Determination of a Representative and 3D-Printable Root Canal Geometry for Endodontic Investigations and Pre-Clinical Endodontic Training-An Ex Vivo Study.
curvature
endodontics
length
parametric model
root canal morphology
tubular geometry
working width
Journal
Dentistry journal
ISSN: 2304-6767
Titre abrégé: Dent J (Basel)
Pays: Switzerland
ID NLM: 101716125
Informations de publication
Date de publication:
15 May 2023
15 May 2023
Historique:
received:
30
03
2023
revised:
10
05
2023
accepted:
11
05
2023
medline:
26
5
2023
pubmed:
26
5
2023
entrez:
26
5
2023
Statut:
epublish
Résumé
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 (n = 29), an artificial root canal model representing the mean length, curvature, torsion and cross-sectional dimensions of these teeth could be derived.
Identifiants
pubmed: 37232784
pii: dj11050133
doi: 10.3390/dj11050133
pmc: PMC10217352
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : DA 1701/1
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