five

Stress distribution analysis in anterior teeth caused by several retraction mechanics

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://figshare.com/articles/dataset/Stress_distribution_analysis_in_anterior_teeth_caused_by_several_retraction_mechanics/19923812
下载链接
链接失效反馈
官方服务:
资源简介:
ABSTRACT Introduction: Orthodontic retraction of the anterior teeth is indicated when the patient has a malocclusion with protrusion of the incisors. Several mechanics are indicated to perform this retraction. Objective: The objective of this study was to compare the strains generated by four different types of retraction mechanics along the roots of the anterior teeth. Methods: A photoelastic model simulating an arch with first premolars extraction was made. Sixty retraction archwires were prepared, including fifteen for each type of mechanics evaluated: sliding, teardrop loop spring, T-loop spring and double key loop archwire. The strains were observed in two perspectives: occlusal and oblique. In the occlusal perspective, strains were compared among the six anterior teeth. From the oblique perspective, strains were compared among the thirds of the left canine root. Results: In the occlusal perspective, the teardrop loop spring mechanics presented greater strains, followed by T-loop spring, double key loop archwire and sliding mechanics. In all mechanics, strains were more concentrated in the canines than in the incisors. From the oblique perspective, the teardrop loop mechanics generated greater strains in the cervical regions of the canine, and in the apical regions, no differences were found in strains among the four types of mechanics. In the same mechanics, greater strains were present in the cervical zones. Conclusion: The teardrop loop spring retraction mechanic presented the greatest mean strain, and the sliding retraction mechanic presented the lowest mean strain on the root of anteroinferior teeth in the occlusal and oblique perspectives.
创建时间:
2021-05-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作