[Dental implant and transplant].

Inf Dent

Published: August 1975

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Design: A triple-armed, double-blind randomized controlled trial with cross-over design investigated patient-reported satisfaction and objective dental evaluation of a 3-unit, monolithic zirconium dioxide (ZrO2), implant-supported fixed dental prosthesis (iFDP) fabricated with 2 completely digital workflows and 1 mixed analog-digital workflow.

Case Selection: Participants enrolled required rehabilitation of 2 dental implants in posterior region of either of the arches with a 3-unit, ZrO2 iFDP. A total of 20 participants received the 3 types of ZrO2, iFDP fabricated by 3 different methods.

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Design: A retrospective cohort study assessing the mid-to-long-term outcomes and risk factors affecting the prosthetic success and survival of implant-supported cross-arch fixed dental prostheses (IFCDPs) with monolithic zirconia frameworks.

Cohort Selection: Forty-seven patients received a total of 51 cross-arch prostheses (27 maxillary and 24 mandibular prostheses), supported by 302 implants. Comprehensive clinical and radiographic records were available over a follow-up period ranging from 5 to 13 years.

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Optimizing dental implant identification using deep learning leveraging artificial data.

Sci Rep

January 2025

Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Kagawa University, 1750-1, Ikenobe, Miki-cho, Kita-gun, Takamatsu, 761-0793, Kagawa, Japan.

This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create implant surface models. Subsequently, implant surface models were used to generate two-dimensional X-ray images, which were compiled along with original images to create a comprehensive dataset.

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Objective: Peri-implant diseases (peri-implant mucositis and peri-implantitis) are inflammatory conditions that affect the peri-implant tissues and are induced by microbial biofilms (dental plaque) formed around the implant. Removal of biofilm is the fundamental step in managing peri-implant diseases. Interdental cleaning aids such as interdental brush, unitufted brush, or oral irrigation along with regular toothbrushing are recommended for effective plaque control around implants.

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Titanium dioxide nanotube arrays (TNTs) generated in situ on the surface of dental implants have been shown to enhance bone integration for load-bearing support while managing load distribution and energy dissipation to prevent bone resorption from overload. However, their inadequate stability limits the clinical use of conventional TNTs. This study introduces an innovative approach to improve the mechanical stability of TNTs while maintaining their bone-integration efficiency.

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