The measured data were analysed using two-way analysis of variance (ANOVA) followed by Bonferroni’s post hoc test with one categorical independent variable and one continuous variable (the independent variable was the group). Pearson’s correlation coefficients were calculated to determine the correlations. The differences in measured data between females and males and between the dentulous and edentulous groups were analysed using the Student’s t-test. The level of significance was set to p<0.05. Multivariate modelling in PCA was used to estimate the interactions of the measured CBCT data and the differences between the left and right (LR) sides, age, and sex. We performed clustering analyses using the average linkage between groups (hierarchical clustering analysis algorithm) based on the significant components of PCA performed on individuals.17 (link) All statistical analyses were performed using IBM SPSS Statistics Base version 22 (IBM Corporation, New York, USA).