OBJECTIVES: The aim of this clinical trial was to test the accuracy of single all-ceramic zirconia crowns resulting from digital intraoral impressions with active wavefront sampling technology by measuring the marginal and internal fits of the crowns. MATERIALS AND METHODS: Thirty-seven teeth (24 anterior and 13 posterior) in fifteen patients were restored with single zirconia-ceramic crowns (Lava/Lava Ceram; 3M ESPE) generated from a digital intraoral scanner (Lava Chairside Oral Scanner; 3M ESPE). Before definitive insertion, silicone replicas were produced for all 37 crowns. The sample was cut in four sections; each section was evaluated in four points: marginal gap, mid-axial wall, axio-occlusal edge and centro-occlusal. A total of 592 measurements (148 for each evaluation point) was examined using stereomicroscopy with a magnification of 50×. The Mann-Whitney U test was used to evaluate whether there were differences between anterior and posterior values (alpha=0.05). RESULTS: The mean values for each point were: 48.65μm (SD 29.45μm) for the marginal gap, 112.25μm (SD 55.54μm) at the mid-axial wall, 137.81μm (SD 71.31μm) at the axio-occlusal edge of the abutments, and 157.25μm (SD 75.51μm) at the centro-occlusal location. No statistical differences were found between the anterior and posterior group for each point (p-values: P1=0.39; P2=0.38; P3=0.07; P4=0.30). CONCLUSIONS: The marginal and internal fitting values obtained were within literature agreed as clinically acceptable for both anterior and posterior teeth. CLINICAL RELEVANCE: Single crown restorations obtained using digital intraoral impressions based on active wavefront sampling technology presented enough accuracy to be used as an alternative to the conventional impression techniques.
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http://dx.doi.org/10.1016/j.jdent.2011.10.005 | DOI Listing |
Cureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFJ Dent
January 2025
Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University; Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Disease, College of Stomatology, Xi'an Jiaotong University; Department of Implant Dentistry, College of Stomatology, Xi'an Jiaotong University. Electronic address:
Objective: The study aimed to evaluate the accuracy and safety of the semi-active robotic system for implant placement in atrophic posterior maxilla.
Methods: Patients underwent robot-assisted implant placement in atrophic posterior maxilla were identified and included. Cone-beam computed tomography (CBCT) was performed before surgery.
J Dent Sci
January 2025
First Clinical Division, 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 Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, Beijing, China.
Background/purpose: Artificial intelligence (AI) can assist in medical diagnosis owing to its high accuracy and efficiency. This study aimed to develop a diagnostic system for automatically determining the degree of tooth wear (TW) using intraoral photographs with deep learning.
Materials And Methods: The study included 388 intraoral photographs.
J Dent Sci
January 2025
School of Dental Technology, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan.
Background/purpose: The performance of intraoral scanners (IOSs) relies on the operator's skills. However, whether operator experience influences IOS accuracy remains unclear. This study investigated the effect of operator experience on the trueness accuracy and time-based efficiency of IOSs.
View Article and Find Full Text PDFJ Dent Sci
January 2025
Department of Dentistry, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.
Background/purpose: Different types of scanners are gradually used to produce digital dental casts in the current dental practice. This study tested the accuracy of the three desktop scanners and two intraoral scanners and evaluated whether the desktop scanners had higher precision than the intraoral scanners.
Materials And Methods: This study used the three desktop and two intraoral scanners to scan a standard dental cast 5 times.
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