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A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models
Inverse bone (re)modeling (IBR) can infer physiological loading conditions from the bone microstructure. IBR scales unit loads, imposed on finite element (FE) models of a bone, such that the trabecular microstructure is homogeneously loaded and the difference to a target stimulus is minimized. Micro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122636/ https://www.ncbi.nlm.nih.gov/pubmed/36418745 http://dx.doi.org/10.1007/s10439-022-03104-x |
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author | Bachmann, Sebastian Pahr, Dieter H. Synek, Alexander |
author_facet | Bachmann, Sebastian Pahr, Dieter H. Synek, Alexander |
author_sort | Bachmann, Sebastian |
collection | PubMed |
description | Inverse bone (re)modeling (IBR) can infer physiological loading conditions from the bone microstructure. IBR scales unit loads, imposed on finite element (FE) models of a bone, such that the trabecular microstructure is homogeneously loaded and the difference to a target stimulus is minimized. Micro-FE (µFE) analyses are typically used to model the microstructure, but computationally more efficient, homogenized FE (hFE) models, where the microstructure is replaced by an equivalent continuum, could be used instead. However, also the target stimulus has to be translated from the tissue to the continuum level. In this study, a new continuum-level target stimulus relating relative bone density and strain energy density is proposed. It was applied using different types of hFE models to predict the physiological loading of 21 distal radii sections, which was subsequently compared to µFE-based IBR. The hFE models were able to correctly identify the dominant load direction and showed a high correlation of the predicted forces, but mean magnitude errors ranged from − 14.7 to 26.6% even for the best models. While µFE-based IBR can still be regarded as a gold standard, hFE-based IBR enables faster predictions, the usage of more sophisticated boundary conditions, and the usage of clinical images. |
format | Online Article Text |
id | pubmed-10122636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101226362023-04-24 A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models Bachmann, Sebastian Pahr, Dieter H. Synek, Alexander Ann Biomed Eng Original Article Inverse bone (re)modeling (IBR) can infer physiological loading conditions from the bone microstructure. IBR scales unit loads, imposed on finite element (FE) models of a bone, such that the trabecular microstructure is homogeneously loaded and the difference to a target stimulus is minimized. Micro-FE (µFE) analyses are typically used to model the microstructure, but computationally more efficient, homogenized FE (hFE) models, where the microstructure is replaced by an equivalent continuum, could be used instead. However, also the target stimulus has to be translated from the tissue to the continuum level. In this study, a new continuum-level target stimulus relating relative bone density and strain energy density is proposed. It was applied using different types of hFE models to predict the physiological loading of 21 distal radii sections, which was subsequently compared to µFE-based IBR. The hFE models were able to correctly identify the dominant load direction and showed a high correlation of the predicted forces, but mean magnitude errors ranged from − 14.7 to 26.6% even for the best models. While µFE-based IBR can still be regarded as a gold standard, hFE-based IBR enables faster predictions, the usage of more sophisticated boundary conditions, and the usage of clinical images. Springer International Publishing 2022-11-23 2023 /pmc/articles/PMC10122636/ /pubmed/36418745 http://dx.doi.org/10.1007/s10439-022-03104-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Bachmann, Sebastian Pahr, Dieter H. Synek, Alexander A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title | A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title_full | A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title_fullStr | A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title_full_unstemmed | A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title_short | A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models |
title_sort | density-dependent target stimulus for inverse bone (re)modeling with homogenized finite element models |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122636/ https://www.ncbi.nlm.nih.gov/pubmed/36418745 http://dx.doi.org/10.1007/s10439-022-03104-x |
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