A two-level subject-specific biomechanical model for improving prediction of hip fracture risk

Predicting population level hip fracture risk: a novel hierarchical model incorporating probabilistic approaches and factor of risk principles

Fall-related hip fractures are a major public health issue. While individual-level risk assessment tools exist, population-level predictive models could catalyze innovation in large-scale interventions. This study presents a hierarchical probabilistic model that predicts population-level hip fracture risk based on Factor of Risk (FOR) principles. Model validation demonstrated that FOR output aligned with a published dataset categorized by sex and hip fracture status. The model predicted normalized FOR for 100000 individuals simulating the Canadian older-adult population. Predicted hip fracture risk was higher for females (by an average of 38%), and increased with age (by15% per decade). Potential applications are discussed.

Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey

This paper provides a starting point for researchers and practitioners from biology, medicine, physics and engineering who can benefit from an up-to-date literature survey on patient-specific bone fracture modelling, simulation and risk analysis. This survey hints at a framework for devising realistic patient-specific bone fracture simulations. This paper has 18 sections: Section 1 presents the main interested parties; Section 2 explains the organzation of the text; Section 3 motivates further work on patient-specific bone fracture simulation; Section 4 motivates this survey; Section 5 concerns the collection of bibliographical references; Section 6 motivates the physico-mathematical approach to bone fracture; Section 7 presents the modelling of bone as a continuum; Section 8 categorizes the surveyed literature into a continuum mechanics framework; Section 9 concerns the computational modelling of bone geometry; Section 10 concerns the estimation of bone mechanical properties; Section 11 concerns the selection of boundary conditions representative of bone trauma; Section 12 concerns bone fracture simulation; Section 13 presents the multiscale structure of bone; Section 14 concerns the multiscale mathematical modelling of bone; Section 15 concerns the experimental validation of bone fracture simulations; Section 16 concerns bone fracture risk assessment. Lastly, glossaries for symbols, acronyms, and physico-mathematical terms are provided.

Subject-specific ex vivo simulations for hip fracture risk assessment in sideways falls

The risk of hip fracture of a patient due to a fall can be described from a mechanical perspective as the capacity of the femur to withstand the force that it experiences in the event of a fall. So far, impact forces acting on the lateral aspect of the pelvic region and femur strength have been investigated separately. This study used inertia-driven cadaveric impact experiments that mimic falls to the side from standing in order to evaluate the subject-specific force applied to the hip during impact and the fracture outcome in the same experimental model. Eleven fresh-frozen pelvis-femur constructs (6 female, 5 male, age = 77 years (SD = 13 years), BMI = 22.8 kg/m² (SD = 7.8 kg/m²), total hip aBMD = 0.734 g/cm² (SD = 0.149 g/cm²)), were embedded into soft tissue surrogate material that matched subject-specific mass and body shape. The specimens were attached to metallic lower-limb constructions with subject-specific masses and subjected to an inverted pendulum motion. Impact forces were recorded with a 6-axis force plate at 10,000 Hz and three dimensional deflections in the pelvic region were tracked with two high-speed cameras at 5000 Hz. Of the 11 specimens, 5 femur fractures and 3 pelvis fractures were observed. Three specimens did not fracture. aBMD alone did not reliably separate femur fractures from non-fractures. However, a mechanical risk ratio, which was calculated as the impact force divided by aBMD, classified specimens reliably into femur fractures and non-fractures. Single degree of freedom models, based on specimen kinetics, were able to predict subject-specific peak impact forces (RMSE = 2.55% for non-fractures). This study provides direct evidence relating subject-specific impact forces and subject-specific strength estimates and improves the assessment of the mechanical risk of hip fracture for a specific femur/pelvis combination in a sideways fall.

A multiscale model to predict current absolute risk of femoral fracture in a postmenopausal population

Osteoporotic hip fractures are a major healthcare problem. Fall severity and bone strength are important risk factors of hip fracture. This study aims to obtain a mechanistic explanation for fracture risk in dependence of these risk factors. A novel modelling approach is developed that combines models at different scales to overcome the challenge of a large space–time domain of interest and considers the variability of impact forces between potential falls in a subject. The multiscale model and its component models are verified with respect to numerical approximations made therein, the propagation of measurement uncertainties of model inputs is quantified, and model predictions are validated against experimental and clinical data. The main results are model predicted absolute risk of current fracture (ARF0) that ranged from 1.93 to 81.6% (median 36.1%) for subjects in a retrospective cohort of 98 postmenopausal British women (49 fracture cases and 49 controls); ARF0 was computed up to a precision of 1.92 percentage points (pp) due to numerical approximations made in the model; ARF0 possessed an uncertainty of 4.00 pp due to uncertainties in measuring model inputs; ARF0 classified observed fracture status in the above cohort with AUC = 0.852 (95% CI 0.753–0.918), 77.6% specificity (95% CI 63.4–86.5%) and 81.6% sensitivity (95% CI 68.3–91.1%). These results demonstrate that ARF0 can be computed using the model with sufficient precision to distinguish between subjects and that the novel mechanism of fracture risk determination based on fall dynamics, hip impact and bone strength can be considered validated.

On the internal reaction forces, energy absorption, and fracture in the hip during simulated sideways fall impact

The majority of hip fractures have been reported to occur as a result of a fall with impact to the greater trochanter of the femur. Recently, we developed a novel cadaveric pendulum-based hip impact model and tested two cadaveric femur-pelvis constructs, embedded in a soft tissue surrogate. The outcome was a femoral neck fracture in a male specimen while a female specimen had no fracture. The aim of the present study was, first, to develop a methodology for constructing and assessing the accuracy of explicit Finite Element Models (FEMs) for simulation of sideways falls to the hip based on the experimental model. Second, to use the FEMs for quantifying the internal reaction forces and energy absorption in the hip during impact. Third, to assess the potential of the FEMs in terms of separating a femoral fracture endpoint from a non-fracture endpoint. Using a non-linear, strain rate dependent, and heterogeneous material mapping strategy for bone tissue in these models, we found the FEM-derived results to closely match the experimental test results in terms of impact forces and displacements of pelvic video markers up to the time of peak impact force with errors below 10%. We found the internal reaction forces in the femoral neck on the impact side to be approximately 35% lower than the impact force measured between soft tissue and ground for both specimens. In addition, we found the soft tissue to be the component that absorbed the largest part of the energy of the tissue types in the hip region. Finally, we found surface strain patterns derived from FEM results to match the fracture location and extent based on post testing x-rays of the specimens. This is the first study with quantitative data on the energy absorption in the pelvic region during a sideways fall.

Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives

PURPOSE OF REVIEW

This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures.

RECENT FINDINGS

CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment. CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

A novel sideways fall simulator to study hip fractures ex vivo

Falls to the side are the leading cause of hip fractures in the elderly. The load that a person experiences during a fall cannot be measured with volunteers for ethical reasons. To evaluate injurious loads, while considering relevant energy input and body posture for a sideways fall, a subject-specific cadaveric impact experiment was developed. Full cadaveric femur-pelvis constructs (N = 2) were embedded in surrogate soft tissue material and attached to metallic surrogate lower limbs. The specimens were then subjected to an inverted pendulum motion, simulating a fall to the side with an impact to the greater trochanter. The load at the ground and the deformation of the pelvis were evaluated using a 6-axis force transducer and two high-speed cameras. Post-test, a trauma surgeon (PG) evaluated specimen injuries. Peak ground contact forces were 7132 N and 5641 N for the fractured and non-fractured specimen, respectively. We observed a cervical fracture of the femur in one specimen and no injuries in a second specimen, showing that the developed protocol can be used to differentiate between specimens at high and low fracture risk.

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.

Fatal falls in the elderly and the presence of proximal femur fractures

Fatal falls are frequent and seem to be an increasing problem in the elderly. Especially ground level falls (GLFs) and falls on or from stairs and steps (stairs falls) are worth examining for forensic classification and in order to improve the development of preventive measures. We retrospectively analyzed 261 fatal falls of elderly age 65 + years, which were autopsied at the Institute of Legal Medicine in Munich between 2008 and 2014. After careful screening, the sub-set of all 77 GLFs and 39 stairs falls were analyzed towards socio-demographic characteristics, fall circumstances, injuries, and circumstances of death. A subsequent analysis of GLF cases regarding the presence of proximal femur fractures (PFF) was performed. The injury pattern of the GLFs and the stairs falls clearly differ with a higher share of injuries to the lower extremities in the GLFs. However, the most severely injured body region was the head in both groups (62% of the stairs cases, 49% of the GLF cases). Alcohol as contributing to the fall was seen more frequently in the stairs falls. PFF were not seen in the stairs falls, but then in 18 GLF cases. Yet, for 17 among them (22% of 77), their hip fracture was the only serious injury leading to hospitalization and death. Only one GLF case was already found dead. This finding indicates a potential of avoiding up to 22% of the GLF fatalities by preventing hip fractures by optimized hip protectors or other measures, especially for the elderly aged 75 + years.

Comparison of non-invasive assessments of strength of the proximal femur

It is not clear which non-invasive method is most effective for predicting strength of the proximal femur in those at highest risk of fracture. The primary aim of this study was to compare the abilities of dual energy X-ray absorptiometry (DXA)-derived aBMD, quantitative computed tomography (QCT)-derived density and volume measures, and finite element analysis (FEA)-estimated strength to predict femoral failure load. We also evaluated the contribution of cortical and trabecular bone measurements to proximal femur strength. We obtained 76 human cadaveric proximal femurs (50 women and 26 men; age 74±8.8years), performed imaging with DXA and QCT, and mechanically tested the femurs to failure in a sideways fall configuration at a high loading rate. Linear regression analysis was used to construct the predictive model between imaging outcomes and experimentally-measured femoral strength for each method. To compare the performance of each method we used 3-fold cross validation repeated 10 times. The bone strength estimated by QCT-based FEA predicted femoral failure load (R²_adj=0.78, 95%CI 0.76-0.80; RMSE=896N, 95%CI 830-961) significantly better than femoral neck aBMD by DXA (R²_adj=0.69, 95%CI 0.66-0.72; RMSE=1011N, 95%CI 952-1069) and the QCT-based model (R²_adj=0.73, 95%CI 0.71-0.75; RMSE=932N, 95%CI 879-985). Both cortical and trabecular bone contribute to femoral strength, the contribution of cortical bone being higher in femurs with lower trabecular bone density. These findings have implications for optimizing clinical approaches to assess hip fracture risk. In addition, our findings provide new insights that will assist in interpretation of the effects of osteoporosis treatments that preferentially impact cortical versus trabecular bone.

Sideways fall-induced impact force and its effect on hip fracture risk: a review

Osteoporotic hip fracture, mostly induced in falls among the elderly, is a major health burden over the world. The impact force applied to the hip is an important factor in determining the risk of hip fracture. However, biomechanical researches have yielded conflicting conclusions about whether the fall-induced impact force can be accurately predicted by the available models. It also has been debated whether or not the effect of impact force has been considered appropriately in hip fracture risk assessment tools. This study aimed to provide a state-of-the-art review of the available methods for predicting the impact force, investigate their strengths/limitations, and suggest further improvements in modeling of human body falling.

METHODS

We divided the effective parameters on impact force to two categories: (1) the parameters that can be determined subject-specifically and (2) the parameters that may significantly vary from fall to fall for an individual and cannot be considered subject-specifically.

RESULTS

The parameters in the first category can be investigated in human body fall experiments. Video capture of real-life falls was reported as a valuable method to investigate the parameters in the second category that significantly affect the impact force and cannot be determined in human body fall experiments.

CONCLUSIONS

The analysis of the gathered data revealed that there is a need to develop modified biomechanical models for more accurate prediction of the impact force and appropriately adopt them in hip fracture risk assessment tools in order to achieve a better precision in identifying high-risk patients. Graphical abstract Impact force to the hip induced in sideways falls is affected by many parameters and may remarkably vary from subject to subject.

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

There is controversy about whether or not body parameters affect hip fracture in men and women in the same way. In addition, although bone mineral density (BMD) is currently the most important single discriminator of hip fracture, it is unclear if BMD alone is equally effective for men and women. The objective of this study was to quantify and compare the associations of hip fracture risk with BMD and body parameters in men and women using our recently developed two-level biomechanical model that combines a whole-body dynamics model with a proximal-femur finite element model. Sideways fall induced impact force of 130 Chinese clinical cases, including 50 males and 80 females, were determined by subject-specific dynamics modeling. Then, a DXA-based finite element model was used to simulate the femur bone under the fall-induced loading conditions and calculate the hip fracture risk. Body weight, body height, body mass index, trochanteric soft tissue thickness, and hip bone mineral density were determined for each subject and their associations with impact force and hip fracture risk were quantified. Results showed that the association between impact force and hip fracture risk was not strong enough in both men (r=-0.31,p<0.05) and women (r=0.42,p<0.001) to consider the force as a sole indicator of hip fracture risk. The correlation between hip BMD and hip fracture risk in men (r=-0.83,p<0.001) was notably stronger than that in women (r=-0.68,p<0.001). Increased body mass index was not a protective factor against hip fracture in men (r=-0.13,p>0.05), but it can be considered as a protective factor among women (r=-0.28,p<0.05). In contrast to men, trochanteric soft tissue thickness can be considered as a protective factor against hip fracture in women (r=-0.50,p<0.001). This study suggested that the biomechanical risk/protective factors for hip fracture are sex-specific. Therefore, the effect of body parameters should be considered differently for men and women in hip fracture risk assessment tools. These findings support further exploration of sex-specific preventive and protective measurements to reduce the incidence of hip fractures.

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

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