Dental Age Estimation Using Cone Beam Computed Tomography and ITK-SNAP Segmentation Software in Canine Pulp Volumes—A Retrospective Study

Abstract

Background: Teeth are preferred in age assessment as they are highly resilient structures. As secondary dentine deposition increases with age, the pulp chamber gradually decreases in size. Objectives: To estimate the human dental age with segmentation software in cone beam computed tomography (CBCT) maxillary and mandibular canine pulp volumes (PV) and compare with chronological age. Methods: Fifty-six CBCT images of both sexes, ranging from 15 to 55 years were selected. A segmentation software was used to measure all permanent canine PV. A regression model was developed, and Pearson's correlation test was used to assess the correlation between chronological age and canine PV. Results: Pearson's correlation coefficients between age and PV are negative for all four canines. Further, the maxillary right canine showed the highest prediction for chronological age and was statistically significant (P < 0.05) with a determination coefficient (R2) of 0.315. A reliable accuracy of age estimation was obtained among age groups between 30 and 40 years with a mean standard error of ± 1.86 years. Conclusion: The study showed that the maxillary right canine PV using segmentation software can be used as a predictive tool in estimating dental age.