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Background: Metastatic femoral tumors may lead to pathological fractures during daily activities. A CT-based finite element analysis of a patient's femurs was shown to assist orthopedic surgeons in making informed decisions about the risk of fracture and the need for a prophylactic fixation. Improving the accuracy of such analyses ruqires an automatic and accurate segmentation of the tumors and their automatic inclusion in the finite element model. We present herein a deep learning algorithm (nnU-Net) to automatically segment lytic tumors within the femur., Method: A dataset consisting of fifty CT scans of patients with manually annotated femoral tumors was created. Forty of them, chosen randomly, were used for training the nnU-Net, while the remaining ten CT scans were used for testing. The deep learning model's performance was compared to two experienced radiologists., Findings: The proposed algorithm outperformed the current state-of-the-art solutions, achieving dice similarity scores of 0.67 and 0.68 on the test data when compared to two experienced radiologists, while the dice similarity score for inter-individual variability between the radiologists was 0.73., Interpretation: The automatic algorithm may segment lytic femoral tumors in CT scans as accurately as experienced radiologists with similar dice similarity scores. The influence of the realistic tumors inclusion in an autonomous finite element algorithm is presented in (Rachmil et al., "The Influence of Femoral Lytic Tumors Segmentation on Autonomous Finite Element Analyses", Clinical Biomechanics, 112, paper 106192, (2024))., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: The validated CT-based autonomous finite element system Simfini (Yosibash et al., 2020) is used in clinical practice to assist orthopedic oncologists in determining the risk of pathological femoral fractures due to metastatic tumors. The finite element models are created automatically from CT-scans, assigning to lytic tumors a relatively low stiffness as if these were a low-density bone tissue because the tumors could not be automatically identified., Methods: The newly developed automatic deep learning algorithm which segments lytic tumors in femurs, presented in (Rachmil et al., 2023), was integrated into Simfini. Finite element models of twenty femurs from ten CT-scans of patients with femoral lytic tumors were analyzed three times using: the original methodology without tumor segmentation, manual segmentation of the lytic tumors, and the new automatic segmentation deep learning algorithm to identify lytic tumors. The influence of explicitly incorporating tumors in the autonomous finite element analysis on computed principal strains is quantified. These serve as an indicator of femoral fracture and are therefore of clinical significance., Findings: Autonomous finite element models with segmented lytic tumors had generally larger strains in regions affected by the tumor. The deep learning and manual segmentation of tumors resulted in similar average principal strains in 19 regions out of the 23 regions within 15 femurs with lytic tumors. A high dice similarity score of the automatic deep learning tumor segmentation did not necessarily correspond to minor differences compared to manual segmentation., Interpretation: Automatic tumor segmentation by deep learning allows their incorporation into an autonomous finite element system, resulting generally in elevated averaged principal strains that may better predict pathological femoral fractures., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Autonomous finite element analyses (AFE) based on CT scans predict the biomechanical response of femurs during stance and sidewise fall positions. We combine AFE with patient data via a machine learning (ML) algorithm to predict the risk of hip fracture. An opportunistic retrospective clinical study of CT scans is presented, aimed at developing a ML algorithm with AFE for hip fracture risk assessment in type 2 diabetic mellitus (T2DM) and non-T2DM patients. Abdominal/pelvis CT scans of patients who experienced a hip fracture within 2 years after an index CT scan were retrieved from a tertiary medical center database. A control group of patients without a known hip fracture for at least 5 years after an index CT scan was retrieved. Scans belonging to patients with/without T2DM were identified from coded diagnoses. All femurs underwent an AFE under three physiological loads. AFE results, patient's age, weight, and height were input to the ML algorithm (support vector machine [SVM]), trained by 80% of the known fracture outcomes, with cross-validation, and verified by the other 20%. In total, 45% of available abdominal/pelvic CT scans were appropriate for AFE (at least 1/4 of the proximal femur was visible in the scan). The AFE success rate in automatically analyzing CT scans was 91%: 836 femurs we successfully analyzed, and the results were processed by the SVM algorithm. A total of 282 T2DM femurs (118 intact and 164 fractured) and 554 non-T2DM (314 intact and 240 fractured) were identified. Among T2DM patients, the outcome was: Sensitivity 92%, Specificity 88% (cross-validation area under the curve [AUC] 0.92) and for the non-T2DM patients: Sensitivity 83%, Specificity 84% (cross-validation AUC 0.84). Combining AFE data with a ML algorithm provides an unprecedented prediction accuracy for the risk of hip fracture in T2DM and non-T2DM populations. The fully autonomous algorithm can be applied as an opportunistic process for hip fracture risk assessment. © 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)., (© 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).)

Background: Patient-specific autonomous finite element analyses of femurs, based on clinical computed tomography scans may be used to monitor the progression of bone-related diseases. Some CT scan protocols provide lower resolution (slice thickness of 3 mm) that affects the accuracy. To investigate the impact of low-resolution scans on the CT-based finite element analyses results, identical CT raw data were reconstructed twice to generate a 1 mm ("gold standard") and a 3 mm slice thickness scans., Methods: CT-based finite element analyses of twenty-four femurs (twelve patients) under stance and sideways fall loads were performed based on 1 and 3 mm slice thickness scans. Bone volume, load direction, and strains were extracted at different locations along the femurs and differences were evaluated., Findings: Average differences in bone volume were 1.0 ± 1.5%. The largest average difference in strains in stance position was in the neck region (11.0 ± 13.4%), whereas in other regions these were much smaller. For sidewise fall loading, the average differences were at most 9.2 ± 16.0%., Interpretation: Whole-body low dose CT scans (3 mm-slice thickness) are suboptimal for monitoring strain changes in patient's femurs but may allow longitudinal studies if larger than 5% in all areas and larger than 12% in the upper neck. CT-based finite element analyses with slice thickness of 3 mm may be used in clinical practice for patients with smoldering myeloma to associate changes in strains with progression to active myeloma if above ∼10%., Competing Interests: Declaration of Competing Interest None of the authors have any conflict of interest to declare that could bias the presented work. ZY has financial interest in PerSimiO Ltd., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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.)

Aims: Type 2 diabetes mellitus (T2DM) impairs bone strength and is a significant risk factor for hip fracture, yet currently there is no reliable tool to assess this risk. Most risk stratification methods rely on bone mineral density, which is not impaired by diabetes, rendering current tests ineffective. CT-based finite element analysis (CTFEA) calculates the mechanical response of bone to load and uses the yield strain, which is reduced in T2DM patients, to measure bone strength. The purpose of this feasibility study was to examine whether CTFEA could be used to assess the hip fracture risk for T2DM patients., Methods: A retrospective cohort study was undertaken using autonomous CTFEA performed on existing abdominal or pelvic CT data comparing two groups of T2DM patients: a study group of 27 patients who had sustained a hip fracture within the year following the CT scan and a control group of 24 patients who did not have a hip fracture within one year. The main outcome of the CTFEA is a novel measure of hip bone strength termed the Hip Strength Score (HSS)., Results: The HSS was significantly lower in the study group (1.76 (SD 0.46)) than in the control group (2.31 (SD 0.74); p = 0.002). A multivariate model showed the odds of having a hip fracture were 17 times greater in patients who had an HSS ≤ 2.2. The CTFEA has a sensitivity of 89%, a specificity of 76%, and an area under the curve of 0.90., Conclusion: This preliminary study demonstrates the feasibility of using a CTFEA-based bone strength parameter to assess hip fracture risk in a population of T2DM patients. Cite this article: Bone Joint J  2021;103-B(9):1497-1504.

Background: Most benign active and latent lesions of proximal femur do not predispose a patient to a pathologic fracture. Nonetheless, there is a tendency to perform internal fixation due to the lack of accurate clinical tools that may reliably confirm low risk of pathologic fracture. As many as 30% of these surgeries may be unnecessary. A patient-specific CT-based finite element analysis may quantify bone strength and risk of fracture under normal weight-bearing conditions., Methods: The clinical relevance of such finite element analysis was investigated in a retrospective study on a cohort of 17 patients. Finite element analysis results (high risk = indication for surgery, low or moderate risk = follow-up) were compared to actual clinical decisions (surgery vs follow-up). All patients predicted by the finite element analysis as high risk underwent internal fixation and had good outcomes (n = 6)., Findings: Four of the 11 low- and moderate-risk finite element analysis patients (36%) were operated immediately, and seven (64%) were either operated after a delay of at least 6 months or were never operated. None sustained a pathologic fracture. Patients who were predicted as low fracture risk by finite element analysis remained fracture-free for a minimal period of 6 months. Prediction of high risk of pathologic fracture by finite element analysis was in complete agreement with the conventional clinical evaluation., Interpretation: We consider finite element analysis a promising decision support system for the management of patients with benign tumors of femur, and that it may reliably endorse the decision to withhold surgery for patients at low fracture-risk., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Long-term survival of hip implants is of increasing relevance due to the rising life expectancy. The biomechanical effect of strain shielding as a result of implant insertion may lead to bone resorption, thus increasing risk for implant loosening and periprosthetic fractures. Patient-specific quantification of strain shielding could assist orthopedic surgeons in choosing the biomechanically most appropriate prosthesis., Methods: Validated quantitative CT-based finite element models of five femurs in intact and implanted states were considered to propose a systematic algorithm for strain shielding quantification. Three different strain measures were investigated and the most appropriate measure for strain shielding quantification is recommended. It is used to demonstrate a practical femur-specific implant selection among three common designs., Findings: Strain shielding measures demonstrated similar trends in all Gruen zones except zone 1, where the volumetric strain measure differed from von-Mises and maximum principal strains. The volumetric strain measure is in better agreement with clinical bone resorption records. It is also consistent with the biological mechanism of bone remodeling so it is recommended for strain shielding quantification. Applying the strain shielding algorithm on three different implants for a specific femur suggests that the collared design is preferable. Such quantitative biomechanical input is valuable for practical patient specific implant selection., Interpretation: Volumetric strain should be considered for strain shielding examination. The presented methodology may potentially enable patient-specific pre-operative strain shielding evaluation so to minimize strain shielding. It should be further used in a longitudinal study so to correlate between strain shielding predictions and clinical bone resorption., Competing Interests: Declaration of Competing Interest YK, NS, MS have no conflicts of interest to declare. ZY has a financial interest in PerSimiO., (Copyright © 2020 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.)

Background: Proximal humerus fractures which occur as a result of a fall on an outstretched arm are frequent among the elderly population. The necessity of stabilizing such fractures by surgical procedures is a controversial matter among surgeons. Validating a personalized FE analysis by ex-vivo experiments of humeri and mimicking such fractures by experiments is the first step along the path to determine the necessity of such surgeries., Methods: Four fresh frozen human humeri were loaded using a new simple experimental setting, so to fracture the humeri at the anatomical neck. Strains on humeri's surfaces predicted by the high order FE analyses (as in Dahan et al., 2016) were compared to the experimental observations to further enhance the validity of the FE analyses. A simplified yield criterion based on a linear elastic analysis and principal strains was used to predict the anatomical neck fracture as observed in the experiment., Findings: An excellent correlation between experimental measured and FE predicted strains was obtained (slope of 0.99 and R 2 =0.98). All humeri were fractured at the anatomical neck. The predicted yield load was within 10%-20% accuracy., Interpretation: High-order FE analyses reliably predict strains and yield loads in the humeri. Fractures induced by the experimental setting correspond to anatomical neck fractures noticed in practice and classified as AO C1.1-C1.3. Surgical neck fractures, which are most common in clinical practice, could not be realized in the proposed experiments, and a different experimental setting should be sought to obtain them ex-vivo., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

A proximal humerus fracture is an injury to the shoulder joint that necessitates medical attention. While it is one of the most common fracture injuries impacting the elder community and those who suffer from traumatic falls or forceful collisions, there are almost no validated computational methods that can accurately model these fractures. This could be due to the complex, inhomogeneous bone microstructure, complex geometries, and the limitations of current fracture mechanics methods. In this paper, we develop a novel phase field method to investigate the proximal humerus fracture. To model the fracture in the inhomogeneous domain, we propose a power-law relationship between bone mineral density and critical energy release rate. The method is validated by an in vitro experiment, in which a human humerus is constrained on both ends while subjected to compressive loads on its head, in the longitudinal direction, that lead to fracture at the anatomical neck. CT scans are employed to acquire the bone geometry and material parameters, from which detailed finite element meshes with inhomogeneous Young modulus distributions are generated. The numerical method, implemented in a high performance computing environment, is used to quantitatively predict the complex 3D brittle fracture of the bone and is shown to be in good agreement with experimental observations. Furthermore, our findings show that the damage is initiated in the trabecular bone-head and propagates outward towards the bone cortex. We conclude that the proposed phase field method is a promising approach to model bone fracture., (© 2019 John Wiley & Sons, Ltd.)

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: Over 1.6 million hip replacements are performed annually in Organisation for Economic Cooperation and Development countries, half of which involve cemented implants. Quantitative computer tomography based finite element methods may be used to assess the change in strain field in a femur following such a hip replacement, and thus determine a patient-specific optimal implant. A combined experimental-computational study on fresh frozen human femurs with different cemented implants is documented, aimed at verifying and validating the methods., Methods: Ex-vivo experiments on four fresh-frozen human femurs were conducted. Femurs were scanned, fractured in a stance position loading, and thereafter implanted with four different prostheses. All femurs were reloaded in stance positions at three different inclination angles while recording strains on bones' and prosthesis' surfaces. High-order FE models of the intact and implanted femurs were generated based on the computer tomography scans and X-ray radiographs. The models were virtually loaded mimicking the experimental conditions and FE results were compared to experimental observations., Findings: Strains predicted by finite element analyses in all four femurs were in excellent correlation with experimental observations FE = 1.01 × EXP - 0.07,R 2  = 0.976, independent of implant's type, loading angle and fracture location., Interpretation: Computer tomography based finite element models can reliably determine strains on femur surface and on inserted implants at the contact with the cement. This allows to investigate suitable norms to rank implants for a patient-specific femur so to minimize changes in strain patterns in the operated femur., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Physician recommendation for prophylactic surgical fixation of a femur with metastatic bone disease (MBD) is usually based on Mirels' criteria and clinical experience, both of which suffer from poor specificity. This may result in a significant number of these health compromised patients undergoing unnecessary surgery. CT-based finite element analyses (CTFEA) have been shown to accurately predict strength in femurs with metastatic tumors in an ex-vivo study. In order to assess the utility of CTFEA as a clinical tool to determine the need for fixation of patients with MBD of the femur, an ad hoc CTFEA was performed on a retrospective cohort of fifty patients. Patients with CT scans appropriate for CTFEA analysis were analyzed. Group 1 was composed of 5 MBD patients who presented with a pathologic femoral fracture and had a scan of their femurs just prior to fracture. Group 2 was composed of 45 MBD patients who were scheduled for a prophylactic surgery because of an impending femoral fracture. CTFEA models were constructed for both femurs for all patients, loaded with a hip contact force representing stance position loading accounting for the patient's weight and femur anatomy. CTFEA analysis of Group 1 patients revealed that they all had higher tumor associated strains compared to typical non-diseased femur bone strains at the same region (>45%). Based on analysis of the 5 patients in Group 1, the ratio between the absolute maximum principal strain in the vicinity of the tumor and the typical median strain in the region of the tumor of healthy bones (typical strain fold ratio) was found to be the 1.48. This was considered to be the predictive threshold for a pathological femoral fracture. Based on this typical strain fold ratio, twenty patients (44.4%) in Group 2 were at low risk of fracture and twenty-five patients (55.5%) high risk of fracture. Eleven patients in Group 2 choose not to have surgery and none fractured in the 5month follow-up period. CTFEA predicted that seven of these patients were below the pathological fracture threshold and four above, for a specificity of 63% Based on CTFEA, 39% of the patients with femoral MBD who were referred and underwent prophylactic stabilization may not have needed surgery. These results indicate that a prospective randomized clinical trial evaluating CTFEA as a criterion for determining the need for surgical stabilization in patients with MBD of the femur may be warranted., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The voxel finite cell method uses unfitted finite element meshes and voxel quadrature rules to seamlessly transfer computed tomography data into patient-specific bone discretizations. The method, however, still requires the explicit parametrization of boundary surfaces to impose traction and displacement boundary conditions, which constitutes a potential roadblock to automation. We explore a phase-field-based formulation for imposing traction and displacement constraints in a diffuse sense. Its essential component is a diffuse geometry model generated from metastable phase-field solutions of the Allen-Cahn problem that assumes the imaging data as initial condition. Phase-field approximations of the boundary and its gradient are then used to transfer all boundary terms in the variational formulation into volumetric terms. We show that in the context of the voxel finite cell method, diffuse boundary conditions achieve the same accuracy as boundary conditions defined over explicit sharp surfaces, if the inherent length scales, ie, the interface width of the phase field, the voxel spacing, and the mesh size, are properly related. We demonstrate the flexibility of the new method by analyzing stresses in a human femur and a vertebral body., (Copyright © 2017 John Wiley & Sons, Ltd.)

Further experimental evidence on the compressibility of arteries under normal physiological pressure range is provided using the experimental apparatus introduced in Yosibash et al., JMBBM 39(2014):339-354. We enlarged the experimental database by including almost twice the number of experiments, we considered a different artery - the porcine common carotid that allowed longer and larger diameters. In the physiological pressure range of 50-200mmHg, a relative volume change of 5% was obtained, lower compared to the sapheneous and femoral arteries (2-6%). Most of the arteries had a relative volume change of 1.5%. The relative volume change is found to be almost linearly proportional to the pressure, and inversely proportional to the dimensions of the experimented arteries (especially the artery length). The smaller the artery tested, the larger the relative volume change (such a phenomenon was also realized in Yosibash et al., JMBBM 39(2014):339-354.). We realized in recent past publications a flaw in the experimental protocol that results in an overestimation of the relative volume change (thus underestimating the bulk modulus). It is due to the consideration of experimental observations close to the zero pressure. Nontheless, in view of the experimental evidence, the pre-assumption of incompressibility in many phenomenological constitutive models of artery walls should be re-evaluated., (Copyright © 2016 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.)