A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
08 04 2020
Historique:
entrez: 28 4 2020
pubmed: 28 4 2020
medline: 22 9 2020
Statut: epublish

Résumé

The center of resistance (CRES) is regarded as the fundamental reference point for predictable tooth movement. The methods used to estimate the CRES of teeth range from traditional radiographic and physical measurements to in vitro analysis on models or cadaver specimens. Techniques involving finite element analysis of high-dose micro-CT scans of models and single teeth have shown a lot of promise, but little has been done with newer, low-dose, and low resolution cone beam computed tomography (CBCT) images. Also, the CRES for only a few select teeth (i.e., maxillary central incisor, canine, and first molar) have been described; the rest have been largely ignored. There is also a need to describe the methodology of determining the CRES in detail, so that it becomes easy to replicate and build upon. This study used routine CBCT patient images for developing tools and a workflow to obtain finite element models for locating the CRES of maxillary teeth. The CBCT volume images were manipulated to extract three-dimensional (3D) biological structures relevant in determining the CRES of the maxillary teeth by segmentation. The segmented objects were cleaned and converted into a virtual mesh made up tetrahedral (tet4) triangles having a maximum edge length of 1 mm with 3matic software. The models were further converted into a solid volumetric mesh of tetrahedrons with a maximum edge length of 1 mm for use in finite element analysis. The engineering software, Abaqus, was used to preprocess the models to create an assembly and set material properties, interaction conditions, boundary conditions, and load applications. The loads, when analyzed, simulated the stresses and strains on the system, aiding in locating the CRES. This study is the first step in accurate prediction of tooth movement.

Identifiants

pubmed: 32338652
doi: 10.3791/60746
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Bill Luu (B)

Division of Orthodontics, University of Connecticut Health.

Edward Anthony Cronauer (EA)

Private Practice, Miami, FL.

Vaibhav Gandhi (V)

Division of Orthodontics, University of Connecticut Health.

Jonathan Kaplan (J)

Department of Biomedical Engineering, University of Connecticut.

David M Pierce (DM)

Department of Biomedical Engineering, University of Connecticut; Department of Mechanical Engineering, University of Connecticut.

Madhur Upadhyay (M)

Division of Orthodontics, University of Connecticut Health; maupadhyay@uchc.edu.

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Classifications MeSH