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

Magnetic resonance imaging based finite element modelling of the proximal femur: a short-term in vivo precision study

Proximal femoral fractures are a serious life-threatening injury with high morbidity and mortality. Magnetic resonance (MR) imaging has potential to non-invasively assess proximal femoral bone strength in vivo through usage of finite element (FE) modelling (a technique referred to as MR-FE). To precisely assess bone strength, knowledge of measurement error associated with different MR-FE outcomes is needed. The objective of this study was to characterize the short-term in vivo precision errors of MR-FE outcomes (e.g., stress, strain, failure loads) of the proximal femur for fall and stance loading configurations using 13 participants (5 males and 8 females; median age: 27 years, range: 21-68), each scanned 3 times. MR-FE models were generated, and mean von Mises stress and strain as well as principal stress and strain were calculated for 3 regions of interest. Similarly, we calculated the failure loads to cause 5% of contiguous elements to fail according to the von Mises yield, Brittle Coulomb-Mohr, normal principal, and Hoffman stress and strain criteria. Precision (root-mean squared coefficient of variation) of the MR-FE outcomes ranged from 3.3% to 11.8% for stress and strain-based mechanical outcomes, and 5.8% to 9.0% for failure loads. These results provide evidence that MR-FE outcomes are a promising non-invasive technique for monitoring femoral strength in vivo.

Patient-specific finite element analysis for assessing hip fracture risk in aging populations

The femur is one of the most important bone in the human body, as it supports the body's weight and helps with movement. The aging global population presents a significant challenge, leading to an increasing demand for artificial joints, particularly in knee and hip replacements, which are among the most prevalent surgical procedures worldwide. This study focuses on hip fractures, a common consequence of osteoporotic fractures in the elderly population. To accurately predict individual bone properties and assess fracture risk, patient-specific finite element models (FEM) were developed using CT data from healthy male individuals. The study employed ANSYS 2023 R2 software to estimate fracture loads under simulated single stance loading conditions, considering strain-based failure criteria. The FEM bone models underwent meticulous reconstruction, incorporating geometrical and mechanical properties crucial for fracture risk assessment. Results revealed an underestimation of the ultimate bearing capacity of bones, indicating potential fractures even during routine activities. The study explored variations in bone density, failure loads, and density/load ratios among different specimens, emphasizing the complexity of bone strength determination. Discussion of findings highlighted discrepancies between simulation results and previous studies, suggesting the need for optimization in modelling approaches. The strain-based yield criterion proved accurate in predicting fracture initiation but required adjustments for better load predictions. The study underscores the importance of refining density-elasticity relationships, investigating boundary conditions, and optimizing models throughin vitrotesting for enhanced clinical applicability in assessing hip fracture risk. In conclusion, this research contributes valuable insights into developing patient-specific FEM bone models for clinical hip fracture risk assessment, emphasizing the need for further refinement and optimization for accurate predictions and enhanced clinical utility.

QCT-based 3D finite element modeling to assess patient-specific hip fracture risk and risk factors

Early assessment of hip fracture risk may play a critical role in designing preventive mechanisms to reduce the occurrence of hip fracture in geriatric people. The loading direction, clinical, and morphological variables play a vital role in hip fracture. Analyzing the effects of these variables helps predict fractures risk more accurately; thereby suggesting the critical variable that needs to be considered. Hence, this work considered the fall postures by varying the loading direction on the coronal plane (α) and on the transverse plane (β) along with the clinical variables-age, sex, weight, and bone mineral density, and morphological variables-femoral neck axis length, femoral neck width, femoral neck angle, and true moment arm. The strain distribution obtained via finite element analysis (FEA) shows that the angle of adduction (α) during a fall increases the risk of fracture at the greater trochanter and femoral neck, whereas with an increased angle of rotation (β) during the fall, the FRI increases by ∼1.35 folds. The statistical analysis of clinical, morphological, and loading variables (αandβ) delineates that the consideration of only one variable is not enough to realistically predict the possibility of fracture as the correlation between individual variables and FRI is less than 0.1, even though they are shown to be significant (p<0.01). On the contrary, the correlation (R2=0.48) increases as all variables are considered, suggesting the need for considering different variables fork predicting FRI. However, the effect of each variable is different. While loading, clinical, and morphological variables are considered together, the loading direction on transverse plane (β) has high significance, and the anatomical variabilities have no significance.

Varus malalignment of the lower limb increases the risk of femoral neck fracture: A biomechanical study using a finite element method

INTRODUCTION

The understanding of the stresses and strains and their dependence on loading direction caused by an axial deformity is very important for understanding the mechanism of femural neck fractures. The hypothesis of this study is that lower limb malalignment is correlated with a substantial stress variation on the upper end of the femur. The purpose of this biomechanical trial using the finite element method is to determine the effect of the loading direction on the proximal femur regarding the malalignment of the lower limb, and also enlighten the relation between the lower limb alignment and the risk of a femoral neck fracture.

METHODS

Ten segmentations of CT scans were considered. An axial compression load was applied to the femoral head to digitally simulate the physiological configuration in neutral position as well as in different axial positions in varus/valgus alignment.

RESULTS

The stress at the proximal femur changes as the varus _valgus angle does. It can be observed the smaller absolute stress at angle 10° (valgus) and the higher absolute stress at angle -10° (varus). The mean maximum von Mises stress value was 14.1 (SD=±3.48) MPa for 0°, while the mean maximum von Mises stress value was 17.96 MPa (SD=4.87) for -10° in varus. The fracture risk indicator of the proximal femoral epiphyses changes inversely with angle direction. The FRI was the highest at -10° and the lowest at 10°.

CONCLUSION

Based on the biomechanical findings and the fracture risk indicator determined in this preliminary study, varus malalignment increases the risk of femoral neck fracture. Consideration of other parameters such as bone mineral density and morphological parameters should also help to plan preventive medical strategy in the elderly.

Biomechanical analysis of the correlation between mid-shaft atypical femoral fracture (AFF) and axial varus deformation

Background

Atypical femoral fractures (AFF) are diaphyseal fractures of the elderly that occur at the end of a minor trauma. The objective of this biomechanical study, using finite element modelling, was to evaluate the variations of the femoral diaphysis fracture indicator according to the variations of the mechanical axis of the lower limb, which can explain all the different atypical fracture types identified in the literature.

Methods

In order to measure variations in stress and risk factors for fracture of the femoral diaphysis, the distal end of the femur was constrained in all degrees of freedom. An axial compression load was applied to the femoral head to digitally simulate the bipodal support configuration in neutral position as well as in different axial positions in varus/valgus (− 10°/10°).

Results

The maximum stress value of Von Mises was twice as high (17.96 ± 4.87 MPa) at a varus angle of − 10^° as in the neutral position. The fracture risk indicator of the femoral diaphysis varies proportionally with the absolute value of the steering angle. However, the largest simulated varus deformation (− 10°) found a higher risk of diaphysis fracture indicator than in valgus (10°).

Conclusions

Variations in the mechanical axis of the lower limb influence the stress distribution at the femur diaphysis and consequently increase the risk of AFF. The axial deformation in varus is particularly at risk of AFF. The combination of axial deformation stresses and bone fragility consequently contribute to the creation of an environment favorable to the development of AFF.

Trial registration: ‘retrospectively registered’.

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.

Finite Element Prediction on Fracture Load of Femur with Osteogenesis Imperfecta under Various Loading Conditions

Osteogenesis Imperfecta (OI) is an inherited disorder characterized by extreme bone fragility due to collagen defects. It is an incurable disease. Bone fractures can occur frequently without prior notice, especially among children. Early quantitative prediction of fracture loads due to OI tends to alert patients to avoid unnecessary situations or dangerous conditions. This study is aimed at investigating the fracture loads of femur with OI under various types of loading. Ten finite element models of an OI-affected bone were reconstructed from the normal femur with different bowing angles ranging from 7.5 to 30.0°. The boundary conditions were assigned on an OI-affected femoral head under three types of load: medial-lateral impacts, compression-tension, and internal-external torsions, and various loading direction cases that reflect the stance condition. The fracture load was examined based on the load that can cause bone fracture for each case. The results show that the loads bearable by the femur before fracture were decreased with respect to the increase of OI bowing angles in most of the loading cases. The risk of fracture for the femur with OI was directly proportional to the increase of bowing angles in the frontal plane. This study provides new insights on fracture load prediction in OI-affected bone with respect to various loading types, which could help medical personnel for surgical intervention judgement.

Approaches to Fracture Risk Assessment and Prevention

PURPOSE OF REVIEW

To critically assess recent evidence concerning osteoporosis fracture risk.

RECENT FINDINGS

Robust instruments exist for predicting factures incorporating well-documented risk factors especially prior fracture whose magnitude varies with site, occurrence time, and age. Stratifying time-since-prior fracture has resulted in the concept of imminent fracture risk and increased focus on secondary fracture prevention. Secondary fracture prevention recommendations include fracture liaison service, pharmacologic and non-pharmacologic multidisciplinary intervention, and communicating that fractures in older adults are the predictable consequence of underlying osteoporosis rather than unfortunate accidents. Quality improvement in osteoporosis care includes diagnosing osteoporosis on the basis of clinical fractures rather than exclusively relying on bone density testing; applying diagnostic rather than screening approaches to patients with prior fractures; regularly updating fall and fracture histories; performing a physical exam focused on spinal curvature, posture, and musculoskeletal function; reviewing images to identify prevalent fractures that may have been missed; and general use of fracture risk algorithms at all stages of osteoporosis management. Communicating effectively with patients about osteoporosis and fractures, their consequences, and pharmacological and non-pharmacological management is the cornerstone of high-value care.

Methods for Post Hoc Quantitative Computed Tomography Bone Density Calibration: Phantom-Only and Regression

Quantitative computed tomography (qCT) relies on calibrated bone mineral density data. If a calibration phantom is absent from the CT scan, post hoc calibration becomes necessary. Scanning a calibration phantom after-the-fact and applying that calibration to uncalibrated scans has been used previously. Alternatively, the estimated density is known to vary with CT settings, suggesting that it may be possible to predict the calibration terms using CT settings. This study compares a novel CT setting regression method for post hoc calibration to standard and post hoc phantom-only calibrations. Five cadaveric upper limbs were scanned at 11 combinations of peak tube voltage and current (80-140 kV and 100-300 mA) with two calibration phantoms. Density calibrations were performed for the cadaver scans, and scans of the phantoms alone. Stepwise linear regression determined if the calibration equation terms were predictable using peak tube voltage and current. Peak tube voltage, but not current, was significantly correlated with regression calibration terms. Calibration equation slope was significantly related to the type of phantom (p < 0.001), calibration method (p = 0.026), and peak tube voltage (p < 0.001), but not current (p = 1.000). The calibration equation vertical intercept was significantly related to the type of phantom (p < 0.001), and peak tube voltage (p = 0.006), but not calibration method (p = 0.682), or current (p = 0.822). Accordingly, regression can correlate peak tube voltage with density calibration terms. Suggesting that, while standard qCT calibration is preferable, regression calibration may be an acceptable post hoc method when necessary.

The Influence of Geometry of Implants for Direct Skeletal Attachment of Limb Prosthesis on Rehabilitation Program and Stress-Shielding Intensity

The purpose of the research was to evaluate the influence of selected parameters of the implants for bone anchored prostheses on possibility of conducting static load bearing exercises and stress-shielding intensity. A press-fit implant, a threaded implant, and the proposed design were compared using the finite element method. For the analyses two features were examined: diameter (19.0 – 21.0 mm) and length (75.0 – 130.0 mm). To define the possibility of conducting rehabilitation exercises the micromotion of implants while axial loading with a force up to 1000 N was examined to evaluate the changes at implant-bone interface. The stress-shielding intensity was estimated by bone mass loss over 60 months. The results suggest that, in terms of micromotion generated during rehabilitation exercises, the threaded (max. micromotion of 16.00 μm) and the proposed (max. micromotion of 45.43 μm) implants ensure low and appropriate micromotion. In the case of the press-fit solution the load values should be selected with care, as there is a risk of losing primary stabilisation. The allowed forces (that do not stimulate the organism to generate fibrous tissue) were approx. 140 N in the case of the length of 75 mm, increasing up to 560 N, while using the length of 130 mm. Moreover, obtained stress-shielding intensities suggest that the proposed implant should provide appropriate secondary stability, similar to the threaded solution, due to the low bone mass loss during long-term use (improving at the same time more bone remodelling in distal Gruen zones, by providing lower bone mass loss by approx. 13% to 20% in dependency of the length and diameter used). On this basis it can be concluded that the proposed design can be an appropriate alternative to commercially used implants.

The Effect of Inhomogeneous Trabecular Stiffness Relationship Selection on Finite Element Outcomes for Shoulder Arthroplasty

An important feature of humeral orthopedic finite element (FE) models is the trabecular stiffness relationship. These relationships depend on the anatomic site from which they are derived; but have not been developed for the humerus. As a consequence, humeral FE modeling relies on relationships for other anatomic sites. The variation in humeral FE outcomes due to the trabecular stiffness relationship is assessed. Stemless arthroplasty FE models were constructed from CT scans of eight humeri. Models were loaded corresponding to 45 deg and 75 deg abduction. Each bone was modeled five times with the only variable being the trabecular stiffness relationship: four derived from different anatomic-sites and one pooled across sites. The FE outcome measures assessed were implant-bone contact percentage, von Mises of the change in stress, and bone response potential. The variance attributed to the selection of the trabecular stiffness relationship was quantified as the standard deviation existing between models of different trabecular stiffness. Overall, variability due to changing the trabecular stiffness relationship was low for all humeral FE outcome measures assessed. The variability was highest within the stress and bone formation potential outcome measures of the trabecular region. Variability only exceeded 10% in the trabecular stress change within two of the eight slices evaluated. In conclusion, the low variations attributable to the selection of a trabecular stiffness relationship based on anatomic-site suggest that FE models constructed for shoulder arthroplasty can utilize an inhomogeneous site-pooled trabecular relationship without inducing marked variability in the assessed outcome measures.

Automation of a DXA-based finite element tool for clinical assessment of hip fracture risk

Finite element analysis of medical images is a promising tool for assessing hip fracture risk. Although a number of finite element models have been developed for this purpose, none of them have been routinely used in clinic. The main reason is that the computer programs that implement the finite element models have not been completely automated, and heavy training is required before clinicians can effectively use them. By using information embedded in clinical dual energy X-ray absorptiometry (DXA), we completely automated a DXA-based finite element (FE) model that we previously developed for predicting hip fracture risk. The automated FE tool can be run as a standalone computer program with the subject's raw hip DXA image as input. The automated FE tool had greatly improved short-term precision compared with the semi-automated version. To validate the automated FE tool, a clinical cohort consisting of 100 prior hip fracture cases and 300 matched controls was obtained from a local community clinical center. Both the automated FE tool and femoral bone mineral density (BMD) were applied to discriminate the fracture cases from the controls. Femoral BMD is the gold standard reference recommended by the World Health Organization for screening osteoporosis and for assessing hip fracture risk. The accuracy was measured by the area under ROC curve (AUC) and odds ratio (OR). Compared with femoral BMD (AUC = 0.71, OR = 2.07), the automated FE tool had a considerably improved accuracy (AUC = 0.78, OR = 2.61 at the trochanter). This work made a large step toward applying our DXA-based FE model as a routine clinical tool for the assessment of hip fracture risk. Furthermore, the automated computer program can be embedded into a web-site as an internet application.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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