Affiliation:
1. Center of 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 Digital Medical Devices & NHC Key Laboratory of Digital Stomatology & Beijing Key Laboratory of Digital Stomatology & Key Laboratory of Digital Stomatology Chinese Academy of Medical Sciences Beijing China
Abstract
AbstractObjectivesThis study aimed to develop a structured light scanning system with a planar mirror to enhance the digital full‐arch implant impression accuracy and to compare it with photogrammetry and intraoral scanner methods.Materials and MethodsAn edentulous maxillary stone cast with six scan bodies was scanned as the reference model using a laboratory scanner. Three scanning modalities were compared (n = 10): (1) self‐developed structured light scanning with a mirror (SSLS); (2) intraoral scanner (IOS); and (3) photogrammetry system (PG). The scanners were stopped for 1 min after each scan. Six scan bodies were analysed within each scan model. Linear deviations between the scan bodies (1–2, 1–3, 1–4, 1–5, and 1–6) and 3D mucosal deviations were established. The overall deviation was calculated as the mean of all linear deviations. “Trueness” represented the discrepancy between the test and reference files, while “precision” denoted the consistency among the test files. Kruskal–Wallis and Mann–Whitney U tests were used for statistical analyses.ResultsSignificant overall linear discrepancies were noted among the SSLS, PG, and IOS groups (p < .001). SSLS showed the best overall trueness and precision (6.6, 5.7 μm), followed by PG (58.4, 6.8 μm) and IOS (214.6, 329.1 μm). For the 3D mucosal deviation, the trueness (p < .001) and precision (p < .001) of the SSLS group were significantly better than those of the IOS group.ConclusionsThe SSLS exhibited higher accuracy in determining the implant positions than the PG and IOS. Additionally, it demonstrated better accuracy in capturing the mucosa than IOS.
Funder
National Natural Science Foundation of China