Three-dimensional quantification of mandibular asymmetries in Caucasian adult patients with different sagittal and vertical skeletal patterns. A cone beam study using 3D segmentation and mirroring procedures

Abstract

Abstract Introduction An accurate identification of mandibular asymmetries is required by modern orthodontics and orthognathic surgery to improve diagnosis and treatment planning of such deformities. Although craniofacial deformities are very frequent pathologies, some types of asymmetries can be very difficult to assess without the proper diagnostic tools. The purpose of this study was to implement the usage of three-dimensional (3D) segmentation procedures to identify asymmetries at the mandibular level in adult patients with different vertical and sagittal patterns where the asymmetries could go unnoticed at the observational level. Methods The study sample comprised 60 adult patients (33 women and 27 men, aged between 18 and 60 years). Subjects were divided into 3 sagittal and vertical skeletal groups. CBCT images were segmented, mirrored and voxel-based registered with reference landmarks using ITK-SNAP® and 3DSlicer® software’s. 3D surface models were constructed to evaluate the degree of asymmetry at different anatomical levels. Results There was a degree of asymmetry, with the left hemimandible tending to contain the right one (0.123 ± 0.270 mm (CI95% 0.036–0.222; p < 0.001). Although the subjects under study did not present significant differences between mandibular asymmetries and their sagittal or vertical skeletal pattern (p = 0.809 and p = 0.453, respectively), a statistically significant difference has been found depending on the anatomical region (p < 0.001; CI95%=1.020–1.021), being higher in the condyle, followed by the ramus and the corpus. Conclusions Although mandibular asymmetries cannot be correlated with vertical and sagittal skeletal patterns in symmetric patients, knowledge about 3D segmentation procedures and color maps can provide valuable information to identify mandibular asymmetries.

Keywords

• Mandibular asymmetry
• Skeletal patterns
• 3D segmentation
• CBCT