IADR Abstract Archives
Impression of Subgingival Dental Preparation With Ultrasound
Objectives: Due to its capability to capture hard structures behind soft tissue, ultrasound-based microscanning is a promising solution for patient-friendly tooth impression, especially in the case of subgingival margin preparation. The aim of this study was to assess the accuracy of subgingival prepared teeth by means of ultrasound.
Methods: Ten human teeth (7 premolars, 3 molars) were prepared for crowns with chamfer as finish line and then digitized using two different intraoral scanners (cara Trios and Lava COS) and one extraoral scanner (Straumann CS2). Afterwards, the preparation margin was covered with porcine gingiva (thickness ranged between 0.3 and 1 mm) and every sample was then scanned with a prototype high-frequency ultrasound scanner under experimental subgingival conditions. The accuracy of the ultrasound scans was assessed by comparing each ultrasound dataset with their three optical pendants using a 3D evaluation software (CloudCompare). One-way analysis of variance (ANOVA) and Post-hoc-tests (LSD) were applied to detect significant differences at p≤.05.
Results: Mean deviation ranged from 12.21 to 46.38 µm. There was no statistically significant difference between superimposition of intraoral and extraoral scans (Trios-Lava, Lava-CS2, Trios-CS2). Whereas comparisons between intra-/extraoral scans and ultrasound scans showed statistically significant higher mean deviation. Concerning the type of tooth (premolars and molars) no significant difference could be found. However, gingiva thickness caused a significant correlation to the quality of the ultrasound scan; thin layers presented better image quality than thicker ones.
Conclusions: Ultrasound was able to scan tooth preparation margin covered with gingiva, however with less accuracy than conventional optical scanners (non-covered margin). Gingiva thickness may play an important role in ultrasound scan quality.
Methods: Ten human teeth (7 premolars, 3 molars) were prepared for crowns with chamfer as finish line and then digitized using two different intraoral scanners (cara Trios and Lava COS) and one extraoral scanner (Straumann CS2). Afterwards, the preparation margin was covered with porcine gingiva (thickness ranged between 0.3 and 1 mm) and every sample was then scanned with a prototype high-frequency ultrasound scanner under experimental subgingival conditions. The accuracy of the ultrasound scans was assessed by comparing each ultrasound dataset with their three optical pendants using a 3D evaluation software (CloudCompare). One-way analysis of variance (ANOVA) and Post-hoc-tests (LSD) were applied to detect significant differences at p≤.05.
Results: Mean deviation ranged from 12.21 to 46.38 µm. There was no statistically significant difference between superimposition of intraoral and extraoral scans (Trios-Lava, Lava-CS2, Trios-CS2). Whereas comparisons between intra-/extraoral scans and ultrasound scans showed statistically significant higher mean deviation. Concerning the type of tooth (premolars and molars) no significant difference could be found. However, gingiva thickness caused a significant correlation to the quality of the ultrasound scan; thin layers presented better image quality than thicker ones.
Conclusions: Ultrasound was able to scan tooth preparation margin covered with gingiva, however with less accuracy than conventional optical scanners (non-covered margin). Gingiva thickness may play an important role in ultrasound scan quality.