MicroCT-based finite element models as a tool for virtual testing of cortical bone

Ramezanzadehkoldeh, Masoud; Skallerud, Bjørn

doi:10.1016/j.medengphy.2017.04.011

Cited by 19 publications

(8 citation statements)

References 41 publications

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“…Parallel to the work conducted on modelling human bone, there have been efforts to model bone of several animals. Studies range from small animals such as mice [287,[329][330][331][332][333][334][335][336], rats [288,[337][338][339][340][341][342][343] and zebrafish [344], to medium-sized animals such as dogs [345], as well as large animals such as pigs [346][347][348][349][350][351][352], sheep [353][354][355], bovine [220,[356][357][358][359][360][361][362][363] and horses [273,364].…”

Section: Remark 27 (Animal Bone Modelling and Simulation)mentioning

confidence: 99%

“…Research directives within the field of animal bone modelling and analysis include 12A 1 -12A 3 . 12A 1 : Usage of animal bone experimental data to estimate mechanical properties [220,287,288,330,331,340,342,347,363,369] and conception of animal bone failure models [331,338,349,351,356,358,362] that may be similar to human bone failure models [342,344,370]. This directive includes studies in which pathological changes to the skeleton are purposefully induced in test animals by genetic manipulation [371] or malnutrition [332,338,354] in order to create models to study osteoporosis [338,354].…”

Section: Remark 27 (Animal Bone Modelling and Simulation)mentioning

confidence: 99%

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

et al. 2019

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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.

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Section: Remark 27 (Animal Bone Modelling and Simulation)mentioning

confidence: 99%

Section: Remark 27 (Animal Bone Modelling and Simulation)mentioning

confidence: 99%

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

et al. 2019

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“…Currently, the direct voxel model and the discrete smooth model are used to develop numerical models of bone tissues. The voxel model is the most widespread and most widely used [ 22 , 23 ]. On the basis of two-dimensional images obtained from a CT, a volume model is developed in which the smallest unit of volume (voxel) is converted into a hexagonal finite element.…”

Section: Introductionmentioning

confidence: 99%

Correlation of Bone Material Model Using Voxel Mesh and Parametric Optimization

et al. 2022

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The authors present an algorithm for determining the stiffness of the bone tissue for individual ranges of bone density. The paper begins with the preparation and appropriate mechanical processing of samples from the bovine femur and their imaging using computed tomography and then processing DICOM files in the MIMICS system. During the processing of DICOM files, particular emphasis was placed on defining basic planes along the sides of the samples, which improved the representation of sample geometry in the models. The MIMICS system transformed DICOM images into voxel models from which the whole bone FE model was built in the next step. A single voxel represents the averaged density of the real sample in a very small finite volume. In the numerical model, it is represented by the HEX8 element, which is a cube. All voxels were divided into groups that were assigned average equivalent densities. Then, the previously prepared samples were loaded to failure in a three-point bending test. The force waveforms as a function of the deflection of samples were obtained, based on which the global stiffness of the entire sample was determined. To determine the stiffness of each averaged voxel density value, the authors used advanced optimization analyses, during which numerical analyses were carried out simultaneously, independently mapping six experimental tests. Ultimately, the use of genetic algorithms made it possible to select a set of stiffness parameters for which the error of mapping the global stiffness for all samples was the smallest. The discrepancies obtained were less than 5%, which the authors considered satisfactory by the authors for such a heterogeneous medium and for samples collected from different parts of the bone. Finally, the determined data were validated for the sample that was not involved in the correlation of material parameters. The stiffness was 7% lower than in the experimental test.

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“…Regarding clinical application, the subject-specific prediction of mechanical bone properties is a highly valuable tool as this technique allows to precisely replicate morphology and structure, as shown in recent studies (Ramezanzadehkoldeh and Skallerud [12], Bahia [13] and Väänänen [14]). Particularly, if one considers this FEM analysis to enter the clinical daily praxis, where more concern is centered toward estimating critical loads at which fracture could occur rather than precisely knowing the load level at which transition to damage occurs.…”

Section: Introductionmentioning

confidence: 99%

Finite element modeling of multiple density materials of bone specimens for biomechanical behavior evaluation

et al. 2021

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The finite elements method allied with the computerized axial tomography (CT) is a mathematical modeling technique that allows constructing computational models for bone specimens from CT data. The objective of this work was to compare the experimental biomechanical behavior by three-point bending tests of porcine femur specimens with different types of computational models generated through the finite elements’ method and a multiple density materials assignation scheme. Using five femur specimens, 25 scenarios were created with differing quantities of materials. This latter was applied to computational models and in bone specimens subjected to failure. Among the three main highlights found, first, the results evidenced high precision in predicting experimental reaction force versus displacement in the models with larger number of assigned materials, with maximal results being an R2 of 0.99 and a minimum root-mean-square error of 3.29%. Secondly, measured and computed elastic stiffness values follow same trend with regard to specimen mass, and the latter underestimates stiffness values a 6% in average. Third and final highlight, this model can precisely and non-invasively assess bone tissue mechanical resistance based on subject-specific CT data, particularly if specimen deformation values at fracture are considered as part of the assessment procedure.

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MicroCT-based finite element models as a tool for virtual testing of cortical bone

Cited by 19 publications

References 41 publications

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

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

Correlation of Bone Material Model Using Voxel Mesh and Parametric Optimization

Finite element modeling of multiple density materials of bone specimens for biomechanical behavior evaluation

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