The aim of this study was to compare the mechanical properties of orthodontic aligners among different commercially available 3D printing devices. Three different 3D printers were included in this study (Formlabs Form 2 3D printer; Moonray S100 printer (Sprintray, Los Angeles, CA, USA); Eden500V Stratasys 3D Printers were used to prepare orthodontic aligners with dental. The central incisors of each aligner were cut, prepared, and evaluated in terms of Martens-Hardness (HM), indentation-modulus (E), and elastic-index (η) as per ISO14577-1:2002. pairwise comparisons indicated no significant difference in Martens-Hardness (HM), indentation-modulus (E), and elastic-index (η) properties in any group. Under the limitations of this study, it may be concluded that the mechanical properties of 3D-printed orthodontic aligners are dependent on the 3D printer used, and thus, differences in their clinical efficacy are anticipated.
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http://dx.doi.org/10.4103/jpbs.jpbs_796_23 | DOI Listing |
PeerJ
January 2025
Section of Orthodontics and Craniofacial Biology, Department of Dentistry, Radboud University Medical Center, Nijmegen, Netherlands.
Aim: To compare three-dimensional (3D) facial morphology of various unilateral cleft subphenotypes at 9-years of age to normative data using a general face template and automatic landmarking. The secondary objective is to compare facial morphology of 9-year-old children with unilateral fusion to differentiation defects.
Methods: 3D facial stereophotogrammetric images of 9-year-old unilateral cleft patients were imported into 3DMedX® for processing.
Sci Rep
January 2025
Department of Orthodontics and Dentofacial Orthopedics, University Medical Center of the Johannes Gutenberg-University Mainz, Augustusplatz 2, 55131, Mainz, Germany.
Direct printed aligners (DPAs) offer benefits like the ability to vary layer thickness within a single DPA and to 3D print custom-made removable orthodontic appliances. The biocompatibility of appliances made from Tera Harz TA-28 (Graphy Inc., Seoul, South Korea) depends on strict adherence to a standardized production and post-production protocol, including UV curing.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Faculty of Dentistry, Department of Orthodontics , Hacettepe University, Sihhiye, Ankara, 06100, Turkey.
Introduction: To evaluate topographic changes of enamel surface in 3-dimensional after different debonding methods of aligner attachments formed with 2 different composite resins.
Methods: Vertical rectangular attachments were created on 88 premolar teeth and divided into two composite resin groups (Group 1:flowable, Group 2:packable) (N = 44). These were then divided into two subgroups (N = 22) using different debonding methods.
J Clin Med
January 2025
Department of Pediatric Dentistry and Preclinical Dentistry, Wroclaw Medical University, Krakowska 26, 50-425 Wroclaw, Poland.
Inflammation in the periapical area of primary teeth can affect the development and eruption of permanent teeth. In an asymptomatic course, they are detected accidentally during routine examinations. In such cases, they often reach significant dimensions and cause irreversible changes.
View Article and Find Full Text PDFBeijing Da Xue Xue Bao Yi Xue Ban
February 2025
Center for Digital Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digi-tal Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Research Center of Engineering and Technology for Computerized Dentistry, Beijing 100081, China.
Objective: To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data, by utilizing a dynamic graph-based registration network model (maxillofacial dynamic graph registration network, MDGR-Net), and to provide a valuable reference for digital design and analysis in clinical dental applications.
Methods: Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022. Through data augmentation, a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm.
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