Cargando…
Application of multidimensional interpolation on nonhomogeneous cancellous bone
Bone, especially cancellous bone, has been demonstrated to be nonhomogeneous. When applied to bone study, it raises the following question: How should the material properties of the bone from the available experimental data be interpolated? In this study, the finite element model of the femur has be...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133422/ https://www.ncbi.nlm.nih.gov/pubmed/30200144 http://dx.doi.org/10.1097/MD.0000000000012224 |
_version_ | 1783354508541165568 |
---|---|
author | Liu, Sikai Li, Sheng Wei, Ning Chang, Wenli Hu, Pan Cheng, Xiaodong Wang, Ling Chen, Wei |
author_facet | Liu, Sikai Li, Sheng Wei, Ning Chang, Wenli Hu, Pan Cheng, Xiaodong Wang, Ling Chen, Wei |
author_sort | Liu, Sikai |
collection | PubMed |
description | Bone, especially cancellous bone, has been demonstrated to be nonhomogeneous. When applied to bone study, it raises the following question: How should the material properties of the bone from the available experimental data be interpolated? In this study, the finite element model of the femur has been built and the nonhomogeneous material properties of the femur have been assigned from the computed tomography (CT) data. These results have been applied to assess some common interpolation algorithms on the bone study, such as Linear Multivariate, Radial Basis, and Nearest Neighbor. It was found that among 3 tested algorithms, the RBAS algorithm has more points with errors from 0% to 15% than in the other 2 algorithms. When the supporting points jump from 160 to 288, the interpolation results significantly improve. When the finite element model reduces the element number from 38,230 to 13,424, all 3 algorithms have slightly better results. The interpolation of bone material properties should use 2 different approaches. The bone interpolation should be applied only to the bone with uniform structure. For the area with dramatic change of structure, the material properties can be defined directly. Among 3 tested algorithms, the Radial Basis algorithm performs best in the statistic study and should be the first choice in the bone study. In addition, the Radial Basis algorithm can be introduced into other methods to smooth the distribution of material properties. Also, with more supporting points (experimental data), the interpolation error becomes less. The interpolation approach offers a significant advantage in the finite element analysis: only 1 material ID needs to define the material interpolated from experimental data, unlike the several hundred material IDs defined for the elements derived from CT data that take material inhomogeneity into account. |
format | Online Article Text |
id | pubmed-6133422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-61334222018-09-19 Application of multidimensional interpolation on nonhomogeneous cancellous bone Liu, Sikai Li, Sheng Wei, Ning Chang, Wenli Hu, Pan Cheng, Xiaodong Wang, Ling Chen, Wei Medicine (Baltimore) Research Article Bone, especially cancellous bone, has been demonstrated to be nonhomogeneous. When applied to bone study, it raises the following question: How should the material properties of the bone from the available experimental data be interpolated? In this study, the finite element model of the femur has been built and the nonhomogeneous material properties of the femur have been assigned from the computed tomography (CT) data. These results have been applied to assess some common interpolation algorithms on the bone study, such as Linear Multivariate, Radial Basis, and Nearest Neighbor. It was found that among 3 tested algorithms, the RBAS algorithm has more points with errors from 0% to 15% than in the other 2 algorithms. When the supporting points jump from 160 to 288, the interpolation results significantly improve. When the finite element model reduces the element number from 38,230 to 13,424, all 3 algorithms have slightly better results. The interpolation of bone material properties should use 2 different approaches. The bone interpolation should be applied only to the bone with uniform structure. For the area with dramatic change of structure, the material properties can be defined directly. Among 3 tested algorithms, the Radial Basis algorithm performs best in the statistic study and should be the first choice in the bone study. In addition, the Radial Basis algorithm can be introduced into other methods to smooth the distribution of material properties. Also, with more supporting points (experimental data), the interpolation error becomes less. The interpolation approach offers a significant advantage in the finite element analysis: only 1 material ID needs to define the material interpolated from experimental data, unlike the several hundred material IDs defined for the elements derived from CT data that take material inhomogeneity into account. Wolters Kluwer Health 2018-09-07 /pmc/articles/PMC6133422/ /pubmed/30200144 http://dx.doi.org/10.1097/MD.0000000000012224 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | Research Article Liu, Sikai Li, Sheng Wei, Ning Chang, Wenli Hu, Pan Cheng, Xiaodong Wang, Ling Chen, Wei Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title | Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title_full | Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title_fullStr | Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title_full_unstemmed | Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title_short | Application of multidimensional interpolation on nonhomogeneous cancellous bone |
title_sort | application of multidimensional interpolation on nonhomogeneous cancellous bone |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133422/ https://www.ncbi.nlm.nih.gov/pubmed/30200144 http://dx.doi.org/10.1097/MD.0000000000012224 |
work_keys_str_mv | AT liusikai applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT lisheng applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT weining applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT changwenli applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT hupan applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT chengxiaodong applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT wangling applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone AT chenwei applicationofmultidimensionalinterpolationonnonhomogeneouscancellousbone |