Usefulness of an artificial intelligence-assisted indirect bonding method for optimizing orthodontic bracket...

To compare the bracket positioning accuracy of a traditional and an artificial intelligence (AI)-assisted digital indirect bonding (IDB) method to explore the current usefulness of AI for optimizing orthodontic bracket positioning.

Twenty-five clinicians positioned brackets using traditional and AI-assisted digital IDB methods. Bracket positioning differences were quantified using digital superimposition of bracket setups and compared with an optimal setup. A total of 1800 bracket positioning differences were evaluated. One-tailed t-tests were used to determine whether these differences were within limits of 0.5 mm in mesial-distal and occlusal-gingival dimensions and within 2° for tip.

Overall mean bracket position differences between the traditional and digital setups were 0.28 mm for mesial-distal placement and 0.32 mm for occlusal-gingival placement; both were significantly below the 0.5-mm limit. In contrast, differences in tip were 3.4°, which was significantly greater than the 2° limit. Comparisons with an optimal setup showed overall statistically significant differences in mean bracket positioning for tip but not for the mesial-distal or occlusal-gingival measurements for both the traditional and AI-assisted digital IDB methods. However, the digital method was more accurate for bracket tip.

Bracket positioning is consistent and highly accurate in linear dimensions with both traditional and digital IDB methods; however, AI may be useful for improving accuracy of bracket angulation. Clinicians who currently use traditional IDB methods may adopt AI-assisted digital IDB without compromising bracket positioning accuracy.