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Updated: Jan 13, 2026

Measuring the Complete-arch Distortion of an Optical Dental Impression
Published on: May 30, 2019
Effectiveness of an AI-Assisted Digital Workflow for Complete-Arch Implant Impressions: An In Vitro Comparative Study
Marco Tallarico1, Mohammad Qaddomi2, Elena De Rosa3
1Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy.
None:
Background: The accuracy and consistency of complete-arch digital impressions are fundamental for long-term success of implant-supported rehabilitations. Recently, artificial intelligence (AI)-assisted tools, such as SmartX (Medit Link v3.4.2, MEDIT Corp., Seoul, South of Korea), have been introduced to enhance scan body recognition and data alignment during intraoral scanning. Objective: This in vitro study aimed to evaluate the impact of SmartX on impression accuracy, consistency, operator confidence, and technique sensitivity in complete-arch implant workflows. Methods: Seventy-two digital impressions were recorded on edentulous mandibular models with four dummy implants, using six experimental subgroups based on scan body design (double- or single-wing), scanning technique (occlusal or combined straight/zigzag), and presence/absence of SmartX tool. Each group was scanned by both an expert and a novice operator (n = 6 scans per subgroup). Root mean square (RMS) deviation and scanning time were assessed. Data were tested for normality (Shapiro-Wilk). Parametric tests (t-test, repeated measures ANOVA with Greenhouse-Geisser correction) or non-parametric equivalents (Mann-Whitney U, Friedman) were applied as appropriate. Post hoc comparisons used Tukey HSD or Dunn-Bonferroni tests (α = 0.05). Results: SmartX significantly improved consistency and operator confidence, especially among novices, although it did not yield statistically significant differences in scan accuracy (p > 0.05). The tool mitigated early scanning errors and reduced dependence on operator technique. SmartX also enabled successful library alignment with minimal data; however, scanning time was generally longer with its use, particularly for beginners. Conclusions: While SmartX did not directly enhance trueness, it substantially improved scan reliability and user experience in complete-arch workflows. Its ability to minimize technique sensitivity and improve reproducibility makes it a valuable aid in both training and clinical settings. Further clinical validation is warranted to support its integration into routine practice.

