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

Area of Science:

• Orthodontics and Dental Aesthetics
• Artificial Intelligence in Healthcare
• Digital Smile Design

Background:

• Increasing patient demand for aesthetic smile improvements.
• Need for accurate orthodontic assessment and treatment planning.
• Emergence of AI-driven tools for smile simulation.

Purpose of the Study:

• Evaluate Invisalign SmileView (SV) for simulating predictable orthodontic outcomes.
• Assess SV's anatomical modifications and adherence to orthodontic criteria.
• Analyze SV's ability to align dental and facial midlines.

Main Methods:

• Collected frontal smile photographs from 51 subjects (T0 and T1 post-simulation).
• Analyzed variables: smile width, incisor exposure and dimensions, gingival exposure, and midline alignment.
• Compared collected data with established orthodontic literature standards.

Main Results:

• SV simulations showed dental expansion in 58% of cases, with 8% excessive (>5 mm).
• High predictability for vertical incisor movements; mesiodistal size adjustments noted.
• SV centered the upper midline in 77.9% of simulated cases.

Conclusions:

• SV generates achievable broader smile simulations via aligner treatments.
• Demonstrates high predictability for incisor vertical movements and midline correction.
• Effectively simulates anatomical adjustments for enhanced orthodontic planning.