Accuracy of autonomous robotic buccal alveolar bone reduction for anterior crown lengthening: An in vitro study.

OBJECTIVES

To evaluate the planned-to-actual accuracy of autonomous robotic buccal alveolar bone reduction for anterior crown-lengthening surgery in vitro.

METHODS

Six standardised maxillary anterior typodont models were digitised using intraoral scanning and cone-beam computed tomography. Buccal reduction volumes were planned for teeth 13-23 (36 tooth-level reduction volumes) and executed by an autonomous robotic system. The planned and actual datasets were compared for apical midpoint deviation (AMD), coronal mesial point deviation (CMD), coronal distal point deviation (CDD), directional components, buccal surface deviation, lingual depth deviation, root surface clearance, and reduction volume deviation. Subgroup and correlation analyses were exploratory.

RESULTS

AMD was 0.391 ± 0.243 mm, CMD was 0.598 ± 0.372 mm, and CDD was 0.506 ± 0.292 mm. Planned area coverage was 92.765 ± 4.908%, actual area agreement was 85.974 ± 7.145%, and relative area difference was 8.627 ± 10.891%. The relative volume difference was -5.773 ± 22.531%. Directional deviations differed significantly among the three point locations along the X and Y axes (both P < 0.001), but not along the Z-axis (P = 0.841). The root mean positive distance was 0.558 ± 0.177 mm. Negative root-distance values occurred in 4 of 36 tooth-level reduction volumes from three models, with maximum negative root distances ranging from -0.0106 to -0.6470 mm.

CONCLUSIONS

Autonomous robotic buccal alveolar bone reduction reproduced the planned crown-lengthening geometry with submillimetre point deviations in this in vitro model, demonstrating the potential of this approach to enhance surgical precision. Further clinical studies are needed to validate its accuracy.

CLINICAL SIGNIFICANCE: In this in vitro study, autonomous robotic buccal alveolar bone reduction for anterior crown lengthening achieved submillimetre accuracy. These findings suggest the potential of this approach to enhance surgical precision.