Accuracy of finite element predictions in sideways load configurations for the proximal human femur

Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China

The water quality index (WQI) is a widely used tool for comprehensive assessment of river environments. However, its calculation involves numerous water quality parameters, making sample collection and laboratory analysis time-consuming and costly. This study aimed to identify key water parameters and the most reliable prediction models that could provide maximum accuracy using minimal indicators. Water quality from 2020 to 2023 were collected including nine biophysical and chemical indicators in seventeen rivers in Yancheng and Nantong, two coastal cities in Jiangsu Province, China, adjacent to the Yellow Sea. Linear regression and seven machine learning models (Artificial Neural Network (ANN), Self-Organizing Maps (SOM), K-Nearest Neighbor (KNN), Support Vector Machines (SVM), Random Forest (RF), Extreme Gradient Boosting (XGB) and Stochastic Gradient Boosting (SGB)) were developed to predict WQI using different groups of input variables based on correlation analysis. The results indicated that water quality improved from 2020 to 2022 but deteriorated in 2023, with inland stations exhibiting better conditions than coastal ones, particularly in terms of turbidity and nutrients. The water environment was comparatively better in Nantong than in Yancheng, with mean WQI values of approximately 55.3-72.0 and 56.4-67.3, respectively. The classifications "Good" and "Medium" accounted for 80 % of the records, with no instances of "Excellent" and 2 % classified as "Bad". The performance of all prediction models, except for SOM, improved with the addition of input variables, achieving R2 values higher than 0.99 in models such as SVM, RF, XGB, and SGB. The most reliable models were RF and XGB with key parameters of total phosphorus (TP), ammonia nitrogen (AN), and dissolved oxygen (DO) (R2 = 0.98 and 0.91 for training and testing phase) for predicting WQI values, and RF using TP and AN (accuracy higher than 85 %) for WQI grades. The prediction accuracy for "Medium" and "Low" water quality grades was highest at 90 %, followed by the "Good" level at 70 %. The model results could contribute to efficient water quality evaluation by identifying key water parameters and facilitating effective water quality management in river basins.

Model Properties and Clinical Application in the Finite Element Analysis of Knee Joint: A Review

The knee is the most complex joint in the human body, including bony structures like the femur, tibia, fibula, and patella, and soft tissues like menisci, ligaments, muscles, and tendons. Complex anatomical structures of the knee joint make it difficult to conduct precise biomechanical research and explore the mechanism of movement and injury. The finite element model (FEM), as an important engineering analysis technique, has been widely used in many fields of bioengineering research. The FEM has advantages in the biomechanical analysis of objects with complex structures. Researchers can use this technology to construct a human knee joint model and perform biomechanical analysis on it. At the same time, finite element analysis can effectively evaluate variables such as stress, strain, displacement, and rotation, helping to predict injury mechanisms and optimize surgical techniques, which make up for the shortcomings of traditional biomechanics experimental research. However, few papers introduce what material properties should be selected for each anatomic structure of knee FEM to meet different research purposes. Based on previous finite element studies of the knee joint, this paper summarizes various modeling strategies and applications, serving as a reference for constructing knee joint models and research design.

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.

Reproducibility in modeling and simulation of the knee: Academic, industry, and regulatory perspectives

Stakeholders in the modeling and simulation (M&S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled "Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives." The goal was to discuss efforts among these stakeholders to address irreproducibility in M&S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&S.

Credibility assessment of computational models according to ASME V&V40: Application to the Bologna Biomechanical Computed Tomography solution

BACKGROUND AND OBJECTIVE

When a computational model aims to be adopted beyond research purposes, e.g. to inform a clinical or regulatory decision, trust must be placed in its predictive accuracy. This practically translates into the need to demonstrate its credibility. In fact, prior to its adoption for regulatory purposes, an in silico methodology should be proven credible enough for the scope. This has become especially relevant as, although evidence of the safety and efficacy of new medical products or interventions has been traditionally provided to the regulator experimentally, i.e., in vivo or ex vivo, recently the idea to inform a regulatory decision in silico has made its way in the regulatory scenario. While a harmonised technical standard is currently missing in the EU regulatory system, in 2018 the ASME issued V&V40-2018, where a risk-based framework to assess the credibility of a computational model through the performance of predefined credibility activities is provided. The credibility framework is here applied to Bologna Biomechanical Computed Tomography (BBCT) solution, which predicts the absolute risk of fracture at the femur for a subject. BBCT has recently been the object of a qualification advice request to the European Medicine Agency.

METHODS

The full implementation of ASME V&V40-2018 framework on BBCT is shown. Starting from BBCT proposed context of use the whole credibility plan is presented and the credibility activities (Verification, Validation, Applicability) described together with the achieved credibility levels.

RESULTS

BBCT risk is judged medium, and the credibility levels achieved considered acceptable. The uncertainties intrinsically present in the material properties assignment affected BBCT predictions to the highest extent.

CONCLUSIONS

This work provides the practical application of the ASME V&V40-2018 risk-based credibility assessment framework, which could be applied to demonstrate model credibility in any field and support future regulatory submissions and foster the adoption of In Silico Trials.

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

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

A new finite element with variable Young's modulus

The Finite Element Method (FEM) is a numerical technique that is well-established in the field of engineering. However, in biological sciences, it is just taking its first steps. Bone tissue is an example of biological material which is exposed to high loads in its natural environment. Practically every movement of the body results in changing stress levels in the bone. Nature copes with this very well but when human intervention is necessary (e.g., endoprostheses implants) bone strength has to be determined based on experience since bone tissue has a very heterogeneous structure. The goal of this paper is to demonstrate how standard FEM calculations may be readily modified to provide for variable material properties of such materials as, for example, bone or wood.

Geometry and bone mineral density determinants of femoral neck strength changes following exercise

Physical exercise induces spatially heterogeneous adaptation in bone. However, it remains unclear where the changes in BMD and geometry have the greatest impact on femoral neck strength. The aim of this study was to determine the principal BMD-and-geometry changes induced by exercise that have the greatest effect on femoral neck strength. Pre- and post-exercise 3D-DXA images of the proximal femur were collected of male participants from the LIFTMOR-M exercise intervention trial. Meshes with element-by-element correspondence were generated by morphing a template mesh to each bone to calculate changes in BMD and geometry. Finite element (FE) models predicted femoral neck strength changes under single-leg stance and sideways fall load. Partial least squares regression (PLSR) models were developed with BMD-only, geometry-only, and BMD-and-geometry changes to determine the principal modes that explained the greatest variation in neck strength changes. The PLSR models explained over 90% of the strength variation with 3 PLS components using BMD-only (R² > 0.92, RMSE < 0.06 N) and 8 PLS components with geometry-only (R² > 0.93, RMSE < 0.06 N). Changes in the superior neck and distal cortex were most important during single-leg stance while the superior neck, medial head, and lateral trochanter were most important during a sideways fall. Local changes in femoral neck and head geometry could differentiate the exercise groups from the control group. Exercise interventions may target BMD changes in the superior neck, inferior neck, and greater trochanter for improved femoral neck strength in single-leg stance and sideways fall.

Effect of fall direction on the lower hip fracture risk in athletes with different loading histories: A finite element modeling study in multiple sideways fall configurations

Physical loading makes bones stronger through structural adaptation. Finding effective modes of exercise to improve proximal femur strength has the potential to decrease hip fracture risk. Previous proximal femur finite element (FE) modeling studies have indicated that the loading history comprising impact exercises is associated with substantially higher fracture load. However, those results were limited only to one specified fall direction. It remains thus unclear whether exercise-induced higher fracture load depends on the fall direction. To address this, using magnetic resonance images of proximal femora from 91 female athletes (mean age 24.7 years with >8 years competitive career) and their 20 non-athletic but physically active controls (mean age 23.7 years), proximal femur FE models were created in 12 different sideways fall configurations. The athletes were divided into five groups by typical loading patterns of their sports: high-impact (H-I: 9 triple- and 10 high-jumpers), odd-impact (O-I: 9 soccer and 10 squash players), high-magnitude (H-M: 17 powerlifters), repetitive-impact (R-I: 18 endurance runners), and repetitive non-impact (R-NI: 18 swimmers). Compared to the controls, the FE models showed that the H-I and R-I groups had significantly (p < 0.05) higher fracture loads, 11-17% and 22-28% respectively, in all fall directions while the O-I group had significantly 10-11% higher fracture loads in four fall directions. The H-M and R-NI groups did not show significant benefit in any direction. Also, the analyses of the minimum fall strength (MFS) among these multiple fall configurations confirmed significantly 15%, 11%, and 14% higher MFSs in these impact groups, respectively, compared to the controls. These results suggest that the lower hip fracture risk indicated by higher fracture loads in athletes engaged in high impact or repetitive impact sports is independent of fall direction whereas the lower fracture risk attributed to odd-impact exercise is more modest and specific to the fall direction. Moreover, in concordance with the literature, the present study also confirmed that the fracture risk increases if the impact is imposed on the more posterolateral aspect of the hip. The present results highlight the importance of engaging in the impact exercises to prevent hip fractures and call for retrospective studies to investigate whether specific impact exercise history in adolescence and young adulthood is also associated with lower incidence of hip fractures in later life.

Can neck fractures in proximal humeri be predicted by CT-based FEA?

BACKGROUND

Proximal humeri fractures at anatomical and surgical neck (∼5% and ∼50% incidence respectively) are frequent in elderly population. Yet, neither in-vitro experiments nor CT-based finite element analyses (CTFEA) have investigated these in depth. Herein we enhance (Dahan et al., 2019) (addressing anatomical neck fractures) by more experiments and specimens, accounting for surgical neck fractures and explore CTFEA's prediction of humeri mechanical response and yield force.

METHODS

Four fresh frozen human humeri were tested in a new experimental configuration inducing surgical neck fractures. Digital image correlation (DIC) provided strains and displacements on humeri surfaces and used to validate CTFEA predictions. CTFEA were enhanced herein to improve the accuracy at the proximal neck: A cortical bone mapping (CBM) algorithm was implemented to overcome insufficient scanning resolution, and a new trabecular material mapping was investigated.

RESULTS

The new experimental setting induced impacted surgical neck fractures in all humeri. Excellent DIC to CTFEA correlation in strains was obtained at the shaft (slope 0.984, R²=0.99) and a fair agreement (slope 0.807, R²=0.73) at the neck. CBM algorithm had worsened the correlation, whereas the new material mapping had a negligible influence. Yield loads predictions improved considerably when trabecular yielding (maximum principal strain criterion) was considered instead of surface cortical yielding.

DISCUSSION

CTFEA well predicts strains on the shaft and reasonably well on the neck. This enhances former conclusions by past studies conducted using SGs, now also evident by DIC. Yield load prediction for surgical neck fractures (involving crushing of trabecular bone) is predicted better by trabecular failure laws rather than cortex ones. Further FEA studies using trabecular orthotropic constitutive models and failure laws are warrant.

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.

Which experimental procedures influence the apparent proximal femoral stiffness? A parametric study

Background

Experimental validation is the gold standard for the development of FE predictive models of bone. Employing multiple loading directions could improve this process. To capture the correct directional response of a sample, the effect of all influential parameters should be systematically considered. This study aims to determine the impact of common experimental parameters on the proximal femur’s apparent stiffness.

Methods

To that end, a parametric approach was taken to study the effects of: repetition, pre-loading, re-adjustment, re-fixation, storage, and μCT scanning as random sources of uncertainties, and loading direction as the controlled source of variation in both stand and side-fall configurations. Ten fresh-frozen proximal femoral specimens were prepared and tested with a novel setup in three consecutive sets of experiments. The neutral state and 15-degree abduction and adduction angles in both stance and fall configurations were tested for all samples and parameters. The apparent stiffness of the samples was measured using load-displacement data from the testing machine and validated against marker displacement data tracked by DIC cameras.

Results

Among the sources of uncertainties, only the storage cycle affected the proximal femoral apparent stiffness significantly. The random effects of setup manipulation and intermittent μCT scanning were negligible. The 15^∘ deviation in loading direction had a significant effect comparable in size to that of switching the loading configuration from neutral stance to neutral side-fall.

Conclusion

According to these results, comparisons between the stiffness of the samples under various loading scenarios can be made if there are no storage intervals between the different load cases on the same samples. These outcomes could be used as guidance in defining a highly repeatable and multi-directional experimental validation study protocol.

Modified pedicle screw-rod versus anterior subcutaneous internal pelvic fixation for unstable anterior pelvic ring fracture: a retrospective study and finite element analysis

Objectives

This study compared the stability and clinical outcomes of modified pedicle screw-rod fixation (MPSRF) and anterior subcutaneous internal pelvic fixation (INFIX) for the treatment of anterior pelvic ring fractures using the Tornetta and Matta grading system and finite element analyses (FEA).

Methods

In a retrospective review of a consecutive patient series, 63 patients with Orthopaedic Trauma Association (OTA)/Arbeitsgemeinschaft für Osteosynthesefragen (AO) type B or C pelvic ring fractures were treated by MPRSF (n = 30) or INFIX (n = 33). The main outcome measures were the Majeed score, incidence of complications, and adverse outcomes, and fixation stability as evaluated by finite element analysis.

Results

Sixty-three patients were included in the study, with an average age of 34.4 and 36.2 in modified group and conventional group, respectively. Two groups did not differ in terms of the injury severity score, OTA classification, cause of injury, and time to pelvic surgery. However, the MPSRF group had a rate of higher satisfactory results according to the Tornetta and Matta grading system than the conventional group (73.33% vs 63.63%) as well as a higher Majeed score (81.5 ± 10.4 vs 76.3 ± 11.2), and these differences were statistically significant at 6 months post-surgery. FEA showed that MPSRF was stiffer and more stable than INFIX and had a lower risk of implant failure.

Conclusions

Both MPSRF and INFIX provide acceptable biomechanical stability for the treatment of unstable anterior pelvic ring fractures. However, MPSRF provides better fixation stability and a lower risk of implant failure, and can thus lead to better clinical outcomes. Therefore, MPSRF should be more widely applied to anterior pelvic ring fractures

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02618-9.

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

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

MRI-derived porosity index is associated with whole-bone stiffness and mineral density in human cadaveric femora

Ultrashort echo time (UTE) magnetic resonance imaging (MRI) measures proton signals in cortical bone from two distinct water pools, bound water, or water that is tightly bound to bone matrix, and pore water, or water that is freely moving in the pore spaces in bone. By isolating the signal contribution from the pore water pool, UTE biomarkers can directly quantify cortical bone porosity in vivo. The Porosity Index (PI) is one non-invasive, clinically viable UTE-derived technique that has shown strong associations in the tibia with μCT porosity and other UTE measures of bone water. However, the efficacy of the PI biomarker has never been examined in the proximal femur, which is the site of the most catastrophic osteoporotic fractures. Additionally, the loads experienced during a sideways fall are complex and the femoral neck is difficult to image with UTE, so the usefulness of the PI in the femur was unknown. Therefore, the aim of this study was to examine the relationships between the PI measure in the proximal cortical shaft of human cadaveric femora specimens compared to (1) QCT-derived bone mineral density (BMD) and (2) whole bone stiffness obtained from mechanical testing mimicking a sideways fall. Fifteen fresh, frozen whole cadaveric femora specimens (age 72.1 ± 15.0 years old, 10 male, 5 female) were scanned on a clinical 3-T MRI using a dual-echo UTE sequence. Specimens were then scanned on a clinical CT scanner to measure volumetric BMD (vBMD) and then non-destructively mechanically tested in a sideways fall configuration. The PI in the cortical shaft demonstrated strong correlations with bone stiffness (r = -0.82, P = 0.0014), CT-derived vBMD (r = -0.64, P = 0.0149), and with average cortical thickness (r = -0.60, P = 0.0180). Furthermore, a hierarchical regression showed that PI was a strong predictor of bone stiffness which was independent of the other parameters. The findings from this study validate the MRI-derived porosity index as a useful measure of whole-bone mechanical integrity and stiffness.

Numerical analysis of hip fracture due to a sideways fall

The primary purpose of this paper is to outline a methodology for evaluating the likelihood of cortical bone fracture in the proximal femur in the event of a sideways fall. The approach includes conducting finite element (FE) analysis in which the cortical bone is treated as an anisotropic material, and the admissibility of the stress field is validated both in tension and compression regime. In assessing the onset of fracture, two methodologies are used, namely the Critical Plane approach and the Microstructure Tensor approach. The former is employed in the tension regime, while the latter governs the conditions at failure in compression. The propagation of localized damage is modeled using a constitutive law with embedded discontinuity (CLED). In this approach, the localized deformation is described by a homogenization procedure in which the average properties of cortical tissue intercepted by a macrocrack are established. The key material properties governing the conditions at failure are specified from a series of independent material tests conducted on cortical bone samples tested at different orientations relative to the loading direction. The numerical analysis deals with simulations of experiments involving the sideways fall, and the results are compared with the experimental data. This includes both the evolution of fracture pattern and the local load-displacement characteristics. The proposed approach is numerically efficient, and the results do not display a pathological mesh-dependency. Also, in contrast to the XFEM approach, the analysis does not require any extra degrees of freedom.

The effect of body configuration on the strain magnitude and distribution within the acetabulum during sideways falls: A finite element approach

While the incidence of hip fractures has declined during the last decades, the incidence of acetabular fractures resulting from low-energy sideways falls has increased, and the mechanisms responsible for this trend remain unknown. Previous studies have suggested that body configuration during the impact plays an important role in a hip fracture. Thus, the aim of this study was to investigate the effect of body configuration angles (trunk tilt angle, trunk flexion angle, femur horizontal rotation angle, and femur diaphysis angle) on low-energy acetabular fractures via a parametric analysis. A computed tomography-based (CT) finite element model of the ground-proximal femur-pelvis complex was created, and strain magnitude, time-history response, and distribution within the acetabulum were evaluated. Results showed that while the trunk tilt angle and femur diaphysis angle have the greatest effect on strain magnitude, the direction of the fall (lateral vs. posterolateral) contributes to strain distribution within the acetabulum. The results also suggest that strain level and distribution within the proximal femur and acetabulum resulting from a sideways fall are not similar and, in some cases, even opposite. Taken together, our simulations suggest that a more horizontal trunk and femoral shaft at the impact phase can increase the risk of low-energy acetabular fractures.

Periprosthetic femoral fractures in sideways fall configuration: comparative numerical analysis of the influence of femoral stem design

INTRODUCTION

The aim of this study was to investigate the mechanisms of periprosthetic fractures occurring as a result of a sideways fall in total hip arthroplasty patients, and to compare the predictions of numerical models in terms of load distribution on the implanted femur with clinical data.

MATERIALS AND METHODS

3 numerical models were built: 1 for intact femur and 2 for implanted femur with a straight stem (resembling PBF, Permedica) and with an anatomical stem (resembling ABG II, Stryker). 4 loading configurations were simulated; 1 simulates a vertical load, and 3 simulate a fall with impact on the greater trochanter in different directions. Stress state calculated in the implanted femur was compared for the 2 models with reference to the intact case. These were compared with clinical data collected at a single centre (Istituto Ortopedico Gaetano Pini, Milan, Italy) where 41 patients were investigated after periprosthetic fracture: 26 patients had a straight uncemented stem and 15 an anatomical uncemented stem.

RESULTS

The maximum calculated strain in compression in the case of ABG II implanted femur was 2 times higher than in the presence of PBF stem in the vertical loading configuration. For configurations of sideways fall, in both models, there was a progressive increase of stress state in the bone with increasing angle. Simulations of sideways fall elicited results in accordance with clinical observations: due to the peculiar stem design and consequent state of stress in the bone, anatomical stems seem to induce trochanteric fractures more frequently, while for straight stems type B fractures are more likely to occur.

CONCLUSIONS

Clinical findings confirmed numerical model predictions: stem design seems to highly influence distribution of stress in the bone and consequent localisation of the fracture site.

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.

Application of Fibre Bragg Grating Sensors in Strain Monitoring and Fracture Recovery of Human Femur Bone

Fibre Bragg Grating (FBG) sensors are gaining popularity in biomedical engineering. However, specific standards for in vivo testing for their use are absolutely limited. In this study, in vitro experimental tests were performed to investigate the behaviors and applications of gratings attached to intact and fractured thighbone for a range of compression loading (<300 N) based around some usual daily activities. The wavelength shifts and the corresponding strain sensitivities of the FBG sensors were measured to determine their effectiveness in monitoring the femoral fracture healing process. Four different arrangements of FBG sensors were selected to measure strains at different critical locations on the femoral sawbones surface. Data obtained for intact and plated sawbones were compared using both embedded longitudinal and coiled FBG arrays. Strains were measured close to the fracture, posterior linea aspera and popliteal surface areas, as well as at the proximal and distal ends of the synthetic femur; their responses are discussed herein. The gratings on the longitudinally secured FBG arrays were found to provide high levels of sensitivity and precise measurements, even for relatively small loads (<100 N). Nevertheless, embedding angled FBG sensors is essential to measure the strain generated by applied torque on the femur bone. The maximum recorded strain of the plated femur was 503.97 µε for longitudinal and -274.97 µε for coiled FBG arrays, respectively. These project results are important to configure effective arrangements and orientations of FBG sensors with respect to fracture position and fixation implant for future in vivo experiments.

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.

Cortical bone mapping improves finite element strain prediction accuracy at the proximal femur

Despite evidence of the biomechanical role of cortical bone, current state of the art finite element models of the proximal femur built from clinical CT data lack a subject-specific representation of the bone cortex. Our main research hypothesis is that the subject-specific modelling of cortical bone layer from CT images, through a deconvolution procedure known as Cortical Bone Mapping (CBM, validated for cortical thickness and density estimates) can improve the accuracy of CT-based FE models of the proximal femur, currently limited by partial volume artefacts. Our secondary hypothesis is that a careful choice of cortical-specific density-elasticity relationship may improve model accuracy. We therefore: (i) implemented a procedure to include subject-specific CBM estimates of both cortical thickness and density in CT-based FE models. (ii) defined alternative models that included CBM estimates and featured a cortical-specific or an independently optimised density-elasticity relationship. (iii) tested our hypotheses in terms of elastic strain estimates and failure load and location prediction, by comparing with a published cohort of 14 femurs, where strain and strength in stance and fall loading configuration were experimentally measured, and estimated through reference FE models that did not explicitly model the cortical compartment. Our findings support the main hypothesis: an explicit modelling of the proximal femur cortical bone layer including CBM estimates of cortical bone thickness and density increased the FE strains prediction, mostly by reducing peak errors (average error reduced by 30%, maximum error and 95th percentile of error distribution halved) and especially when focusing on the femoral neck locations (all error metrics at least halved). We instead rejected the secondary hypothesis: changes in cortical density-elasticity relationship could not improve validation performances. From these improved baseline strain estimates, further work is needed to achieve accurate strength predictions, as models incorporating cortical thickness and density produced worse estimates of failure load and equivalent estimates of failure location when compared to reference models. In summary, we recommend including local estimates of cortical thickness and density in FE models to estimate bone strains in physiological conditions, and especially when designing exercise studies to promote bone strength.

Biomechanical comparison of anterior cruciate ligament repair with internal brace augmentation versus anterior cruciate ligament repair without augmentation

BACKGROUND

Newer repair techniques of anterior cruciate ligament tears, including augmentation with internal brace, have shown promising clinical results. Few biomechanical studies exist comparing anterior cruciate ligament repair only versus repair with internal brace. The purpose of this study was to compare the load to failure and stiffness of anterior cruciate ligament repair with internal brace augmentation versus repair-only.

METHODS

Proximal femoral avulsion type anterior cruciate ligament injuries were created in 20 cadaver knees. Anterior cruciate ligament repair-only or repair with internal brace was performed using arthroscopic tools. Load to failure and failure modes were collected, with calculations of stiffness and energy to failure performed.

FINDINGS

The average load to failure for the internal brace group was higher than the repair-only group: 693 N (SD 248) versus 279 N (SD 91), P = .002. The stiffness and energy to failure values were higher for the internal brace group than the repair-only group: 83 N/mm versus 58 N/mm, P = .02 and 16.88 J (SD 12.44) versus 6.91 J (SD 2.49), P = .04, respectively. Failure modes differed between groups (P = .00097) with 80% failure in the repair-only due to suture pull through the anterior cruciate ligament and 90% failure in the internal brace group due to suture button pull through the femur.

INTERPRETATION

There was higher load to failure, stiffness, and energy to failure for the internal brace group compared to the repair-only group, and a high positive correlation between bone density and load to failure for the internal brace group.

CLINICAL SIGNIFICANCE

Anterior cruciate ligament repair with internal brace augmentation demonstrates significantly higher load to failure. It may be a useful adjunct to protect the anterior cruciate ligament repair from failure during the early stages of healing.

Biomechanical Computed Tomography analysis (BCT) for clinical assessment of osteoporosis

The surgeon general of the USA defines osteoporosis as "a skeletal disorder characterized by compromised bone strength, predisposing to an increased risk of fracture." Measuring bone strength, Biomechanical Computed Tomography analysis (BCT), namely, finite element analysis of a patient's clinical-resolution computed tomography (CT) scan, is now available in the USA as a Medicare screening benefit for osteoporosis diagnostic testing. Helping to address under-diagnosis of osteoporosis, BCT can be applied "opportunistically" to most existing CT scans that include the spine or hip regions and were previously obtained for an unrelated medical indication. For the BCT test, no modifications are required to standard clinical CT imaging protocols. The analysis provides measurements of bone strength as well as a dual-energy X-ray absorptiometry (DXA)-equivalent bone mineral density (BMD) T-score at the hip and a volumetric BMD of trabecular bone at the spine. Based on both the bone strength and BMD measurements, a physician can identify osteoporosis and assess fracture risk (high, increased, not increased), without needing confirmation by DXA. To help introduce BCT to clinicians and health care professionals, we describe in this review the currently available clinical implementation of the test (VirtuOst), its application for managing patients, and the underlying supporting evidence; we also discuss its main limitations and how its results can be interpreted clinically. Together, this body of evidence supports BCT as an accurate and convenient diagnostic test for osteoporosis in both sexes, particularly when used opportunistically for patients already with CT. Biomechanical Computed Tomography analysis (BCT) uses a patient's CT scan to measure both bone strength and bone mineral density at the hip or spine. Performing at least as well as DXA for both diagnosing osteoporosis and assessing fracture risk, BCT is particularly well-suited to "opportunistic" use for the patient without a recent DXA who is undergoing or has previously undergone CT testing (including hip or spine regions) for an unrelated medical condition.

Simulated lesions representative of metastatic disease predict proximal femur failure strength more accurately than idealized lesions

Metastatic disease in bone is characterized by highly amorphous and variable lesion geometry, with increased fracture risk. Assumptions of idealized lesion geometry made in previous finite element (FE) studies of metastatic disease in the proximal femur may not sufficiently capture effects of local stress/strain concentrations on predicted failure strength. The goal of this study was to develop and validate a FE failure model of the proximal femur incorporating artificial defects representative of physiologic metastatic disease. Data from 11 cadaveric femur specimens were randomly divided into either a training set (n = 5) or a test set (n = 6). Clinically representative artificial defects were created, and the femurs were loaded to failure under offset torsion. Voxel-based FE models replicating the experimental setup were created from the training set pre-fracture computed tomography data. Failure loads from the linear model with maximum principal strain failure criterion correlated best with the experimental data (R² = 0.86, p = 0.024). The developed model was found to be reliable when applied to the test dataset with a relatively low RMSE of 46.9 N, mean absolute percent error of 12.7 ± 17.1%, and cross-validation R² = 0.88 (p < 0.001). Models simulating realistic lesion geometry explained an additional 26% of the variance in experimental failure load compared to idealized lesion models (R² = 0.62, p = 0.062). Our validated automated FE model representative of physiologic metastatic disease may improve clinical fracture risk prediction and facilitate research studies of fracture risk during functional activities and with treatment interventions.

MRI-based assessment of proximal femur strength compared to mechanical testing

Half of the women who sustain a hip fracture would not qualify for osteoporosis treatment based on current DXA-estimated bone mineral density criteria. Therefore, a better approach is needed to determine if an individual is at risk of hip fracture from a fall. The objective of this study was to determine the association between radiation-free MRI-derived bone strength and strain simulations compared to results from direct mechanical testing of cadaveric femora. Imaging was conducted on a 3-Tesla MRI scanner using two sequences: one balanced steady-state free precession sequence with 300 μm isotropic voxel size and one spoiled gradient echo with anisotropic voxel size of 234 × 234 × 1500 μm. Femora were dissected free of soft-tissue and 4350-ohm strain-gauges were securely applied to surfaces at the femoral shaft, inferior neck, greater trochanter, and superior neck. Cadavers were mechanically tested with a hydraulic universal test frame to simulate loading in a sideways fall orientation. Sideways fall forces were simulated on MRI-based finite element meshes and bone stiffness, failure force, and force for plastic deformation were computed. Simulated bone strength metrics from the 300 μm isotropic sequence showed strong agreement with experimentally obtained values of bone strength, with stiffness (r = 0.88, p = 0.0002), plastic deformation point (r = 0.89, p < 0.0001), and failure force (r = 0.92, p < 0.0001). The anisotropic sequence showed similar trends for stiffness, plastic deformation point, and failure force (r = 0.68, 0.70, 0.84; p = 0.02, 0.01, 0.0006, respectively). Surface strain-gauge measurements showed moderate to strong agreement with simulated magnitude strain values at the greater trochanter, superior neck, and inferior neck (r = -0.97, -0.86, 0.80; p ≤0.0001, 0.003, 0.03, respectively). The findings from this study support the use of MRI-based FE analysis of the hip to reliably predict the mechanical competence of the human femur in clinical settings.

The status and challenges of replicating the mechanical properties of connective tissues using additive manufacturing

The ability to fabricate complex structures via precise and heterogeneous deposition of biomaterials makes additive manufacturing (AM) a leading technology in the creation of implants and tissue engineered scaffolds. Connective tissues (CTs) remain attractive targets for manufacturing due to their "simple" tissue compositions that, in theory, are replicable through choice of biomaterial(s) and implant microarchitecture. Nevertheless, characterisation of the mechanical and biological functions of 3D printed constructs with respect to their host tissues is often limited and remains a restriction towards their translation into clinical practice. This review aims to provide an update on the current status of AM to mimic the mechanical properties of CTs, with focus on arterial tissue, articular cartilage and bone, from the perspective of printing platforms, biomaterial properties, and topological design. Furthermore, the grand challenges associated with the AM of CT replacements and their subsequent regulatory requirements are discussed to aid further development of reliable and effective implants.

Investigating rolling as mechanism for humeral fractures in non-ambulant infants: a preliminary finite element study

AIM

To use personalised computed tomography (CT)-based finite element models to quantitatively investigate the likelihood of self-inflicted humeral fracture in non-ambulant infants secondary to rolling.

MATERIALS AND METHODS

Three whole-body post-mortem CT examinations of children at the age of rolling (two 4-month-old and one 6-month-old) were used. The mechanical moment needed by each infant to perform a rolling manoeuvre was calculated and applied to the finite element model in order to simulate spontaneous rolling from the prone to the supine position.

RESULTS

The maximum predicted strains were found to be substantially lower (with a difference of >80%) than the elastic limit of the bone.

CONCLUSION

Results of this study challenge the plausibility of self-inflicted humeral fracture caused by rolling in non-ambulant infants and indicate that it is unlikely for a humeral fracture to result from this mechanism without the assistance of an external force.

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.

The effect of boundary and loading conditions on patient classification using finite element predicted risk of fracture

BACKGROUND

Osteoporotic proximal femoral fractures associated to falls are a major health burden in the ageing society. Recently, bone strength estimated by finite element models emerged as a feasible alternative to areal bone mineral density as a predictor of fracture risk. However, previous studies showed that the accuracy of patients' classification under their risk of fracture using finite element strength when simulating posterolateral falls is only marginally better than that of areal bone mineral density. Patients tend to fall in various directions: since the predicted strength is sensitive to the fall direction, a prediction based on certain fall directions might not be fully representative of the physical event. Hence, side fall boundary conditions may not be completely representing the physical event.

METHODS

The effect of different side fall boundary and loading conditions on a retrospective cohort of 98 postmenopausal women was evaluated to test models' ability to discriminate fracture and control cases. Three different boundary conditions (Linear, Multi-point constraints and Contact model) were investigated under various anterolateral and posterolateral falls.

FINDINGS

The stratification power estimated by the area under the receiver operating characteristic curve was highest for Contact model (0.82), followed by Multi-point constraints and Linear models with 0.80. Both Contact and MPC models predicted high strains in various locations of the proximal femur including the greater trochanter, which has rarely reported previously.

INTERPRETATION

A full range of fall directions and less restrictive displacement constraints can improve the finite element strength ability to classify patients under their risk of fracture.

Assessment of finite element models for prediction of osteoporotic fracture

With increasing life expectancy and mortality rates, the burden of osteoporotic hip fractures is continually on an upward trend. In terms of prevention, there are several osteoporosis treatment strategies such as anti-resorptive drug treatments, which attempt to retard the rate of bone resorption, while promoting the rate of formation. With respect to prediction, several studies have provided insights into obtaining bone strength by non-invasive means through the application of FE analysis. However, what valuable information can we obtain from FE studies that have focused on osteoporosis research, with respect to the prediction of osteoporotic fractures? This paper aims to fine studies that have used FE analysis to predict fractures in the proximal femur through a systematic search of literature using PUBMED, with the main objective of supporting the diagnosis of osteoporosis. The focus of these FE studies is first discussed, and the methodological aspects are summarized, by mainly comparing and contrasting their meshing properties, material properties, and boundary conditions. The implications of these methodological differences in FE modelling processes and propositions with the aim of consolidating or minimalizing these differences are further discussed. We proved that studies need to start converging in terms of their input parameters to make the FE method applicable to clinical settings. This, in turn, will decrease the time needed for in vitro tests. Current advancements in FE analysis need to be consolidated before any further steps can be taken to implement engineering analysis into the clinical scenario.

Numerical modelling of hip fracture patterns in human femur

BACKGROUND AND OBJECTIVE

Hip fracture morphology is an important factor determining the ulterior surgical repair and treatment, because of the dependence of the treatment on fracture morphology. Although numerical modelling can be a valuable tool for fracture prediction, the simulation of femur fracture is not simple due to the complexity of bone architecture and the numerical techniques required for simulation of crack propagation. Numerical models assuming homogeneous fracture mechanical properties commonly fail in the prediction of fracture patterns. This paper focuses on the prediction of femur fracture based on the development of a finite element model able to simulate the generation of long crack paths.

METHODS

The finite element model developed in this work demonstrates the capability of predicting fracture patterns under stance loading configuration, allowing the distinction between the main fracture paths: intracapsular and extracapsular fractures. It is worth noting the prediction of different fracture patterns for the same loading conditions, as observed during experimental tests.

RESULTS AND CONCLUSIONS

The internal distribution of bone mineral density and femur geometry strongly influences the femur fracture morphology and fracture load. Experimental fracture paths have been analysed by means of micro-computed tomography allowing the comparison of predicted and experimental crack surfaces, confirming the good accuracy of the numerical model.

Effects of loading rate on the of mechanical behavior of the femur in falling condition

The Surgeon General estimates that by 2020, half of all Americans could have weak bones due to bone loss. Osteoporosis causes more than 1.5 million fractures every year. Identifying effective interventions based on individual patient characteristics remains a major challenge. Proximal femur fractures are common and devastating events for individuals with osteoporosis. Since fracture is primarily a mechanical event, noninvasive predictions of fracture strength and location would be useful both for identifying at-risk individuals and evaluating treatment effects. However, bone fracture prediction is complicated due to the complex microstructure and nanostructure of bone. Bone is a highly heterogeneous material with rate-dependent mechanical behavior and large inter-individual variation. In this study, we designed two mechanical test procedures to understand the mechanical response of bone under impact and quasi-static load tests. The boundary conditions of the tests were designed in a way to simulate a fall to the side. The present study consists of three main parts: cadaver testing, quantitative image analysis, and finite element (FE) modeling. We obtained ten human femur bones and used high-resolution CT to quantify the microstructure and density of each sample. Specimen-specific FE models were created to evaluate the ability of various failure criteria to predict experimental fracture. Afterward, the samples were tested and their failure patterns were recorded. The fractured samples were rescanned to analyze the fractured surfaces. Our experimental results show that the loading necessary to fracture the femur samples is much higher in the impact tests. However, the toughening mechanisms are more pronounced in quasi-static tests. We found that FE model formulations were able to accurately predict femur stiffness and strength for quasi-static and impact conditions separately, but that no single formulation could account for the rate-dependent outcomes.

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.

Biofidelic finite element models for accurately classifying hip fracture in a retrospective clinical study of elderly women from the AGES Reykjavik cohort

Clinical retrospective studies have only reported limited improvements in hip fracture classification accuracy using finite element (FE) models compared to conventional areal bone mineral density (aBMD) measurements. A possible explanation is that state-of-the-art quasi-static models do not estimate patient-specific loads. A novel FE modeling technique was developed to improve the biofidelity of simulated impact loading from sideways falling. This included surrogate models of the pelvis, lower extremities, and soft tissue that were morphed based on subject anthropometrics. Hip fracture prediction models based on aBMD and FE measurements were compared in a retrospective study of 254 elderly female subjects from the AGES-Reykjavik study. Subject fragility ratio (FR) was defined as the ratio between the ultimate forces of paired biofidelic models, one with linear elastic and the other with non-linear stress-strain relationships in the proximal femur. The expected end-point value (EEV) was defined as the FR weighted by the probability of one sideways fall over five years, based on self-reported fall frequency at baseline. The change in maximum volumetric strain (ΔMVS) on the surface of the femoral neck was calculated between time of ultimate femur force and 90% post-ultimate force in order to assess the extent of tensile tissue damage present in non-linear models. After age-adjusted logistic regression, the area under the receiver-operator curve (AUC) was highest for ΔMVS (0.72), followed by FR (0.71), aBMD (0.70), and EEV (0.67), however the differences between FEA and aBMD based prediction models were not deemed statistically significant. When subjects with no history of falling were excluded from the analysis, thus artificially assuming that falls were known a priori with no uncertainty, a statistically significant difference in AUC was detected between ΔMVS (0.85), and aBMD (0.74). Multivariable linear regression suggested that the variance in maximum elastic femur force was best explained by femoral head radius, pelvis width, and soft tissue thickness (R2 = 0.79; RMSE = 0.46 kN; p < 0.005). Weighting the hip fracture prediction models based on self-reported fall frequency did not improve the models' sensitivity, however excluding non-fallers lead to significant differences between aBMD and FE based models. These findings suggest that an accurate assessment of fall probability is necessary for accurately identifying individuals predisposed to hip fracture.

From bed to bench: How in silico medicine can help ageing research

Driven by the raising ethical concerns surrounding animal experimentation, there is a growing interest for non-animal methods, in vitro or in silico technologies that can be used to reduce, refine, and replace animal experimentation. In addition, animal experimentation is being critically revised in regard to its ability to predict clinical outcomes. In this manuscript we describe an initial exploration where a set of in vivo imaging based subject-specific technologies originally developed to predict the risk of femoral strength and hip fracture in osteoporotic patients, were adapted to assess the efficacy of bone drugs pre-clinically on mice. The CT2S technology we developed generates subject-specific models based on Computed Tomography that can separate fractured and non-fractured patients with an accuracy of 82%. When used in mouse experiments the use of in vivo imaging and modelling was found to improve the reproducibility of Bone Mineral Content measurements to a point where up to 63% less mice would be required to achieve the same statistical power of a conventional cross-sectional study. We also speculate about a possible approach where animal-specific and patient-specific models could be used to better translate the observation made on animal models into predictions of response in humans.

Mapping anisotropy improves QCT-based finite element estimation of hip strength in pooled stance and side-fall load configurations

Hip fractures are one of the most severe consequences of osteoporosis. Compared to the clinical standard of DXA-based aBMD at the femoral neck, QCT-based FEA delivers a better surrogate of femoral strength and gains acceptance for the calculation of hip fracture risk when a CT reconstruction is available. Isotropic, homogenised voxel-based, finite element (hvFE) models are widely used to estimate femoral strength in cross-sectional and longitudinal clinical studies. However, fabric anisotropy is a classical feature of the architecture of the proximal femur and the second determinant of the homogenised mechanical properties of trabecular bone. Due to the limited resolution, fabric anisotropy cannot be derived from clinical CT reconstructions. Alternatively, fabric anisotropy can be extracted from HR-pQCT images of cadaveric femora. In this study, fabric anisotropy from HR-pQCT images was mapped onto QCT-based hvFE models of 71 human proximal femora for which both HR-pQCT and QCT images were available. Stiffness and ultimate load computed from anisotropic hvFE models were compared with previous biomechanical tests in both stance and side-fall configurations. The influence of using the femur-specific versus a mean fabric distribution on the hvFE predictions was assessed. Femur-specific and mean fabric enhance the prediction of experimental ultimate force for the pooled, i.e. stance and side-fall, (isotropic: r²=0.81, femur-specific fabric: r²=0.88, mean fabric: r²=0.86,p<0.001) but not for the individual configurations. Fabric anisotropy significantly improves bone strength prediction for the pooled configurations, and mapped fabric provides a comparable prediction to true fabric. The mapping of fabric anisotropy is therefore expected to help generate more accurate QCT-based hvFE models of the proximal femur for personalised or multiple load configurations.

Osteoporotic hip fracture prediction: is T-score based criterion enough? A Hip Structural Analysis based model

At present, the current gold-standard for osteoporosis diagnosis is based on bone mineral density measurement, which, however, has been demonstrated to poorly estimate fracture risk. Further parameters in the hands of the clinicians are represented by the Hip Structural Analysis (HSA) variables, which include geometric information of the proximal femur cross-section. The purpose of this study was to investigate the suitability of HSA parameters as additional hip fracture risk predictors. With this aim, twenty-eight three-dimensional patient-specific models of the proximal femur were built from CT images and a sideways fall condition was reproduced by finite element analyses. A tensile or compressive predominance based on minimum and maximum principal strains was determined at each volume element and a Risk Factor (RF) was calculated. The power of HSA variables combinations to predict the maximum superficial RF values was assessed by multivariate linear regression analysis. The optimal regression model, identified through the Akaike information criterion, only comprises two variables, the buckling ratio and the neck-shaft angle. In order to validate the study, the model was tested on two additional patients who suffered a hip fracture after a fall. The results classified the patients in the high risk level, confirming the prediction power of the adopted model.

Influence of geometry on proximal femoral shaft strains: Implications for atypical femoral fracture

INTRODUCTION

Atypical femoral fractures (AFF) are characterized as low-energy fractures of the femoral shaft or subtrochanteric region. Femoral geometry is known to play a role in AFF risk; it is hypothesized that high-risk geometries are associated with elevated femoral shaft strain. However, it is not well known which geometric parameters have the greatest effect on strain, or whether interaction between parameters is significant. The purpose of this study was to thoroughly quantify the relationship between femoral geometry and diaphyseal strain, using patient specific finite element (FE) modelling in concert with parametric mesh morphing.

METHODS

Ten FE models were generated from computed tomography (CT) images of cadaveric femora. Heterogeneous material properties were assigned based on average CT intensities at element locations and models were subject to loads and boundary conditions representing the stance phase of gait. Mesh morphing was used to manipulate 8 geometric parameters: neck shaft angle (NSA), neck version angle (NV), neck length (NL), femoral length (FL), lateral bowing angle (L.Bow), anterior bowing angle (A.Bow), shaft diameter (S.Dia), and cortical bone thickness (C·Th). A 2-Level full factorial analysis was used to explore the effect of different combinations of physiologically realistic minimum and maximum values for each parameter. Statistical analysis (Generalized Estimating Equations) was used to assess main effects and first order interactions of each parameter.

RESULTS

Six independent parameters and seven interaction terms had statistically significant (p<0.05) effects on peak strain and strained volume. For both measures, the greatest changes were caused by S.Dia, L.Bow, and A.Bow, and/or first order interactions involving two of these variables.

CONCLUSIONS

As hypothesized, a large number of geometric measures (six) and first order interactions (seven) are associated with changes in femoral shaft strain. These measures can be evaluated radiographically, which may have important implications for future studies investigating AFF risk in clinical populations.

Clinical hip fracture is accompanied by compression induced failure in the superior cortex of the femoral neck

Hip fractures pose a major health problem throughout the world due to their devastating impact. Current theories for why these injuries are so prevalent in the elderly point to an increased propensity to fall and decreases in bone mass with ageing. However, the fracture mechanisms, particularly the stress and strain conditions leading to bone failure at the hip remain unclear. Here, we directly examined the cortical bone from clinical intra-capsular hip fractures at a microscopic level, and found strong evidence of compression induced failure in the superior cortex. A total of 143 sections obtained from 24 femoral neck samples that were retrieved from 24 fracturing patients at surgery were examined using laser scanning confocal microscopy (LSCM) after fluorescein staining. The stained microcracks showed significantly higher density in the superior cortex than in the inferior cortex, indicating a greater magnitude of strain in the superior femoral neck during the failure-associated deformation and fracture process. The predominant stress state for each section was reconstructed based on the unique correlation between the microcrack pattern and the stress state. Specifically, we found clear evidence of longitudinal compression and buckling as the primary failure mechanisms in the superior cortex. These findings demonstrate the importance of microcrack analysis in studying clinical hip fractures, and point to the central role of the superior cortex failure as an important aspect of the failure initiation in clinical intra-capsular hip fractures.

Validation of an alignment method using motion tracking system for in-vitro orientation of cadaveric hip joints with reduced set of anatomical landmarks

Accurate in-vitro orientation of cadaveric hip joints is challenging due to limited available anatomical landmarks. Published hip joint in-vitro investigations commonly lack details on methods used to achieve reported orientations and the accuracy with which the desired orientation has been achieved. The aim of this study was to develop an accurate method for orienting hip joints with limited anatomical landmarks for in-vitro investigations, and to compare this method against orientation using guiding axes and by visual approximation. The proposed orientation method resulted in orientation angles achieved to within one degree (SD ± 0.58°). For most specimens, orientation using physical tools resulted in errors of ±8° and ±12° in at least one of three orientation angles used to place the femur and pelvis in neutral orientation, respectively. Precision was also worse, with SDs ranging from ±1° to ±5° for orientation angles of femoral specimens and SDs ranging from ±1° to ±8° for pelvic specimens. The error in the orientation angles was worse for orientation by visual approximation and the range of SDs were greater for both the femur and pelvis. Finite element modeling was used to assess the effects of observed orientation errors, on prediction of fracture load. In most cases, the largest error in fracture load among all trials exceeded 30%, relative to a femur oriented without any error in the orientation angles.

Study of the variations of fall induced hip fracture risk between right and left femurs using CT-based FEA

Background

Hip fracture of elderly people—suffering from osteoporosis—is a severe public health concern, which can be reduced by providing a prior assessment of hip fracture risk. Image-based finite element analysis (FEA) has been considered an effective computational tool to assess the hip fracture risk. Considering the femoral neck region is the weakest, fracture risk indicators (FRI) are evaluated for both single-legged stance and sideways fall configurations and are compared between left and right femurs of each subject. Quantitative Computed Tomography (QCT) scan datasets of thirty anonymous patients’ left and right femora have been considered for the FE models, which have been simulated with an equal magnitude of load applied to the aforementioned configurations. The requirement of bilateral hip assessment in predicting the fracture risk has been explored in this study.

Results

Comparing the sideways fall and single-legged stance, the FRI varies by 64 to 74% at the superior aspects and by 14 to 19% at the inferior surfaces of both the femora. The results of this in vivo analysis clearly substantiate that the fracture is expected to initiate at the superior surface of femoral neck region if a patient falls from his/her standing height. The distributions of FRI between the femurs vary considerably, and the variability is significant at the superior aspects. The p value (= 0.02) obtained from paired sample t-Test yields p value ≤ 0.05, which shows the evidence of variability of the FRI distribution between left and right femurs. Moreover, the comparison of FRIs between the left and right femur of men and women shows that women are more susceptible to hip fracture than men.

Conclusions

The results and statistical variation clearly signify a need for bilateral hip scanning in predicting hip fracture risk, which is clinically conducted, at present, based on one hip chosen randomly and may lead to inaccurate fracture prediction. This study, although preliminary, may play a crucial role in assessing the hip fractures of the geriatric population and thereby, reducing the cost of treatment by taking predictive measure.

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation

This protocol describes the method using digital image correlation to estimate cortical strain from high speed video images of the cadaveric femoral surface obtained from mechanical testing. This optical method requires a texture of many contrasting fiduciary marks on a solid white background for accurate tracking of surface deformation as loading is applied to the specimen. Immediately prior to testing, the surface of interest in the camera view is painted with a water-based white primer and allowed to dry for several minutes. Then, a black paint is speckled carefully over the white background with special consideration for the even size and shape of the droplets. Illumination is carefully designed and set such that there is optimal contrast of these marks while minimizing reflections through the use of filters. Images were obtained through high speed video capture at up to 12,000 frames/s. The key images prior to and including the fracture event are extracted and deformations are estimated between successive frames in carefully sized interrogation windows over a specified region of interest. These deformations are then used to compute surface strain temporally during the fracture test. The strain data is very useful for identifying fracture initiation within the femur, and for eventual validation of proximal femur fracture strength models derived from Quantitative Computed Tomography-based Finite Element Analysis (QCT/FEA).