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Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study
Models of artificial root canals are used in several fields of endodontic investigations and pre-clinical endodontic training. They allow the physical testing of dental treatments, the operating of instruments used and the interaction between these instruments and the tissues. Currently, a large num...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217352/ https://www.ncbi.nlm.nih.gov/pubmed/37232784 http://dx.doi.org/10.3390/dj11050133 |
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author | Kucher, Michael Dannemann, Martin Modler, Niels Böhm, Robert Hannig, Christian Kühne, Marie-Theres |
author_facet | Kucher, Michael Dannemann, Martin Modler, Niels Böhm, Robert Hannig, Christian Kühne, Marie-Theres |
author_sort | Kucher, Michael |
collection | PubMed |
description | Models of artificial root canals are used in several fields of endodontic investigations and pre-clinical endodontic training. They allow the physical testing of dental treatments, the operating of instruments used and the interaction between these instruments and the tissues. Currently, a large number of different artificial root canal models exist whose geometry is created either on the basis of selected natural root canal systems or to represent individual geometrical properties. Currently, only a few geometric properties such as the root canal curvature or the endodontic working width are taken into consideration when generating these models. To improve the representational capability of the artificial root canal models, the aim of the current study is therefore to generate an artificial root canal based on the statistical evaluation of selected natural root canals. Here, the approach introduced by Kucher for determining the geometry of a root canal model is used, which is based on the measurement and statistical evaluation of the root canal center line’s curvatures and their cross-sectional dimensions. Using the example of unbranched distal root canals of mandibular molars ([Formula: see text] = 29), an artificial root canal model representing the mean length, curvature, torsion and cross-sectional dimensions of these teeth could be derived. |
format | Online Article Text |
id | pubmed-10217352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102173522023-05-27 Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study Kucher, Michael Dannemann, Martin Modler, Niels Böhm, Robert Hannig, Christian Kühne, Marie-Theres Dent J (Basel) Article Models of artificial root canals are used in several fields of endodontic investigations and pre-clinical endodontic training. They allow the physical testing of dental treatments, the operating of instruments used and the interaction between these instruments and the tissues. Currently, a large number of different artificial root canal models exist whose geometry is created either on the basis of selected natural root canal systems or to represent individual geometrical properties. Currently, only a few geometric properties such as the root canal curvature or the endodontic working width are taken into consideration when generating these models. To improve the representational capability of the artificial root canal models, the aim of the current study is therefore to generate an artificial root canal based on the statistical evaluation of selected natural root canals. Here, the approach introduced by Kucher for determining the geometry of a root canal model is used, which is based on the measurement and statistical evaluation of the root canal center line’s curvatures and their cross-sectional dimensions. Using the example of unbranched distal root canals of mandibular molars ([Formula: see text] = 29), an artificial root canal model representing the mean length, curvature, torsion and cross-sectional dimensions of these teeth could be derived. MDPI 2023-05-15 /pmc/articles/PMC10217352/ /pubmed/37232784 http://dx.doi.org/10.3390/dj11050133 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kucher, Michael Dannemann, Martin Modler, Niels Böhm, Robert Hannig, Christian Kühne, Marie-Theres Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title | Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title_full | Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title_fullStr | Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title_full_unstemmed | Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title_short | Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training—An Ex Vivo Study |
title_sort | determination of a representative and 3d-printable root canal geometry for endodontic investigations and pre-clinical endodontic training—an ex vivo study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217352/ https://www.ncbi.nlm.nih.gov/pubmed/37232784 http://dx.doi.org/10.3390/dj11050133 |
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