Literature DB >> 32037294

Effect of thermocycling on the surface texture and release of titanium particles from titanium alloy (Ti6Al4V) plates and dental implants: An in vitro study.

Mohammad Ali Saghiri1, Armen Asatourian2, Hamed Kazerani3, James L Gutmann4, Steven M Morgano5.   

Abstract

STATEMENT OF PROBLEM: The release of titanium (Ti) particles from the surface of endosseous dental implants is not well understood.
PURPOSE: The purpose of this in vitro study was to evaluate the effect of thermocycling on the surface texture and release of Ti particles from the surface of dental implants.
MATERIAL AND METHODS: Three MSI dental implants and 3 Ti alloy (Ti6Al4V) plates were divided into 6 subgroups (n=3). Specimens in each group were subjected to 0 (control group), 100, 200, 500, 1000, and 2000 thermocycles. After each cycling process, artificial saliva was collected, and the concentrations of released Ti particles were quantified by inductively coupled plasma-mass spectrophotometry (ICP-MS). The surfaces of the dental implants and Ti plates were evaluated before and after thermocycling by scanning electron microscopy (SEM), and SEM images were analyzed by using the ImageJ software program. Data were analyzed by mixed-model ANOVA and post hoc Tukey tests (α=.05).
RESULTS: The greatest Ti release was seen after 2000 thermocycles. After increasing the number of cycles, additional Ti particles were released. SEM images of the surfaces of the dental implants and Ti plates displayed significant changes in surface texture.
CONCLUSIONS: Thermocycling continuously removed the protective TiO2 layer on the surface of dental implants, resulting in the release of Ti particles. The surface treatment and texture did not affect the release of Ti particles.
Copyright © 2019 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 32037294     DOI: 10.1016/j.prosdent.2019.11.013

Source DB:  PubMed          Journal:  J Prosthet Dent        ISSN: 0022-3913            Impact factor:   3.426


  2 in total

1.  Deep Neural Networks for Dental Implant System Classification.

Authors:  Shintaro Sukegawa; Kazumasa Yoshii; Takeshi Hara; Katsusuke Yamashita; Keisuke Nakano; Norio Yamamoto; Hitoshi Nagatsuka; Yoshihiko Furuki
Journal:  Biomolecules       Date:  2020-07-01

2.  TVGG Dental Implant Identification System.

Authors:  Jianbin Guo; Pei-Wei Tsai; Xingsi Xue; Dong Wu; Qui Tran Van; Chanaka Nimantha Kaluarachchi; Hong Thi Dang; Nikhitha Chintha
Journal:  Front Pharmacol       Date:  2022-08-08       Impact factor: 5.988

  2 in total

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