Nonlinear voxel-based finite element model for strength assessment of healthy and metastatic proximal femurs
Publication year
2020Source
Bone Reports, 12, (2020), article 100263ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
Orthopaedics
Journal title
Bone Reports
Volume
vol. 12
Subject
Radboudumc 10: Reconstructive and regenerative medicine RIHS: Radboud Institute for Health Sciences; Orthopaedics - Radboud University Medical CenterAbstract
Nonlinear finite element (FE) models can accurately quantify bone strength in healthy and metastatic femurs. However, their use in clinical practice is limited since state-of-the-art implementations using tetrahedral meshes involve a lot of manual work for which specific modelling software and engineering knowledge are required. Voxel-based meshes could enable the transition since they are robust and can be highly automated. Therefore, the aim of this work was to bridge the modelling gap between the tetrahedral and voxel-based approach. Specifically, we validated a nonlinear voxel-based FE method relative to experimental data from 20 femurs with and without artificial metastases that had been mechanically loaded until failure. CT scans of the femurs were segmented and automatically converted into a voxel-based mesh with hexahedral elements. Nonlinear material properties were implemented in an open-source linear voxel-based FE solver by adding an additional loop to the routine such that the material properties could be adapted after each increment. Bone strength, quantified as the maximum force in the force-displacement curve, was evaluated. The results were compared to a previously established nonlinear tetrahedral FE approach as well as to the experimentally measured bone strength. The voxel-based FE model predicted the experimental bone strength very well both for healthy (R(2) = 0.90, RMSE = 0.88 kN) and metastatic femurs (R(2) = 0.93, RMSE = 0.64 kN). The model precision and accuracy were very similar to the ones obtained with the tetrahedral model (R(2) = 0.90/0.93, RMSE = 0.90/0.64 kN for intact/metastatic respectively). The more intuitive voxel-based meshes thus quantified macroscale femoral strength equally well as state-of-the-art tetrahedral models. The robustness, high level of automation and time-efficiency (< 30 min) of the implemented workflow offer great potential for developing FE models to improve fracture risk prediction in clinical practice.
This item appears in the following Collection(s)
- Academic publications [244280]
- Electronic publications [131328]
- Faculty of Medical Sciences [92906]
- Open Access publications [105278]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.