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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, R 2 =0.99) and a fair agreement (slope 0.807, R 2 =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., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Finite element analyses (FEAs) of human femurs are mostly validated by ex-vivo experimental observations. Such validations were largely performed by comparing local strains at a small subset of points to the gold standard strain gauge (SG) measurements. A comprehensive full field validation of femoral FEAs including both strains and displacements using digital image correlation (DIC) full field measurements, especially at medial and lateral surfaces of the neck that experience the highest strains, provide new insights on femurs' mechanical behavior. Five cadaver femurs were loaded in stance position and monitored at the shaft and neck using two DIC systems simultaneously. DIC strains were compared to SG measurements at a limited number of locations so to corroborate DIC measurements by the gold standard technique. These were used to quantitatively assess the validity of FEA strains prediction especially at the neck where fracture usually occurs. Strains measured by DIC correspond well to the SG observations. An excellent agreement was observed between DIC and FEA predicted strains excluding the superior neck surface: FE=1.02×DIC-17,r 2 =0.977. At the superior neck however, strains were not well predicted by FEA models: Although the FEA predicted high strains at the 'saddle region', these were not observed experimentally. On the other hand, strain concentrations were measured by DIC at numerous vessel holes which were not represented by FE models. Since fractures usually initiate at the subcapital region in stance position ex-vivo experiments, where numerus vessel holes exist, these vessel holes may be required to be accounted for in future FE models so to allow a better estimation of the fracture load. Full field measurements are mandatory to allow a better validation of fracture load and location predictions which are of high clinical importance., Competing Interests: Declaration of Competing Interest YK has no conflicts of interest. ZY has a financial interest in PerSimiO., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Patient-specific QCT-based finite element (QCTFE) analyses enable highly accurate quantification of bone strength. We evaluated CT scanner influence on QCTFE models of long bones. A femur, humerus, and proximal femur without the head were scanned with K 2 HPO 4 phantoms by seven CT scanners (four models) using typical clinical protocols. QCTFE models were constructed. The geometrical dimensions, as well as the QCT-values expressed in Hounsfield unit (HU) distribution was compared. Principal strains at representative regions of interest (ROIs), and maximum principal strains (associated with fracture risk) were compared. Intraclass correlation coefficients (ICCs) were calculated to evaluate strain prediction reliability for different scanners. Repeatability was examined by scanning the femur twice and comparing resulting QCTFE models. Maximum difference in geometry was 2.3%. HU histograms before phantom calibration showed wide variation between QCT scans; however, bone density histogram variability was reduced after calibration and algorithmic manipulation. Relative standard deviation (RSD) in principal strains at ROIs was <10.7%. ICC estimates between scanners were >0.9. Fracture-associated strain had 6.7%, 8.1%, and 13.3% maximum RSD for the femur, humerus, and proximal femur, respectively. The difference in maximum strain location was <2 mm. The average difference with repeat scans was 2.7%. Quantification of strain differences showed mean RSD bounded by ∼6% in ROIs. Fracture-associated strains in "regular" bones showed a mean RSD bounded by ∼8%. Strains were obtained within a ±10% difference relative to the mean; thus, in a longitudinal study only changes larger than 20% in the principal strains may be significant. ICCs indicated high reliability of QCTFE models derived from different scanners., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Although ~200,000 emergency room visits per year in the US alone are associated with fractures of the proximal humerus, only limited studies exist on their mechanical response. We hypothesise that for the proximal humeri (a) the mechanical response can be well predicted by using inhomogeneous isotropic material properties, (b) the relation between bone elastic modulus and ash density (E(ρash)) is similar for the humerus and the femur, and may be general for long bones, and (c) it is possible to replicate a proximal humerus fracture in vitro by applying uniaxial compression on humerus׳ head at a prescribed angle., Methods: Four fresh frozen proximal humeri were CT-scanned, instrumented by strain-gauges and loaded at three inclination angles. Thereafter head displacement was applied to obtain a fracture. CT-based high order (p-) finite element (FE) and classical (h-) FE analyses were performed that mimic the experiments and predicted strains were compared to the experimental observations., Results: The E(ρash) relationship appropriate for the femur is equally appropriate for the humeri: predicted strains in the elastic range showed an excellent agreement with experimental observations with a linear regression slope of m=1.09 and a coefficient of regression R(2)=0.98. p-FE and h-FE results were similar for the linear elastic response. Although fractures of the proximal humeri were realised in the in vitro experiments, the contact FE analyses (FEA) were unsuccessful in representing properly the experimental boundary conditions., Discussion: The three hypotheses were confirmed and the linear elastic response of the proximal humerus, attributed to a stage at which the cortex bone is intact, was well predicted by the FEA. Due to a large post-elastic behaviour following the cortex fracture, a new non-linear constitutive model for proximal humerus needs to be incorporated into the FEA to well represent proximal humerus fractures. Thereafter, more in vitro experiments are to be performed, under boundary conditions that may be well represented by the FEA, to allow a reliable simulation of the fracture process., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Computational models for the personalized analysis of human femurs contain uncertainties in bone material properties and loads, which affect the simulation results. To quantify the influence we developed a probabilistic framework based on polynomial chaos (PC) that propagates stochastic input variables through any computational model. We considered a stochastic E-ρ relationship and a stochastic hip contact force, representing realistic variability of experimental data. Their influence on the prediction of principal strains (ϵ1 and ϵ3) was quantified for one human proximal femur, including sensitivity and reliability analysis. Large variabilities in the principal strain predictions were found in the cortical shell of the femoral neck, with coefficients of variation of ≈40%. Between 60 and 80% of the variance in ϵ1 and ϵ3 are attributable to the uncertainty in the E-ρ relationship, while ≈10% are caused by the load magnitude and 5-30% by the load direction. Principal strain directions were unaffected by material and loading uncertainties. The antero-superior and medial inferior sides of the neck exhibited the largest probabilities for tensile and compression failure, however all were very small (pf<0.001). In summary, uncertainty quantification with PC has been demonstrated to efficiently and accurately describe the influence of very different stochastic inputs, which increases the credibility and explanatory power of personalized analyses of human proximal femurs., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Uncertainty quantification for the response of a patient specific femur is mandatory when advocating finite element (FE) models in clinical applications. Reliable stochastic descriptions of physiological hip contact forces are an essential prerequisite for such an endeavor. We therefore analyze the in-vivo available data of seven individuals from HIP98 and OrthoLoad with the objective of characterizing the variability of the peak hip contact force magnitude and two corresponding spatial angles (in sagittal and frontal plane) during walking free and going upstairs. Regression analyses with linear mixed-effects models were performed resulting in six normal random variables, one for each force component and activity. Importantly, the statistical analysis accounts for the fact that same individuals performed both activities. The mean of the peak force magnitude was found to be linearly dependent on the body weight with an additional, activity-specific intercept and all variances were dominated by the inter-patient variability. No distinct correlation was found between the two angles and the force magnitude. The proposed stochastic description of the peak hip contact force during walking free and going upstairs contributes towards future uncertainty quantification of patient-specific FE models., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

A mandatory requirement for any reliable prediction of the mechanical response of bones, based on quantitative computer tomography, is an accurate relationship between material properties (usually Young's modulus E) and bone density ρ. Many such E-ρ relationships are available based on different experiments on femur specimens with a large spread due to uncertainties. The first goal of this study is to pool and analyze the relevant available experimental data and develop a stochasticE-ρ relationship. This analysis highlights that there is no experimental data available to cover the entire density range of the human femur and that some "popular" E-ρ relationships are based on data that contains extreme scatter, while others are based on a very limited amount of information. The second goal is to use the newly developed stochastic E-ρ relationship in high-order finite element analyses (FEAs) for the computation of strains and displacements in two human proximal femurs, mimicking in vitro experiments. When compared with the experimental observations, the FEA predictions using the median of the stochastic E-ρ relationship follow the underlying distribution of the stochastic E-ρ relationship. Thus, most deviations of the FEA predictions from experimental observations can possibly be explained by uncertain elastic properties of the femur., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Patient-specific finite element (PSFE) models based on quantitative computer tomography (qCT) are generally used to "predict" the biomechanical response of human bones with the future goal to be applied in clinical decision-making. However, clinical applications require a well validated tool that is free of numerical errors and furthermore match closely experimental findings. In previous studies, not all measurable data (strains and displacements) were considered for validation. Furthermore, the same research group performed both the experiments and PSFE analyses; thus, the validation may have been biased. The aim of the present study was therefore to validate PSFE models with biomechanical experiments, and to address the above-mentioned issues of measurable data and validation bias. A PSFE model (p-method) of each cadaver femur (n = 12) was generated based on qCT scans of the specimens. The models were validated by biomechanical in-vitro experiments, which determined strains and local displacements on the bone surface and the axial stiffness of the specimens. The validation was performed in a double-blinded manner by two different research institutes to avoid any bias. Inspecting all measurements (155 values), the numerical results correlated well with the experimental results (R(2) = 0.93, slope 1.0093, mean of absolute deviations 22%). In conclusion, a method to generate PSFE models from qCT scans was used in this study on a sample size not yet considered in the past, and compared to experiments in a douple-blinded manner. The results demonstrate that the presented method is in an advanced stage, and can be used in clinical computer-aided decision-making., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Background: The use of subject-specific finite element (FE) models in clinical practice requires a high level of automation and validation. In Yosibash et al. [2007a. Reliable simulations of the human proximal femur by high-order finite element analysis validated by experimental observations. J. Biomechanics 40, 3688-3699] a novel method for generating high-order finite element (p-FE) models from CT scans was presented and validated by experimental observations on two fresh frozen femurs (harvested from a 30 year old male and 21 year old female). Herein, we substantiate the validation process by enlarging the experimental database (54 year old female femur), improving the method and examine its robustness under different CT scan conditions., Approach: A fresh frozen femur of a 54 year old female was scanned under two different environments: in air and immersed in water (dry and wet CT). Thereafter, the proximal femur was quasi-statically loaded in vitro by a 1000N load. The two QCT scans were manipulated to generate p-FE models that mimic the experimental conditions. We compared p-FE displacements and strains of the wet CT model to the dry CT model and to the experimental results. In addition, the material assignment strategy was reinvestigated. The inhomogeneous Young's modulus was represented in the FE model using two different methods, directly extracted from the CT data and using continuous spatial functions as in Yosibash et al. [2007a. Reliable simulations of the human proximal femur by high-order finite element analysis validated by experimental observations. J. Biomechanics 40, 3688-3699]., Results: Excellent agreement between dry and wet FE models was found for both displacements and strains, i.e. the method is insensitive to CT conditions and may be used in vivo. Good agreement was also found between FE results and experimental observations. The spatial functions representing Young's modulus are local and do not influence strains and displacements prediction. Finally, the p-FE results of all three fresh frozen human femurs compare very well to experimental observations exemplifying that the presented method may be in a mature stage to be used in clinical computer-aided decision making.

Background: The mechanical response of patient-specific bone to various load conditions is of major clinical importance in orthopedics. Herein we enhance the methods presented in Yosibash et al. [2007. A CT-based high-order finite element analysis of the human proximal femur compared to in-vitro experiments. ASME Journal of Biomechanical Engineering 129(3), 297-309.] for the reliable simulations of the human proximal femur by high-order finite elements (FEs) and validate the simulations by experimental observations., Method of Approach: A fresh-frozen human femur was scanned by quantitative computed tomography (QCT) and thereafter loaded (in vitro experiments) by a quasi-static force of up to 1250 N. QCT scans were manipulated to generate a high-order FE bone model with distinct cortical and trabecular regions having inhomogeneous isotropic elastic properties with Young's modulus represented by continuous spatial functions. Sensitivity analyses were performed to quantify parameters that mostly influence the mechanical response. FE results were compared to displacements and strains measured in the experiments., Results: Young moduli correlated to QCT Hounsfield Units by relations in Keyak and Falkinstein [2003. Comparison of in situ and in vitro CT scan-based finite element model predictions of proximal femoral fracture load. Medical Engineering and Physics 25, 781-787.] were found to provide predictions that match the experimental results closely. Excellent agreement was found for both the displacements and strains. The presented study demonstrates that reliable and validated high-order patient-specific FE simulations of human femurs based on QCT data are achievable for clinical computer-aided decision making.