Artificial Intelligence in Aesthetic Dentistry: Is Treatment with Aligners Clinically Realistic?

Smile aesthetics are increasingly prioritized in dental practice, with accurate orthodontic assessment and treatment planning being crucial for optimal outcomes. This study evaluates Invisalign^® SmileView™ (SV), an AI-based tool that simulates post-treatment smiles, focusing on its ability to present potential orthodontic outcomes to patients. Background/Objectives: This research aims to study whether SV can simulate predictable orthodontic results and if it makes anatomical modifications to the teeth. Additionally, it will evaluate whether SV displays smiles that conform to the orthodontic criteria described in the literature. Finally, the study will analyze whether the software can align the dental with the facial midline. Methods: A total of 51 subjects were recruited in Madrid, Spain. The operator took a frontal photograph of the subjects with a social smile (T0), following the application's instructions. Subsequently, the subjects followed the steps to modify their smile (T1), resulting in a new image of the subject with a different smile. The following variables were collected, analyzed, and compared with the standards defined in the literature: smile width, vertical exposure of the maxillary central incisor, width of the maxillary central and lateral incisors, proportion of the maxillary lateral incisor width to the central incisor, anterior gingival exposure level, position of the upper and lower dental midlines relative to the facial midline. Results: 58% of the sample showed dental expansion, with an excessive expansion (>5 mm) observed in 8%. In the maxillary arch, 5.9% of incisors exceeded predictable aligner movement (>1.5 mm), with 3.9% showing excessive extrusion and 2% excessive intrusion. For the lateral incisors, the mesiodistal size was reduced less than 0.5 mm in 31.4% of cases, with excessive interproximal reduction (>0.5 mm) in 5.9%. Additionally, 62.7% of cases would require multidisciplinary treatment due to an increase in size. SV centered the upper midline in 77.9% of these cases. Among the sample, the upper midline was initially centered in 74.5% of subjects, and SV maintained it centered in 84.2% of these subjects. Conclusions: SV tends to generate simulations of broader smiles, which are mostly achievable through aligner treatments, from an orthodontic perspective, and showed high predictability regarding the vertical movements of the incisors that can be achieved with aligners. Moreover, it adjusted the mesiodistal size of the upper incisors in its simulations and demonstrated the ability to identify and correct deviations of the dental midlines relative to the facial midline.