Parameters to Improve the Accuracy of Intraoral Scanners for Fabricating Tooth-Supported Restorations.

J Esthet Restor Dent

Department of Restorative Dentistry, School of Dentistry, University of Washington, Seattle, Washington, USA.

Published: November 2024

Objectives: To review the factors that impact the accuracy of intraoral scanners (IOSs) when fabricating tooth-supported restorations.

Overview: Factors can have a different impact on IOS accuracy depending on the scanning purpose. If the goal is to fabricate tooth-supported restorations, it is essential to review the following operator-related factors: IOS technology and system, scan extension and starting quadrant, scanning pattern, scanning distance, and rescanning methods. Additionally, it is critical to interpret the following patient-related factors differently: edentulous spaces, presence of existing restorations on adjacent teeth, and characteristics of the tooth preparation (build-up material, geometry, total occlusal convergence [TOC], finish line location, and surface finishing), and interdental spaces (between tooth preparations or between preparation and the adjacent tooth).

Conclusions: For crown or short-span fixed dental prostheses, a reduced scan extension is recommended. For complete-arch scans, it is advisable to start the scan in the same quadrant as the preparation. If the IOS permits locking the scan, rescanning may be indicated. Restorations on tooth preparations and adjacent teeth reduce accuracy. The simpler the geometry and the larger the TOC, the higher the IOS accuracy. Intracrevicular finish lines result in lower accuracy than equigingival or supragingival positions. Air-particle procedures showed better accuracy than coarse and fine grit and immediate dentin sealing. The greater the space between a preparation and the adjacent tooth, the better the accuracy.

Clinical Implications: Dental professionals must understand and handle the factors that impact the scanning accuracy of intraoral scanners differently depending on the purpose of the scan.

Download full-text PDF

Source
http://dx.doi.org/10.1111/jerd.13364DOI Listing

Publication Analysis

Top Keywords

accuracy intraoral
12
intraoral scanners
12
factors impact
12
accuracy
8
fabricating tooth-supported
8
tooth-supported restorations
8
ios accuracy
8
scan extension
8
adjacent teeth
8
tooth preparations
8

Similar Publications

Objective: This study aimed to compare the manufacturing accuracy of different printing techniques - Stereolithography (SLA), Digital Light Processing (DLP), and PolyJet-using digital dental models.

Methods: The study included cast models of 30 patients aged between 12 and 20 years. The selected models were scanned using an intraoral scanner, and surface topography format files were obtained.

View Article and Find Full Text PDF

Validation of a novel tool for automated tooth modelling by fusion of CBCT-derived roots with the respective IOS-derived crowns.

J Dent

December 2024

OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Dental Medicine, Karolinska Institute, Stockholm, Sweden. Electronic address:

Objectives: To validate a novel artificial intelligence (AI)-based tool for automated tooth modelling by fusing cone beam computed tomography (CBCT)-derived roots with corresponding intraoral scanner (IOS)-derived crowns.

Methods: A retrospective dataset of 30 patients, comprising 30 CBCT scans and 55 IOS dental arches, was used to evaluate the fusion model at full arch and single tooth levels. AI-fused models were compared with CBCT tooth segmentation using point-to-point surface distances-reported as median surface distance (MSD), root mean square distance (RMSD), and Hausdorff distance (HD)- alongside visual assessments.

View Article and Find Full Text PDF

Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.

View Article and Find Full Text PDF

Background: This study aims to evaluate the impact of different thresholds and voxel sizes on the accuracy of Cone-beam computed tomography (CBCT) tooth reconstruction and to assess the accuracy of fused CBCT and intraoral scanning (IOS) tooth models using curvature continuity algorithms under varying thresholds and voxel conditions.

Methods: Thirty-two isolated teeth were digitized using IOS and CBCT at two voxel sizes and five threshold settings. Crown-root fusion was performed using a curvature continuity algorithm.

View Article and Find Full Text PDF

Background: The success of a restoration largely depends on the quality of its fit. This study aimed to investigate the fit quality of monolithic zirconia veneers (MZVs) produced through traditional and digital workflows.

Methods: A typodont maxillary right central incisor was prepared.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!