Comparative Preparation Margin Assessment between Technician Visualization and Artificial Intelligence Utilizing Micro-CT
Abstract
Objective: The objective of this project is to assess the marginal fit of zirconia crowns designed by the 3Shape Automate Machine Learning CAD system to previously established acceptable values for marginal fit of zirconia crowns. Methods: Twenty-Nine crown preparations were completed on a variety of posterior Dentoform teeth and the preparations were scanned via the Dentsply Sirona Primescan intra-oral scanner. Digital files of the scans were uploaded to Dentsply Sirona In-Lab software for digital die trimming and also to the 3Shape Automate program for CAD design for zirconia crowns with a return time of five minutes. The Automate CAD designs were then milled from Zenostar Translucent Zirconia pucks (98mm) and then sintered and sintered in), and the digital die files were printed using a Form 3B 3-D printer. The milled crowns and printed dies were then scanned without luting using a Skyscan 1172 micro-CT and marginal gap, discrepancy, and overhang were measured and analyzed from the image sequences. Results: Total mean for marginal discrepancy (M=236um, SD = 81), overhang (M=212um, SD=101), and gap (M=84um, SD=21). When sample groups were compared between molar and premolar crowns, premolars showed a statistically significantly lower (p = 0.001) mean marginal discrepancy (M=203um, SD=41) than molars (M=250, SD=89). Premolar samples did have a lower percentage of marginal gap measurements that were clinically acceptable when compared to molars, but the difference was not statistically significant (p > 0.05). Significance: When compared to the literature values for marginal fit of CAD/CAM zirconia crowns on chamfer margin preparations, the Automate system had a comparable marginal gap, but did show a greater mean overhang.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 30, 2022
- Accession Number
- AD1186214
Entities
People
- Aaron J Gringer
Organizations
- Uniformed Services University of the Health Sciences