Assessment of virtual bracket removal by artificial intelligence and thermoplastic retainer fit

Abstract

Introduction

Digital orthodontics is here to make our specialty more efficient, and the integration of artificial intelligence (AI) is no exception. This study aimed to compare the accuracy of a workflow involving virtual bracket removal (VBR) by AI to traditional bracket removal. A secondary objective was to compare the clinical fit of thermoplastic orthodontic retainers fabricated from 3-dimensional (3D) printed models created by each method.

Methods

Thirty dental arches were scanned intraorally with the fixed labial orthodontic brackets in place, creating 30 standard tessellation language (STL) files which were labeled “pre-debond.” For each patient, all brackets and residual adhesive were then clinically removed, and an additional intraoral scan was taken and labeled “post-debond.” Each pre-debond scan was uploaded to the uDesign by uLab software (version 7.0; uLab Systems, Inc, Memphis, Tenn), which uses AI to virtually remove orthodontic brackets using 1-touch bracket identification. New STL files were created for each of the 30 arches and labeled VBR. Best fit superimpositions were performed using Geomagic Control X (3D Systems, Inc, Rock Hill, SC), and data were collected as both numerical values and color-coded deviation maps. Superimposition data were segmented for each arch (anterior, posterior right, and posterior left) to determine if the arch location was a relevant factor. All post-debond and VBR STL files were 3D printed. Thermoplastic retainers were fabricated on each 3D-printed model. Retainers were delivered to patients and clinically graded by 2 practitioners.

Results

There was a statistically significant difference in standard deviation and out-of-tolerance percentage values when comparing traditional debonded arches and virtually debonded arches when using sextant locations as a factor (anterior, posterior right, and posterior left). Grading scores for both evaluators show a statistically significant difference for the evaluation of facial surface adaptation and snap-fit acceptability between retainer fabrication methods. However, there was no correlation between out-of-tolerance values and clinical retainer fit evaluation among any of the graded variables in either the maxillary or mandibular arches.

Conclusions

VBR by AI is considered accurate enough to be used for the fabrication of clinically acceptable thermoplastic orthodontic retainers.