Age estimation based on tooth pulp volume using cbct images - Oscandar, Fahmi (2020)
Earlier studies on age estimation were unable to accurately estimate the age of over 20 years of age because they only examined tooth growth and development morphology from 2D radiographs as measurement parameters. In terms of growth and development, the tooth pulp volume will decrease in size over the years and this change can only be seen using 3D radiographs like CBCT. This study proposes that the tooth pulp volume can be used as a measurement parameter in determining age. As far as the author is aware, no study has been conducted regarding the measurement of tooth pulp volume for age estimation in the Deutero-Malay subrace. The general objectives of this study were to evaluate, develop, and optimize dentomaxillofacial radiology using CBCT images for age estimation via tooth pulp volume examination in single-rooted and multi-rooted teeth by gender in the Deutero-Malay subrace. A cross-sectional study was conducted to analyse tooth pulp volume using CBCT (Vatech, Korea) and ITK-SNAP 3.6.0 software. In addition, non-linear/logarithmic regression to examine the correlation between pulp volume decrease in single and multi-rooted teeth and mathematical models for producing the formula for age estimation. This study used CBCT data obtained from 16 types of teeth in selected Deutero-Malay subrace population. The inclusion criteria of the teeth were: without caries, pulpal calcification, and periapical pathology; the shape and size were normal without restorations; without artifacts from metal dental material; visible in detail from CBCT scans; from patients with the chronological age of 10 to 61 years old; and without root canal treatment. In total, 5760 CBCT data were selected. The study was conducted at the Radiology Unit of the Dental Hospital at Universitas Padjadjaran, Bandung Indonesia and Pusat Pengajian Sains Pergigian Universiti Sains Malaysia, Kelantan. Correlation between tooth pulp volume decrease and the increase of could be observed from the regression equation: