Importance Of Dental Age Estimation

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Identification is the establishment of a person's individuality and estimation of age is one of its crucial criteria. Forensic age estimation in living or dead individuals is an important and difficult task. Finding an accurate and dependable method to determine age, especially in adults, has become increasingly important (Cameriere et al., 2004; Saxena, 2011; Acharya and Sivapathasundharam, 2012).
Teeth were found to be the most durable and least body parts affected by post-mortem changes. Teeth are resistant to different external influences, mechanical, chemical and thermal insults. It is also observed that tooth development is not perceptibly affected by diseases, drugs, endocrine status as compared to bone, consequently making them the
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Dental age estimation is based on morphological, histological, biochemical and radiological assessment of teeth (Willems, 2001). Dental age prediction in adults is usually done using a number of methods including Gustafson’s parameters, Johanson’s grading, dental translucency, and cementum annulations. Other studies based on amino acid racemization and dental nuclear tests (Zaher et al., 2011). However, these methods are destructive and require extraction of teeth which is unethical and not feasible in living individuals (Bosmans et al., 2005).
Radiograph is a less invasive technique, which can be utilized in both living and dead persons. Dental orthopantomogram has been employed as a helpful tool in forensic medicine. Digital panoramic images have important advantages including; broad coverage, minimal radiation exposure and the brief time frame required for obtaining images (Razi et al., 2009).
The aim of this study was to estimate the age in a sample of Egyptian population based on the relationship between age and measurement of the tooth coronal index (TCI) in the mandibular permanent 1st molars in dental panoramic radiographs and to develop regression equations that can be used in
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For quantitative data, the Shapiro-Wilk test for normality was performed. For data that were not normally distributed median and interquartile range (expressed as 25th -75th percentiles) were calculated and Mann-Whitney test was used for comparison between independent groups while Wilcoxon signed rank test was used to compare related samples. Spearman's correlation was performed. For normally distributed data, values were expressed as mean and standard deviation and independent sample t test was used for comparison between independent groups. For qualitative data, Pearson's Chi-square was used. Simple Linear regression analysis was employed to calculate an equation for prediction of age using TCI in females and males. Significance was adopted at p < 0.05 for interpretation of results of tests (Dawson and Trapp,

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