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Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study

Bone adapts to the change of mechanical stimulus by bone remodeling activities. A number of numerical algorithms have been developed to model the adaptive bone remodeling under mechanical loads for orthopedic and dental applications. This paper examines the effects of several model parameters on the...

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Autores principales: Su, Kangning, Yuan, Li, Yang, Jie, Du, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797806/
https://www.ncbi.nlm.nih.gov/pubmed/31624317
http://dx.doi.org/10.1038/s41598-019-51429-w
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author Su, Kangning
Yuan, Li
Yang, Jie
Du, Jing
author_facet Su, Kangning
Yuan, Li
Yang, Jie
Du, Jing
author_sort Su, Kangning
collection PubMed
description Bone adapts to the change of mechanical stimulus by bone remodeling activities. A number of numerical algorithms have been developed to model the adaptive bone remodeling under mechanical loads for orthopedic and dental applications. This paper examines the effects of several model parameters on the computed apparent bone density in mandible under normal chewing and biting forces. The density change rate was based on the strain energy density per unit mass. The algorithms used in this study containing an equilibrium zone (lazy zone) and saturated values of density change rate provides certain stability to result in convergence without discontinuous checkerboard patterns. The parametric study shows that when different boundary conditions were applied, the bone density distributions at convergence were very different, except in the vicinity of the applied loads. Compared with the effects of boundary conditions, the models are less sensitive to the choice of initial density values. Several models starting from different initial density values resulted in similar but not exactly the same bone density distribution at convergence. The results also show that higher reference value of mechanical stimulus resulted in lower average bone density at convergence. Moreover, the width of equilibrium zone did not substantially affect the average density at convergence. However, with increasing width, the areas with the highest and the lowest bone density areas were all reduced. The limitations of the models and challenges for future work were discussed for the better agreement between the computed results and the in vivo data.
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spelling pubmed-67978062019-10-25 Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study Su, Kangning Yuan, Li Yang, Jie Du, Jing Sci Rep Article Bone adapts to the change of mechanical stimulus by bone remodeling activities. A number of numerical algorithms have been developed to model the adaptive bone remodeling under mechanical loads for orthopedic and dental applications. This paper examines the effects of several model parameters on the computed apparent bone density in mandible under normal chewing and biting forces. The density change rate was based on the strain energy density per unit mass. The algorithms used in this study containing an equilibrium zone (lazy zone) and saturated values of density change rate provides certain stability to result in convergence without discontinuous checkerboard patterns. The parametric study shows that when different boundary conditions were applied, the bone density distributions at convergence were very different, except in the vicinity of the applied loads. Compared with the effects of boundary conditions, the models are less sensitive to the choice of initial density values. Several models starting from different initial density values resulted in similar but not exactly the same bone density distribution at convergence. The results also show that higher reference value of mechanical stimulus resulted in lower average bone density at convergence. Moreover, the width of equilibrium zone did not substantially affect the average density at convergence. However, with increasing width, the areas with the highest and the lowest bone density areas were all reduced. The limitations of the models and challenges for future work were discussed for the better agreement between the computed results and the in vivo data. Nature Publishing Group UK 2019-10-17 /pmc/articles/PMC6797806/ /pubmed/31624317 http://dx.doi.org/10.1038/s41598-019-51429-w Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Su, Kangning
Yuan, Li
Yang, Jie
Du, Jing
Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title_full Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title_fullStr Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title_full_unstemmed Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title_short Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study
title_sort numerical simulation of mandible bone remodeling under tooth loading: a parametric study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797806/
https://www.ncbi.nlm.nih.gov/pubmed/31624317
http://dx.doi.org/10.1038/s41598-019-51429-w
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