Nonlinear voxel-based finite element model for strength assessment of healthy and metastatic proximal femurs.
Bone metastasis
Bone strength
Finite element analysis
Human femurs
Voxel-based mesh
Journal
Bone reports
ISSN: 2352-1872
Titre abrégé: Bone Rep
Pays: United States
ID NLM: 101646176
Informations de publication
Date de publication:
Jun 2020
Jun 2020
Historique:
received:
16
01
2020
revised:
27
03
2020
accepted:
30
03
2020
entrez:
24
4
2020
pubmed:
24
4
2020
medline:
24
4
2020
Statut:
epublish
Résumé
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
Identifiants
pubmed: 32322609
doi: 10.1016/j.bonr.2020.100263
pii: S2352-1872(20)30023-1
pii: 100263
pmc: PMC7163060
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100263Informations de copyright
© 2020 The Authors.
Déclaration de conflit d'intérêts
None.
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