a number of factors influence the precision (also known as repeatability or reproducibility) of a DXA-based FE procedure, for example, subject positioning in DXA scanning. As a procedure is required to have adequately high precision in clinical application, we investigated the effects of the involved factors on the precision of a DXA-based patient-specific FE procedure developed by the authors, to provide insight into how the precision of the procedure can be improved so that it can meet the clinical standards. Fracture risk indices corresponding to initial and repeat DXA scans acquired in 30 typical clinical subjects were computed and compared to assess short term repeatability of the procedure. It was found that inconsistent positioning followed by manual segmentation of the projected femur contour induced significant variability in the predicted fracture risk indices. This research suggests that, to apply the DXA-based FE procedure in clinical assessment, it will be necessary to pay more strict attention to subject positioning in DXA scanning.

Investigation of repeatability in hip fracture risk predicted by DXA-based finite element model

DXA (dual energy X-ray absorptiometry) based finite element model is able to integrate all mechanical factors affecting hip fracture in osteoporosis patients and it is thus, in principle, more reliable than areal bone mineral density (BMD) for assessing fracture risk. However, short-term repeatability of DXA-based finite element model in predicting fracture risk has not yet been investigated and satisfactory repeatability is a prerequisite for the procedure to be applied in clinic. Therefore, in the reported research, the repeatability of a previously developed DXA-based patient-specific finite element procedure was investigated. It was found that inconsistence in positioning the patient during DXA scanning and manual segmentation of DXA image in constructing the finite element model are the two dominant factors affecting short-term repeatability of the finite element procedure. The study outcome indicated that to apply the finite element procedure in clinic, a set of more strict guidelines for positioning the patient in DXA scanning must be established and followed.