An open source software tool to assign the material properties of bone for ABAQUS finite element simulations

A new software tool to assign the material properties of bone to an ABAQUS finite element mesh was created and compared with Bonemat, a similar tool originally designed to work with Ansys finite element models. Our software tool (py_bonemat_abaqus) was written in Python, which is the chosen scripting language for ABAQUS. The purpose of this study was to compare the software packages in terms of the material assignment calculation and processing speed. Three element types were compared (linear hexahedral (C3D8), linear tetrahedral (C3D4) and quadratic tetrahedral elements (C3D10)), both individually and as part of a mesh. Comparisons were made using a CT scan of a hemi-pelvis as a test case. A small difference, of -0.05 kPa on average, was found between Bonemat version 3.1 (the current version) and our python package. Errors were found in the previous release of Bonemat (version 3.0 downloaded from www.biomedtown.org) during calculation of the quadratic tetrahedron Jacobian, and conversion of the apparent density to modulus when integrating over the Young’s modulus field. These issues caused up to 2 GPa error in the modulus assignment. For these reasons, we recommend users upgrade to the most recent release of Bonemat. Processing speeds were assessed for the three different element types. Our Python package took significantly longer (110 s on average) to perform the calculations compared with the Bonemat software (10 s). Nevertheless, the workflow advantages of the package and added functionality makes ‘py_bonemat_abaqus’ a useful tool for ABAQUS users

A Python Package to Assign Material Properties of Bone to Finite Element Models from within Abaqus Software

Introduction: Using Python scripting it is possible to automate the pre-processing, solving and post-processing stages of finite element analysis using ABAQUS software. This is particularly useful when running multiple models parametrically. When the model involves a bony part, it is necessary to assign material properties based on the CT scan to represent bone heterogeneity, and unfortunately this cannot currently be done from within ABAQUS using software such as Bonemat [1]. To address this issue a Python package was written called 'py_bonemat_abaqus' to assign material properties from within ABAQUS. The purpose of this study was to compare the material assignments of py_bonemat_abaqus and Bonemat, to compare the processing speed, and to describe the workflow.Materials & Methods: The software packages were compared using a CT scan of a half pelvis downloaded from the VAKHUM database, and the associated hexahedral finite element mesh of the left half pelvis. To examine different element types, the hexahedral mesh was converted to linear and quadratic tetrahedral elements by dividing each hexahedron into 5 tetrahedral elements. The equations used to convert the Hounsfield Unit (HU) values to apparent density (papp), and to convert the apparent density to elastic modulus (E) are shown in Equations 1&2 [2].    Equation 1: papp = -0.021075 + 0.000786 HU    Equation 2: E = 2.0173 papp 2.46The time taken to analyse the models by each software was assessed using a Windows 7 PC with a 64-bit operating system, 4 CPUS, 8 GB of RAM and an Intel Core I5-3470 processor.Results: The mean difference between the moduulus assignment made by py_bonemat_abaqus and Bonemat was -0.05 kPa (range -10.19 to 4.50 kPa, standard deviation 0.62 kPa). The Python package took a similar time to run for all element types; this was between 109 and 126 s. Bonemat software was significantly faster, and took between 5 and 20 s. Finally, the Python package was successfully used from within a Python script to perform material assignment from within ABAQUS software in a fully automated manner.Discussion: Material assignments were almost equivalent between the two software packages, with any differences explainable by rounding effects. To put the differences into context, a difference of -0.05 kPa is 0.00000002% of the typical modulus of cortical bone (20.7 GPa), and 0.00000003% of the modulus of trabecular bone (14.8 GPa) [3]. The Python package was slower to process the models, but was successfully able to assign material properties from within ABAQUS software as part of an automated script. References: [1] Taddei, F. et al. “The material mapping strategy influences the accuracy of CT-based finite element models of bones: An evaluation against experimental measurements” (2007) Med Eng Phys 29, p973-979.[2] Anderson, A.E. et al. “Subject-Specific Finite Element Model of the Pelvis: Development, Validation and Sensitivity Studies” (2005) J Biomech Eng 127, p364-373.[3] Rho, J.Y. et al. “Young's modulus of trabecular and cortical bone material: ultrasonic and microtensile measurements.” (1993) J Biomech 26 p111-11

Topographical and chemical effects of electrochemically assisted deposited hydroxyapatite coatings on osteoblast-like cells

A recently commercialised hydroxyapatite electrochemically assisted chemical deposition technique (BoneMaster) has been shown to induce increased bone apposition; whether this response is caused by the surface topography or chemistry is unknown. An in-vitro examination using human osteoblast-like cells was performed on a series of BoneMaster-coated surfaces. The chemistry was separated from the topography using a thin gold coating; Thermanox coverslips were used as a control. BoneMaster surfaces showed significantly greater alkaline phosphatase activity and osteocalcin production compared with controls; however, no difference was found between the gold-coated and uncoated BoneMaster samples, indicating topography is the main contributing factor

Does surgical treatment of femoral neck fracture increase the risk of femoral head collapse?

Introduction: Femoral head collapse is a possible complication after surgical treatment of femoral neck fractures. The purpose of this study was to examine whether implantation of a Sliding Hip Screw (SHS) or an X-Bolt could increase the risk of femoral head collapse. Similar to traditional hip screws, the X-Bolt is implanted through the femoral neck; however, it uses an expanding cross-shape to improve rotational stability. The risk of collapse was investigated alongside patient factors, such as osteonecrosis.Materials & Methods: This numerical study assessed the risk of femoral head collapse using linear eigenvalue buckling (an established method [1]), and also from the maximum von Mises stress within the cortical bone. The femoral head was loaded using the pressures reported by Yoshida et al. for a patient sitting down (reported to put the femoral head at greatest risk of collapse [2]), with a peak pressure of 9.4 MPa and an average pressure of 1.59 MPa. The femur was fixed in all degrees of freedom at a plane through the femoral neck. The X-Bolt and SHS were implanted in accordance with the operative techniques. The femoral head and implants were meshed with quadratic tetrahedral elements, and cortical bone was meshed with triangular thin shell elements. A converged mesh seeding density of 1.2 mm was used. All models were create and solved using ABAQUS finite element software (version 6.12, Simulia, Dassault Systèmes, France). The influence of implant type and presence was examined alongside a variety of patient factors: osteonecrosis (modelled as a cone of bone of varying angle, and varying modulus values), cortical thinning, reduced cortical modulus, and femoral head size. Twenty-two finite element models were run for each implant condition (intact; implanted with the X-Bolt; implanted with a SHS), resulting in a total of 66 models. The finite element models were validated using experimental tests performed on five 4th generation composite Sawbones femurs (Malmö, Sweden), and verified against previously published results [1].Results: No significant difference was found between the X-Bolt and the SHS, for either critical buckling pressure (p=0.964), or the maximum von Mises stress (p=0.274), indicating no difference in the risk of femoral head collapse. The maximum von Mises stress (and therefore the risk of collapse) within the cortical bone was significantly higher for the intact femoral head compared to both implants (X-Bolt: p=0.048, SHS: p=0.002). Of the factors examined, necrosis of the femoral head caused the greatest increase in risk.Discussion: The study by Volokh et al. [1] concluded that deterioration of the cancellous bone underneath the cortical shell can greatly increase the risk of femoral head collapse, and the results of the present study support this finding. Interestingly the presence of either an X-Bolt or SHS implant appeared to reduce the risk of femoral head collapse.References: [1] Volokh, K. Y. et al. “Prediction of femoral head collapse in osteonecrosis.” (2006) J Biomech Eng 128, p467-470.[2] Yoshida, H. et al. “Three-dimensional hip contact area and pressure distribution during activities of daily living” (2005) J Biomech 39, p1996-2004.

Elasto-plastic Material Models Introduce Error in Finite Element Polyethylene Wear Predictions

Introduction: Polyethylene wear of joint replacements can cause severe clinical complications, including; osteolysis, implant loosening, inflammation and pain. Wear simulator testing is often used to assess new designs, but it is expensive and time consuming. It is possible to predict the volume of polyethylene implant wear from finite element models using a modification of Archard's classic wear law [1-2]. Typically, linear elastic isotropic, or elasto-plastic material models are used to represent the polyethylene. The purpose of this study was to investigate whether use of a viscoelastic material model would significantly alter the predicted volumetric wear of a mobile-bearing unicompartmental knee replacement. Materials & Methods: Tensile creep-recovery experiments were performed to characterise the creep and relaxation behaviour of the polyethylene (moulded GUR 4150 samples machined to 180x20x1 mm). Samples were loaded to 3 MPa stress in 4 minutes, and then held for 6 hours, the tensile stress was removed and samples were left to relax for 6 hours. The mechanical test data was used fit to a validated three--dimensional fractional Maxwell viscoelastic constitutive material model [3].An explicit finite element model of a mobile--bearing unicompartmental knee replacement was created, which has been described previously [4]. The medial knee replacement was loaded to 1200 N over a period of 0.2 s. The bearing was meshed using quadratic tetrahedral elements (1.5 mm seeding size based on results of a mesh convergence study), and the femoral component was represented as an analytical rigid body. Wear predictions were made from the contact stress and sliding distance using Archard's law, as has been described in the literature [1-2]. A wear factor of 5.24x10-11 was used based upon the work by Netter et al. [2]. All models were created and solved using ABAQUS finite element software (version 6.14, Simulia, Dassault Systemes).Results: The fractional viscoelastic material model predicted almost twice as much wear (0.119 mm3/million cycles) compared to the elasto-plastic model (0.069 mm3/million cycles). The higher wear prediction was due to both an increased sliding distance and higher contact pressures in the viscoelastic model. Discussion: These preliminary findings indicate the simplified elasto-plastic polyethylene material representation can underestimate wear predictions from numerical simulations. Polyethylene is known to be a viscoelastic material which undergoes creep clinically, and it is not surprising that it is necessary to represent that viscoelastic behaviour to accurately predict implant wear. However, it does increase the complexity and run time of such computational studies, which may be prohibitive.References: [1] Maxian, T. A. et al. “A sliding--distance--coupled finite element formulation for polyethylene wear in total hip arthroplasty. ” (1996) J Biomech 29, p687-692. [2] Netter, J. et al. “Prediction of wear in crosslinked polyethylene unicompartmental knee arthroplasty” (2015) Lubricants 3 p381-393. [3] Alotta, G., et al. “On the behaviour of a three-dimensional fractional viscoelastic constitutive model” Manuscript submitted to Meccanica (2016). [4] Pegg, E.C. et al. “Fracture of mobile unicompartmental knee bearings: A parametric finite element study”. (2013) Proc ImechE Part H: Journal of Engineering in Medicine 227 p1213-1223

Viscoelastic material models for more accurate polyethylene wear estimation

Wear debris from ultra-high molecular weight polyethylene (UHMWPE) components used for joint replacement prostheses can cause significant clinical complications, and it is essential to be able to predict implant wear accurately in vitro to prevent unsafe implant designs continuing to clinical trials. The established method to predict wear is simulator testing, but the significant equipment costs, experiment time and equipment availability can be prohibitive. It is possible to predict implant wear using finite element methods, though those reported in the literature simplify the material behaviour of polyethylene and typically use linear or elasto–plastic material models. Such models cannot represent the creep or viscoelastic material behaviour and may introduce significant error. However, the magnitude of this error and importance of this simplification has never been determined. This study compares the volume of predicted wear from a standard elasto–plastic model, to a fractional viscoelastic material model. Both models have been fitted to experimental data. Standard tensile tests in accordance with ISO 527-3 and tensile creep-recovery tests were performed to experimentally characterise both (a) the elasto–plastic parameters and (b) creep and relaxation behaviour of the ultra-high molecular weight polyethylene. Digital image correlation technique was used in order to measure the strain field. The predicted wear with the two material models was compared for a finite element model of a mobile-bearing unicompartmental knee replacement, and wear predictions were made using Archard’s law. The fractional viscoelastic material model predicted almost ten times as much wear compared to the elasto-plastic material representation. This work quantifies, for the first time, the error in troduced by use of a simplified material model in polyethylene wear predictions, and shows the importance of representing the viscoelastic behaviour of polyethylene for wear predictions

PLANTAR PRESSURE CHARACTERISTICS OF SKELETON ATHLETES DURING THE PUSH START ON A DRY-LAND TRAINING SURFACE

The purpose of this study was to characterise plantar pressure maps through the push start of top-level skeleton athletes. The push start is a vital component in skeleton to achieve success, and therefore, a focus on the performance characteristics of the push start could help to reduce the run time and increase the athlete’s initial velocity. Five international skeleton athletes each performed 3-5 push starts on a dry-land push track with wireless pressure insoles. Key differences in 2-d plantar pressure patterns were identified with a confidence interval of