Literature DB >> 30427953

In Vitro Characterization of Original and Nonoriginal Implant Abutments.

Matthias Karl, Ainara Irastorza-Landa.   

Abstract

PURPOSE: In addition to original componentry, clinicians can choose to restore an implant using third-party parts claimed to be compatible with the original implant system. The goal of these in vitro experiments was to evaluate the performance of a selection of original and clone titanium abutments available for a widely used implant system with an internal conical connection.
MATERIALS AND METHODS: Six groups of original and clone abutments compatible with NobelActive implants were compared based on the following parameters: dimensional accuracy, gap formation, circumferential strain, abutment screw preload, micromotion, abutment settling, median fatigue limit (MFL), and bacterial leakage. Each parameter was analyzed separately and compared with the original (reference) abutment applying a variety of statistical tests (α = .05).
RESULTS: Overall, the results obtained in the different experiments showed considerable deviation from the reference abutment. Deviations in interface geometry of the abutments were inconsistent and reached up to 56.26%. Gap measurements performed on cross sections of implant-abutment assemblies were not sensitive enough for detecting consistent differences. Development of circumferential strain at the implant shoulder reached up to 1,389.30 μm/m. Abutment screw preload ranged from 285.25 N to 397.70 N, while micromotion at the implant-abutment interface ranged from 61.68 μm to 79.69 μm. Abutment settling resulting from screw fixation was greater compared with settling caused by dynamic loading, reaching up to 0.09 mm. The MFL ranged from 246.00 N to 344.00 N. All implant-abutment combinations showed bacterial leakage after 6 days of incubation.
CONCLUSION: While clone abutments may look similar to the original component, they display considerable differences and variations in their physico-mechanical characteristics detectable by advanced testing methods. How much these differences affect reliability and longevity of the restoration's clinical performance should be investigated in clinical studies.

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Substances:

Year:  2018        PMID: 30427953     DOI: 10.11607/jomi.6921

Source DB:  PubMed          Journal:  Int J Oral Maxillofac Implants        ISSN: 0882-2786            Impact factor:   2.804


  7 in total

1.  A comparative biomechanical study of original and compatible titanium bases: evaluation of screw loosening and 3D-crown displacement following cyclic loading analysis.

Authors:  Rimantas Ožiūnas; Jurgina Sakalauskienė; Darius Jegelevičius; Gintaras Janužis
Journal:  J Adv Prosthodont       Date:  2022-04-27       Impact factor: 1.989

2.  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

3.  Conical connection adjustment in prosthetic abutments obtained by different techniques.

Authors:  Roser Camós-Tena; Tomás Escuin-Henar; Sergi Torné-Duran
Journal:  J Clin Exp Dent       Date:  2019-05-01

4.  An In-Vitro Analysis of Peri-Implant Mucosal Seal Following Photofunctionalization of Zirconia Abutment Materials.

Authors:  Masfueh Razali; Wei Cheong Ngeow; Ros Anita Omar; Wen Lin Chai
Journal:  Biomedicines       Date:  2021-01-15

5.  Transfer learning in a deep convolutional neural network for implant fixture classification: A pilot study.

Authors:  Hak-Sun Kim; Eun-Gyu Ha; Young Hyun Kim; Kug Jin Jeon; Chena Lee; Sang-Sun Han
Journal:  Imaging Sci Dent       Date:  2022-03-15

6.  Deep learning-based dental implant recognition using synthetic X-ray images.

Authors:  Aviwe Kohlakala; Johannes Coetzer; Jeroen Bertels; Dirk Vandermeulen
Journal:  Med Biol Eng Comput       Date:  2022-08-18       Impact factor: 3.079

7.  Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

Authors:  Jong-Eun Kim; Na-Eun Nam; June-Sung Shim; Yun-Hoa Jung; Bong-Hae Cho; Jae Joon Hwang
Journal:  J Clin Med       Date:  2020-04-14       Impact factor: 4.241

  7 in total

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