Abstract
Objective
To investigate asymmetry in the maxillary volume of subjects with unilateral palatal canine impactions using a novel artificial intelligence (AI)-assisted Cone-beam computed tomography (CBCT) segmentation method.
Methods
Craniofacial CBCT datasets of eleven subjects with unilateral palatal canine impactions were processed with a combination of AI-assisted automatic and investigator-guided segmentation techniques. Post-segmentation, three investigators independently measured the voxel-based volumes of specific maxillary structures, including the impaction and non-impaction maxillary sides, and the maxillary canines.
Results
High inter- and intra-investigator reliability in the volumetric measurements was seen. No significant right-left differences in the volumetric measurements of the skeletal maxillary halves (p = 0.3) or maxillary canines (p = 0.87) was observed in subjects with unilateral palatal canine impactions.
Conclusions
Within study limitations, right-left maxillary volumetric symmetry is observed in subjects with unilateral palatal canine impactions. The study establishes a reliable method for future AI-assisted investigations to understand the aetiology of canine impactions using CBCT datasets.