Fit accuracy of complete crowns fabricated by generative artificial intelligence design: a comparative clinical study

Designing restorations remains challenging because the process is time-consuming and requires operator skill and experience. This clinical study evaluated the fit accuracy of polymerized complete crowns fabricated using a web-based 3D generative artificial intelligence design (GAID) method compared to crowns fabricated using a conventional computer-aided design (CCAD) method. Sixty-two patients requiring complete crowns in maxillary and mandibular premolars and molars were enrolled. After tooth preparation, digital impressions were taken using an intraoral scanner. Two crowns per patient were designed: one used a web-based automatic 3D GAID software program, and the other used a standard human-driven CCAD software program. The crowns were 3D-printed and delivered to the patients. Marginal and internal discrepancies and occlusal contacts were evaluated using a digital triple scan technique. Statistical analysis used two one-sided t-tests for paired samples to assess crown accuracy in both methods (α = .05). Marginal gaps of crowns made by both methods showed equivalence in the buccal, mesial, and distal regions; however, in the lingual region, the GAID method produced higher marginal discrepancies (P > .001). Regarding internal gaps, no significant difference was observed between the two methods. Crowns produced by the GAID method exhibited larger occlusal discrepancies than those made by the CCAD method (P < .001). The fit accuracy of crowns fabricated using generative artificial intelligence was equivalent to those produced using the manual-input computer design method when the margins were well defined. While marginal and occlusal discrepancies were within clinically acceptable range, careful attention must be given to automated design outcomes, considering various tooth preparation shapes, anatomical structures, and clinical variations.