Three-dimensional (3D) printing is increasingly being utilized in the dental field. After fabricating a prosthesis using a 3D printed resin, a post-curing process is required to improve its mechanical properties, but there has been insufficient research on the optimal post-curing conditions. We used various 3D printed crown and bridge materials in this study, and evaluated the changes in their properties according to post-curing time by evaluating the flexural strength, Weibull modulus, Vickers hardness, color change, degree of conversion, and biocompatibility. The obtained results confirmed that the strength of the 3D printed resin increased when it was post-cured for 60–90 min. The Vickers hardness, the degree of conversion, and biocompatibility of the 3D printed resins increased significantly around the beginning of the post-curing time, and then increased more gradually as the post-curing time increased further. It was observed that the color tone also changed as the post-curing time increased, with some groups showing a ΔE00 value of ≥ 2.25, which can be recognized clinically. This study has confirmed that, after the printing process of a 3D printed resin was completed, a sufficient post-curing time of at least 60 min is required to improve the overall clinical performance of the produced material.

Recent advances in three-dimensional (3D) printing have introduced new materials that can be utilized for dental restorations. Nonetheless, there are limited studies on the color stability of restorations using 3D-printed crowns and bridge resins. Herein, the color stability of conventional computer-aided design/computer-aided manufacturing (CAD/CAM) blocks and 3D-printing resins was evaluated and assessed for their degrees of discoloration based on material type, colorant types (grape juice, coffee, curry, and distilled water (control group)), and storage duration (2, 7, and 30 days) in the colorants. Water sorption, solubility, and scanning electron microscope (SEM) analyses were conducted. A three-way ANOVA analysis showed that all three factors significantly affected the color change of the materials. Notably, the discoloration (ΔE00) was significantly higher in all 3D printing resins (4.74–22.85 over the 30 days) than in CAD/CAM blocks (0.64–4.12 over the 30 days) following immersion in all colorants. 3D-printing resins showed color differences above the clinical limit (2.25) following storage for 7 days or longer in all experimental groups. Curry was the most prominent colorant, and discoloration increased in almost all groups as the storage duration increased. This study suggests that discoloration must be considered when using 3D printing resins for restorations.

In the absence of accurate medical records, it is critical to correctly classify implant fixture systems using periapical radiographs to provide accurate diagnoses and treatments to patients or to respond to complications. The purpose of this study was to evaluate whether deep neural networks can identify four different types of implants on intraoral radiographs. In this study, images of 801 patients who underwent periapical radiographs between 2005 and 2019 at Yonsei University Dental Hospital were used. Images containing the following four types of implants were selected: Brånemark Mk TiUnite, Dentium Implantium, Straumann Bone Level, and Straumann Tissue Level. SqueezeNet, GoogLeNet, ResNet-18, MobileNet-v2, and ResNet-50 were tested to determine the optimal pre-trained network architecture. The accuracy, precision, recall, and F1 score were calculated for each network using a confusion matrix. All five models showed a test accuracy exceeding 90%. SqueezeNet and MobileNet-v2, which are small networks with less than four million parameters, showed an accuracy of approximately 96% and 97%, respectively. The results of this study confirmed that convolutional neural networks can classify the four implant fixtures with high accuracy even with a relatively small network and a small number of images. This may solve the inconveniences associated with unnecessary treatments and medical expenses caused by lack of knowledge about the exact type of implant.

Reproduction of the exact interocclusal relationship using digital workflow is crucial for precise fabrication of accurate prostheses. Intraoral scanner is known to be valid for the measurement of quadrants, however, the role of missing area in the quadrant scan on the virtual interocclusal record (VIR) is uncertain. This study aimed to evaluate the accuracy of VIR in quadrant scans using an intraoral scanner (IOS) under four different edentulous conditions. Eight scans per group were obtained using a laboratory scanner and three IOSs (Trios3, CS3600, i500). Based on trueness and precision, Trios3 had the best results, followed by CS3600 and i500. The trueness and precision were affected by edentulous conditions. The three IOSs showed deviation in the posterior region during assessment of VIR for the missing area with posterior support. CS3600 and i500 showed deviation in the short-span edentulous area without support. In extended edentulous condition without support, Trios3 showed overclosure, while i500 showed an angular deviation. In some groups scanned with Trios3 and i500, the tilting effect was observed. Based on the edentulous condition and type of IOS used, local or general deviations in occlusion were seen. The accuracy of VIR was dependent on accurate scan data. Thus, registration of the occlusal relationship in an edentulous area with more than two missing teeth using IOSs may be clinically more inaccurate than that with a laboratory scanner.

The properties of underlying substrates influence the quality of an intraoral scan, but few studies have compared the outcomes using common restorative materials. In this study, we aimed to compare the accuracy of digital and conventional impressions recorded for four different dental materials as the substrates. Experimental crowns were produced with a metallic surface (gold or cobalt-chromium alloy (Co-Cr)) or without a metallic surface (zirconia or PMMA (polymethyl methacrylate)). A conventional impression was made in the conventional group (CON group), and gypsum models were subsequently scanned with a tabletop scanner. An intraoral scanner was used to scan the crowns either after applying a powder spray to reduce the surface reflectivity (IOS-P group) or without the powder spray (IOS group). The scans were assessed in three dimensions for precision and trueness. The accuracy did not differ between the CON and IOS groups for the non-metallic crowns. However, it was statistically different for the Co-Cr metallic crown, reducing trueness observed between groups as CON > IOS > IOS-P. The study evidences the differences in outer surface accuracy observed with a change in the substrate material to be imaged using an oral scanner and with the impression method. These findings suggest that the restoration material present in the oral cavity should be considered when selecting an impression-taking method.