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. 2010 Jul 15;200(1-3):35-40.
doi: 10.1016/j.forsciint.2010.03.024. Epub 2010 Apr 9.

Age estimation using microfocus X-ray computed tomography of lower premolars

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Age estimation using microfocus X-ray computed tomography of lower premolars

H Aboshi et al. Forensic Sci Int. .

Abstract

The dental pulp, like other parts of the body, shows age-related changes. The aim of this study was to develop an age estimation method based on the ratio of the three-dimensional volume of the pulp chamber compared to the total tooth. Pulp chamber volumes were calculated using microfocus X-ray computed tomography (SMX-130CT, Shimadzu, Co., Kyoto, Japan) of the three-dimensional digital radiographic images of teeth. The specimens used in this study were 50 lower first and 50 lower second premolar teeth without caries or other abnormalities, obtained from patients in six 10-year age groups (age range 20-78 years). Each specimen was imaged by a micro-CT to reconstruct the three-dimensional structure. Using the reconstructed images, the tooth and pulp volumes at four levels (crown area (L(1)); coronal one third (L(2)); midroot (L(3)), and apical one third of the root (L(4))) were measured. Mean values of the pulp-tooth volume ratio (PTVR(1-4)) were compared between the six age groups and these values were used as the variables for the multiple regression analysis. The coronal one third of the root (L(2)) showed the greatest ratio values, followed by L(3), L(4) and L(1) in all age groups. Morphological changes of the pulp cavity in different age groups were observed. PTVR gradually reduced in value with increasing age, with the steepest reduction occurring in the 20-50 age range, and most noticeably at the L(2) level. The coefficients of determination by multiple regression analysis for four variables were 0.635 for lower first and 0.703 for lower second premolars. Among the variables used for estimating age by this method, only PTVR(2) showed a significant correlation at P<0.001. To determine the variables with the most significant contribution and to optimize the models, stepwise regression method was applied with inclusion level at P<0.05. Only the variable of PTVR(2) contributed significantly to the fit for lower first premolar whereas the two variables of PTVR(1) and PTVR(2) for lower second premolars. The coefficients of determination for the chosen variables were 0.625 for lower first and 0.698 for lower second premolars. Pulp-tooth volume ratio is an age-dependent variable that can be used to estimate age with reasonable accuracy.

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