Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

A convolutional neural network-based method for the generation of super-resolution 3D models from clinical CT images

BACKGROUND AND OBJECTIVE

The accurate evaluation of bone mechanical properties is essential for predicting fracture risk based on clinical computed tomography (CT) images. However, blurring and noise in clinical CT images can compromise the accuracy of these predictions, leading to incorrect diagnoses. Although previous studies have explored enhancing trabecular bone CT images to super-resolution (SR), none of these studies have examined the possibility of using clinical CT images from different instruments, typically of lower resolution, as a basis for analysis. Additionally, previous studies rely on 2D SR images, which may not be sufficient for accurate mechanical property evaluation, due to the complex nature of the 3D trabecular bone structures. The objective of this study was to address these limitations.

METHODS

A workflow was developed that utilizes convolutional neural networks to generate SR 3D models across different clinical CT instruments. The morphological and finite-element-derived mechanical properties of these SR models were compared with ground truth models obtained from micro-CT scans.

RESULTS

A significant improvement in analysis accuracy was demonstrated, where the new SR models increased the accuracy by up to 700 % compared with the low-resolution data, i.e. clinical CT images. Additionally, we found that the mixture of different CT image datasets may improve the SR model performance.

CONCLUSIONS

SR images, generated by convolutional neural networks, outperformed clinical CT images in the determination of morphological and mechanical properties. The developed workflow could be implemented for fracture risk prediction, potentially leading to improved diagnoses and subsequent clinical decision making.

Impact forces in backward falls: Subject-specific video-based rigid body simulation of backward falls

A critical missing component in the study of real-world falls is the ability to accurately determine impact forces resulting from the fall. Subject-specific rigid body dynamic (RBD) models calibrated to video captured falls can quantify impact forces and provide additional insights into injury risk factors. RBD models were developed based on five backward falls captured on surveillance video in long-term care facilities in British Columbia, Canada. Model joint stiffness and initial velocities were calibrated to match the kinematics of the fall and contact forces were calculated. The effect of joint stiffnesses (neck, lumbar spine, hip, and knee joint) on head contact forces were determined by modifying the calibrated stiffness values ±25%. Fall duration, fall trajectories, and maximum velocities showed a close match between fall events and simulations. The maximum value of pelvic velocity difference between Kinovea (an open-source software 2D digitization software) and Madymo multibody modeling was found to be 6% ± 21.58%. Our results demonstrate that neck and hip stiffness values have a non-significant yet large effect on head contact force (t(3) = 1, p = 0.387 and t(3) = 2, p = 0.138), while lower effects were observed for knee stiffness, and the effect of lumbar spine stiffness was negligible. The subject-specific fall simulations constructed from real world video captured falls allow for direct quantification of force outcomes of falls and may have applications in improving the assessment of fall-induced injury risks and injury prevention methods.

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).

Assessing the risk of re-fracture related to the percentage of partial union in scaphoid waist fractures

Aims

There is ambiguity surrounding the degree of scaphoid union required to safely allow mobilization following scaphoid waist fracture. Premature mobilization could lead to refracture, but late mobilization may cause stiffness and delay return to normal function. This study aims to explore the risk of refracture at different stages of scaphoid waist fracture union in three common fracture patterns, using a novel finite element method.

Methods

The most common anatomical variant of the scaphoid was modelled from a CT scan of a healthy hand and wrist using 3D Slicer freeware. This model was uploaded into COMSOL Multiphysics software to enable the application of physiological enhancements. Three common waist fracture patterns were produced following the Russe classification. Each fracture had differing stages of healing, ranging from 10% to 90% partial union, with increments of 10% union assessed. A physiological force of 100 N acting on the distal pole was applied, with the risk of refracture assessed using the Von Mises stress.

Results

Overall, 90% to 30% fracture unions demonstrated a small, gradual increase in the Von Mises stress of all fracture patterns (16.0 MPa to 240.5 MPa). All fracture patterns showed a greater increase in Von Mises stress from 30% to 10% partial union (680.8 MPa to 6,288.6 MPa).

Conclusion

Previous studies have suggested 25%, 50%, and 75% partial union as sufficient for resuming hand and wrist mobilization. This study shows that 30% union is sufficient to return to normal hand and wrist function in all three fracture patterns. Both 50% and 75% union are unnecessary and increase the risk of post-fracture stiffness. This study has also demonstrated the feasibility of finite element analysis (FEA) in scaphoid waist fracture research. FEA is a sustainable method which does not require the use of finite scaphoid cadavers, hence increasing accessibility into future scaphoid waist fracture-related research.

The efficacy of femoral augmentation for hip fracture prevention using ceramic-based cements: A preliminary experimentally-driven finite element investigation

Femoral fractures due to sideways falls continue to be a major cause of concern for the elderly. Existing approaches for the prevention of these injuries have limited efficacy. Prophylactic femoral augmentation systems, particularly those involving the injection of ceramic-based bone cements, are gaining more attention as a potential alternative preventative approach. We evaluated the mechanical effectiveness of three variations of a bone cement injection pattern (basic ellipsoid, hollow ellipsoid, small ellipsoid) utilizing finite element simulations of sideways fall impacts. The basic augmentation pattern was tested with both high- and low-strength ceramic-based cements. The cement patterns were added to the finite element models (FEMs) of five cadaveric femurs, which were then subject to simulated sideways falls at seven impact velocities ranging from 1.0 m/s to 4.0 m/s. Peak impact forces and peak acetabular forces were examined, and failure was evaluated using a strain-based criterion. We found that the basic HA ellipsoid provided the highest increases in both the force at the acetabulum of the impacted femur ("acetabular force", 55.0% ± 22.0%) and at the force plate ("impact force", 37.4% ± 15.8%). Changing the cement to a weaker material, brushite, resulted in reduced strengthening of the femur (45.2% ± 19.4% acetabular and 30.4% ± 13.0% impact). Using a hollow version of the ellipsoid appeared to have no effect on the fracture outcome and only a minor effect on the other metrics (54.1% ± 22.3% acetabular force increase and 35.3% ± 16.0% impact force increase). However, when the outer two layers of the ellipsoid were removed (small ellipsoid), the force increases that were achieved were only 9.8% ± 5.5% acetabular force and 8.2% ± 4.1% impact force. These results demonstrate the importance of supporting the femoral neck cortex to prevent femoral fractures in a sideways fall, and provide plausible options for prophylactic femoral augmentation. As this is a preliminary study, the surgical technique, the possible effects of trabecular bone damage during the augmentation process, and the effect on the blood supply to the femoral head must be assessed further.

Fatty infiltration of hip muscles and trochanteric soft tissue thickness are associated with hip fractures in the elderly

PURPOSE

Apart from bone conditions, muscle and soft tissue parameters might also influence hip fractures. We aimed to evaluate the association between hip muscle and trochanteric soft tissue parameters and hip fractures.

METHODS

We retrospectively reviewed 60 patients with hip fractures and 114 controls without hip fractures. Cases and controls were matched for age, sex, and body mass index using propensity score matching. Muscle cross-sectional area (CSA), mean attenuation, and fatty infiltration rate (FIR) (proportion of intramuscular fat content) were measured on CT images for the gluteus maximus, the gluteus medius/minimus, and the anterior and medial compartments of the upper thigh. Trochanteric soft tissue thickness (TSTT) and femoral neck attenuation were also measured. Univariate and multivariate analyses were conducted to identify potential risk factors of hip fractures.

RESULTS

Patients with hip fractures had significantly lower femoral neck attenuation, TSTT, and CSA of the gluteus maximus and anterior compartment than controls. FIR of all hip muscle groups were significantly higher in hip fracture patients than controls. Multivariate analysis revealed that every 1% increase in FIR of medial compartment independently increased the odds of hip fractures by 23.7% (OR = 1.237, 95% CI = 1.093-1.401) and every 1 cm longer TSTT independently decreased the odds by 32.8% (OR = 0.672, 95% CI = 0.477-0.946).

CONCLUSION

Fatty infiltration of hip muscles can better discriminate hip fractures than muscle area. Increased TSTT is independently associated with low fracture risk.

A Review of CT-Based Fracture Risk Assessment with Finite Element Modeling and Machine Learning

PURPOSE OF REVIEW

We reviewed advances over the past 3 years in assessment of fracture risk based on CT scans, considering methods that use finite element models, machine learning, or a combination of both.

RECENT FINDINGS

Several studies have demonstrated that CT-based assessment of fracture risk, using finite element modeling or biomarkers derived from machine learning, is equivalent to currently used clinical tools. Phantomless calibration of CT scans for bone mineral density enables accurate measurements from routinely taken scans. This opportunistic use of CT scans for fracture risk assessment is facilitated by high-quality automated segmentation with deep learning, enabling workflows that do not require user intervention. Modeling of more realistic and diverse loading conditions, as well as improved modeling of fracture mechanisms, has shown promise to enhance our understanding of fracture processes and improve the assessment of fracture risk beyond the performance of current clinical tools. CT-based screening for fracture risk is effective and, by analyzing scans that were taken for other indications, could be used to expand the pool of people screened, therefore improving fracture prevention. Finite element modeling and machine learning both provide valuable tools for fracture risk assessment. Future approaches should focus on including more loading-related aspects of fracture risk.

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.

The Influence of Fall Direction and Hip Protector on Fracture Risk: FE Model Predictions Driven by Experimental Data

Hip fractures in older adults, which often lead to lasting impairments and an increased risk of mortality, are a major public health concern. Hip fracture risk is multi-factorial, affected by the risk of falling, the load acting on the femur, and the load the femur can withstand. This study investigates the influence of impact direction on hip fracture risk and hip protector efficacy. We simulated falls for 4 subjects, in 7 different impact directions (15° and 30° anterior, lateral, and 15°, 30°, 60°, and 90° posterior) at two different impact velocities (2.1 and 3.1 m/s), all with and without hip protector, using previously validated biofidelic finite element models. We found the highest number of fractures and highest fragility ratios in lateral and 15° posterior impacts. The hip protector attenuated femur forces by 23–49 % for slim subjects under impact directions that resulted in fractures (30° anterior to 30° posterior). The hip protector prevented all fractures (6/6) for 2.1 m/s impacts, but only 10% of fractures for 3.1 m/s impacts. Our results provide evidence that, regarding hip fracture risk, posterior-lateral impacts are as dangerous as lateral impacts, and they support the efficacy of soft-shell hip protectors for anterior- and posterior-lateral impacts.

Personalised 3D Assessment of Trochanteric Soft Tissues Improves HIP Fracture Classification Accuracy

Passive soft tissues surrounding the trochanteric region attenuate fall impact forces and thereby control hip fracture risk. The degree of attenuation is related to Soft Tissue Thickness (STT). STT at the neutral hip impact orientation, estimated using a regression relation in body mass index (BMI), was previously shown to influence the current absolute risk of hip fracture (ARF0) and its fracture classification accuracy. The present study investigates whether fracture classification using ARF0 improves when STT is determined from the subject’s Computed-Tomography (CT) scans (i.e. personalised) in an orientation-specific (i.e. 3D) manner. STT is calculated as the shortest distance along any impact orientation between a semi-automatically segmented femur surface and an automatically segmented soft tissue/air boundary. For any subject, STT along any of the 33 impact orientations analysed always exceeds the value estimated using BMI. Accuracy of fracture classification using ARF0 improves when using personalised 3D STT estimates (AUC = 0.87) instead of the BMI-based STT estimate (AUC = 0.85). The improvement is smaller (AUC = 0.86) when orientation-specificity of CT-based STT is suppressed and is nil when personalisation is suppressed instead. Thus, fracture classification using ARF0 improves when CT is used to personalise STT estimates and improves further when, in addition, the estimates are orientation specific.

Finite element derived femoral strength is a better predictor of hip fracture risk than aBMD in the AGES Reykjavik study cohort

Hip fractures associated with a high economic burden, loss of independence, and a high rate of post-fracture mortality, are a major health concern for modern societies. Areal bone mineral density is the current clinical metric of choice when assessing an individual's future risk of fracture. However, this metric has been shown to lack sensitivity and specificity in the targeted selection of individuals for preventive interventions. Although femoral strength derived from computed tomography based finite element models has been proposed as an alternative based on its superior femoral strength prediction ex vivo, such predictions have only shown marginal or no improvement for assessing hip fracture risk. This study compares finite element derived femoral strength to aBMD as a metric for hip fracture risk assessment in subjects (N = 601) from the AGES Reykjavik Study cohort and analyses the dependence of femoral strength predictions and classification accuracy on the material model and femoral loading alignment. We found hip fracture classification based on finite element derived femoral strength to be significantly improved compared to aBMD. Finite element models with non-linear material models performed better at classifying hip fractures compared to finite element models with linear material models and loading alignments with low internal rotation and adduction, which do not correspond to weak femur alignments, were found to be most suitable for hip fracture classification.

Finite Element Assessment of Bone Fragility from Clinical Images

PURPOSE OF REVIEW

We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.

RECENT FINDINGS

CT-to-FE is useful in longitudinal treatment evaluation and groups discrimination. In metastatic lesions, CT-to-FE strength alone accurately predicts impending femoral fractures. In osteoporosis, strength from CT-to-FE or DXA-to-FE predicts incident fractures similarly to DXA-aBMD. Coupling loads and strength (possibly in dynamic models) may improve prediction. One promising MRI-to-FE workflow may now be tested on clinical data. Evidence of artificial intelligence usefulness is appearing. CT-to-FE is already clinical in opportunistic CT screening for osteoporosis, and risk of metastasis-related impending fractures. Short-term keys to improve image-to-FE in osteoporosis may be coupling FE with fall risk estimates, pool FE results with other parameters through robust artificial intelligence approaches, and increase reproducibility and cross-validation of models. Modeling bone modifications over time and bone fracture mechanics are still open issues.

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care

PURPOSE OF REVIEW

Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation.

RECENT FINDINGS

Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

Prophylactic augmentation implants in the proximal femur for hip fracture prevention: An in silico investigation of simulated sideways fall impacts

Femoral fractures from sideways falls in the elderly are associated with significant rates of morbidity and mortality. Approaches to prevent these catastrophic injuries include pharmacological treatments, which have limited efficacy. Prophylactic femoral augmentation systems are a promising alternative that are gaining prominence by addressing the most debilitating osteoporosis-related fracture. We have developed finite element models (FEMs) of a novel experimental sideways fall simulator for cadavers. By virtue of the range of specimens and injury outcomes, these FEMs are well-suited to the evaluation of such implants. The purpose of this study was to use the FEMs to evaluate the mechanical effectiveness of three different prophylactic femoral augmentation systems. Models of the Y-Strut® (Hyprevention®, Pessac, France), Gamma Nail® (Stryker, Kalamazoo, USA), and a simple lag screw femoral fracture implant systems were placed into FEMs of five cadaveric pelvis-femur constructs embedded in a soft tissue surrogate, which were then subject to simulated sideways falls at seven impact velocities. Femur-only FEMs were also evaluated. Peak impact forces and peak acetabular forces were examined, and failure was evaluated using a strain-based criterion. We found that the femoral augmentation systems increased the peak forces prior to fracture, but were unable to prevent fracture for severe impacts. The Gamma Nail® system consistently produced the largest strength increases relative to the unaugmented femur for all five specimens in both the pendulum-drop FEMs and the femur-only simulations. In some cases, the same implant appeared to cause fractures in the acetabulum. The femur-only FEMs showed larger force increases than the pendulum-drop simulations, which suggests that the results of the femur-only simulations may not represent sideways falls as accurately as the soft tissue-embedded pendulum-drop simulations. The results from this study demonstrate the ability to simulate a high energy phenomenon and the effect of implants in an in silico environment. The results also suggest that implants could increase the force applied to the proximal femur during impact. Fracture outcomes from the tested implants can be used to inform the design of future devices, which reaffirms the value of modelling with biofidelic considerations in the implant design process. To the authors' knowledge, this is the first paper to use more complex biofidelic FEMs to assess prophylactic femoral augmentation methods.

Factors that influence the distribution of impact force relative to the proximal femur during lateral falls

In-vivo fall simulations generally evaluate hip fracture risk through differences in impact force magnitude; however, the distribution of force over the hip likely modulates loading and subsequent injury risk of the underlying femur. The current study characterized impact force distribution over the hip during falls, and the influence of biological sex and trochanteric soft tissue thickness (TSTT). Forty young adults completed fall simulation protocols (FSP) including highly controlled vertical pelvis and more dynamic kneeling and squat releases. At the instant of peak force, percentage of impact force applied in a circular region (r = 5 cm) centered over the greater trochanter (F_GT%) was determined to characterize force localization. To assess the need for anatomically aligned pressure analysis, this process was repeated utilizing peak pressure location as a surrogate for the greater trochanter (F_PP%). F_GT% was 10.8 and 21.9% greater in pelvis release than kneeling and squat releases respectively. F_GT% was 19.1 and 30.4% greater in males and low-TSTT individuals compared to females and high-TSTT individuals. TSTT explained the most variance (43.7-55.3%) in F_GT% across all protocols, while sex explained additional variance (5.3-19.0%) during dynamic releases. In all FSP, TSTT-groups and sexes, average peak pressure location was posterior and distal to the GT. F_PP% overestimated F_GT% by an average of 15.7%, highlighting the need for anatomically aligned pressure analysis. This overestimation was FSP and sex dependent, minimized during pelvis release and in males. The data have important implications from clinical and methodological perspectives, and for implementation in tissue-level computational models.

Anatomically Aligned Loading During Falls: Influence of Fall Protocol, Sex and Trochanteric Soft Tissue Thickness

Fall simulations provide insight into skin-surface impact dynamics but have focused on vertical force magnitude. Loading direction and location (relative to the femur) likely influence stress generation. The current study characterized peak impact vector magnitude, orientation, and center of pressure over the femur during falls, and the influence of biological sex and trochanteric soft tissue thickness (TSTT). Forty young adults completed fall simulations including a vertical pelvis release, as well as kneeling and squat releases, which incorporate lateral/rotational motion. Force magnitude and direction varied substantially across fall simulations. Kneeling and squat releases elicited 57.4 and 38.8% greater force than pelvis release respectively, with differences accentuated in males. With respect to the femoral shaft, kneeling release had the most medially and squat release the most distally directed loading vectors. Across all fall simulations, sex and TSTT influenced force magnitude and center of pressure. Force was 28.0% lower in females and was applied more distally than in males. Low-TSTT participants had 16.8% lower force, applied closer to the greater trochanter than high-TSTT participants. Observed differences in skin-surface impact dynamics likely interact with underlying femur morphology to influence stress generation. These data should serve as inputs to tissue-level computational models assessing fracture risk.

The Role of Fall Biomechanics in the Cause and Prevention of Bone Fractures in Older Adults

PURPOSE OF REVIEW

Adults over age 65 experience the highest rates of bone fracture, and 90% of fractures in older adults are caused by falls from standing height or lower. Advances in fracture prevention rely on our ability to prevent falls, reduce the severity of falls, and enhance the resistance of bone to trauma. To help guide these efforts, we need improved understanding on the types of falls that cause fractures.

RECENT FINDINGS

In this review, we describe recent evidence on how the mechanics of falls in older adults influence the risk for fractures to the hip, wrist, vertebrae, and humerus. We discuss how fracture risk depends on fall height, fall direction, and landing configuration. We also review the benefits of exercise, wearable protective gear, and environmental modifications in preventing fractures in older adults. Our findings highlight promising new directions in fracture prevention, and the need for collaboration between the bone and falls research communities to implement proven strategies and generate new solutions.

Validation of 3D finite element models from simulated DXA images for biofidelic simulations of sideways fall impact to the hip

Computed tomography (CT)-derived finite element (FE) models have been proposed as a tool to improve the current clinical assessment of osteoporosis and personalized hip fracture risk by providing an accurate estimate of femoral strength. However, this solution has two main drawbacks, namely: (i) 3D CT images are needed, whereas 2D dual-energy x-ray absorptiometry (DXA) images are more generally available, and (ii) quasi-static femoral strength is predicted as a surrogate for fracture risk, instead of predicting whether a fall would result in a fracture or not. The aim of this study was to combine a biofidelic fall simulation technique, based on 3D computed tomography (CT) data with an algorithm that reconstructs 3D femoral shape and BMD distribution from a 2D DXA image. This approach was evaluated on 11 pelvis-femur constructs for which CT scans, ex vivo sideways fall impact experiments and CT-derived biofidelic FE models were available. Simulated DXA images were used to reconstruct the 3D shape and bone mineral density (BMD) distribution of the left femurs by registering a projection of a statistical shape and appearance model with a genetic optimization algorithm. The 2D-to-3D reconstructed femurs were meshed, and the resulting FE models inserted into a biofidelic FE modeling pipeline for simulating a sideways fall. The median 2D-to-3D reconstruction error was 1.02 mm for the shape and 0.06 g/cm³ for BMD for the 11 specimens. FE models derived from simulated DXAs predicted the outcome of the falls in terms of fracture versus non-fracture with the same accuracy as the CT-derived FE models. This study represents a milestone towards improved assessment of hip fracture risk based on widely available clinical DXA images.

Body Anthropometry and Bone Strength Conjointly Determine the Risk of Hip Fracture in a Sideways Fall

We hypothesize that variations of body anthropometry, conjointly with the bone strength, determine the risk of hip fracture. To test the hypothesis, we compared, in a simulated sideways fall, the hip impact energy to the energy needed to fracture the femur. Ten femurs from elderly donors were tested using a novel drop-tower protocol for replicating the hip fracture dynamics during a fall on the side. The impact energy was varied for each femur according to the donor’s body weight, height and soft-tissue thickness, by adjusting the drop height and mass. The fracture pattern, force, energy, strain in the superior femoral neck, bone morphology and microarchitecture were evaluated. Fracture patterns were consistent with clinically relevant hip fractures, and the superior neck strains and timings were comparable with the literature. The hip impact energy (11 – 95 J) and the fracture energy (11 – 39 J) ranges overlapped and showed comparable variance (CV = 69 and 61%, respectively). The aBMD-based definition of osteoporosis correctly classified 7 (70%) fracture/non-fracture cases. The incorrectly classified cases presented large impact energy variations, morphology variations and large subcortical voids as seen in microcomputed tomography. In conclusion, the risk of osteoporotic hip fracture in a sideways fall depends on both body anthropometry and bone strength.

Subject-specific FE models of the human femur predict fracture path and bone strength under single-leg-stance loading

Hip fractures are a major health problem with high socio-economic costs. Subject-specific finite element (FE) models have been suggested to improve the fracture risk assessment, as compared to clinical tools based on areal bone mineral density, by adding an estimate of bone strength. Typically, such FE models are limited to estimate bone strength and possibly the fracture onset, but do not model the fracture process itself. The aim of this study was to use a discrete damage approach to simulate the full fracture process in subject-specific femur models under stance loading conditions. A framework based on the partition of unity finite element method (PUFEM), also known as XFEM, was used. An existing PUFEM framework previously used on a homogeneous generic femur model was extended to include a heterogeneous material description together with a strain-based criterion for crack initiation. The model was tested on two femurs, previously mechanically tested in vitro. Our results illustrate the importance of implementing a subject-specific material distribution to capture the experimental fracture pattern under stance loading. Our models accurately predicted the fracture pattern and bone strength (1% and 5% error) in both investigated femurs. This is the first study to simulate complete fracture paths in subject-specific FE femur models and it demonstrated how discrete damage models can provide a more complete picture of fracture risk by considering both bone strength and fracture toughness in a subject-specific fashion.