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Computational modelling of bone augmentation in the spine

Computational models are gaining importance not only for basic science, but also for the analysis of clinical interventions and to support clinicians prior to intervention. Vertebroplasty has been used to stabilise compression fractures in the spine for years, yet there are still diverging ideas on...

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Detalles Bibliográficos
Autores principales: Badilatti, Sandro D., Kuhn, Gisela A., Ferguson, Stephen J., Müller, Ralph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chinese Speaking Orthopaedic Society 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5986996/
https://www.ncbi.nlm.nih.gov/pubmed/30035057
http://dx.doi.org/10.1016/j.jot.2015.09.003
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author Badilatti, Sandro D.
Kuhn, Gisela A.
Ferguson, Stephen J.
Müller, Ralph
author_facet Badilatti, Sandro D.
Kuhn, Gisela A.
Ferguson, Stephen J.
Müller, Ralph
author_sort Badilatti, Sandro D.
collection PubMed
description Computational models are gaining importance not only for basic science, but also for the analysis of clinical interventions and to support clinicians prior to intervention. Vertebroplasty has been used to stabilise compression fractures in the spine for years, yet there are still diverging ideas on the ideal deposition location, volume, and augmentation material. In particular, little is known about the long-term effects of the intervention on the surrounding biological tissue. This review aims to investigate computational efforts made in the field of vertebroplasty, from the augmentation procedure to strength prediction and long-term in silico bone biology in augmented human vertebrae. While there is ample work on simulating the augmentation procedure and strength prediction, simulations predicting long-term effects are lacking. Recent developments in bone remodelling simulations have the potential to show adaptation to cement augmentation and, thus, close this gap.
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spelling pubmed-59869962018-07-20 Computational modelling of bone augmentation in the spine Badilatti, Sandro D. Kuhn, Gisela A. Ferguson, Stephen J. Müller, Ralph J Orthop Translat Review Article Computational models are gaining importance not only for basic science, but also for the analysis of clinical interventions and to support clinicians prior to intervention. Vertebroplasty has been used to stabilise compression fractures in the spine for years, yet there are still diverging ideas on the ideal deposition location, volume, and augmentation material. In particular, little is known about the long-term effects of the intervention on the surrounding biological tissue. This review aims to investigate computational efforts made in the field of vertebroplasty, from the augmentation procedure to strength prediction and long-term in silico bone biology in augmented human vertebrae. While there is ample work on simulating the augmentation procedure and strength prediction, simulations predicting long-term effects are lacking. Recent developments in bone remodelling simulations have the potential to show adaptation to cement augmentation and, thus, close this gap. Chinese Speaking Orthopaedic Society 2015-10-01 /pmc/articles/PMC5986996/ /pubmed/30035057 http://dx.doi.org/10.1016/j.jot.2015.09.003 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Badilatti, Sandro D.
Kuhn, Gisela A.
Ferguson, Stephen J.
Müller, Ralph
Computational modelling of bone augmentation in the spine
title Computational modelling of bone augmentation in the spine
title_full Computational modelling of bone augmentation in the spine
title_fullStr Computational modelling of bone augmentation in the spine
title_full_unstemmed Computational modelling of bone augmentation in the spine
title_short Computational modelling of bone augmentation in the spine
title_sort computational modelling of bone augmentation in the spine
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5986996/
https://www.ncbi.nlm.nih.gov/pubmed/30035057
http://dx.doi.org/10.1016/j.jot.2015.09.003
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