%A Talabani, Ranjdar
%A Baban, Mohammed
%A Mahmood, Mohammed
%T Age estimation using lower permanent first molars on a panoramic radiograph: A digital image analysis
%9 Original Article
%D 2015
%J Journal of Forensic Dental Sciences
%R 10.4103/0975-1475.154597
%P 158-162
%V 7
%N 2
%U http://www.jfds.org/article.asp?issn=0975-1475;year=2015;volume=7;issue=2;spage=158;epage=162;aulast=Talabani
%8 May 1, 2015
%X **Objective:** A study was carried out to analyze the efficacy and practical application for age estimation using digital panoramic radiograph to exploit image analysis to obtain metric measurement of morphological parameters of permanent mandibular first molar on Sulaimani population. **Materials and Methods:** In the present study a population of known age and sex was studied and subjected to digital panoramic radiographic examination. The correlation between the reduction of coronal pulp cavity and chronological age was examined in a sample of 96 individuals distributed into four age groups: 20-29 years (29 cases), 30-39 years (29 cases), 40-49 years (26 cases) and 50-59 years (12 cases). The height (mm) of the crown (CH = coronal height) and the height (mm) of coronal pulp cavity (CPCH = coronal pulp cavity height) of 96 of first molars from all subjects was measured. The tooth-coronal index (TCI) after Ikeda *et al*. was computed for each tooth and regressed on real age. **Results:** ANOVA was used to show the strength of relation between the age and TCI (*P* = 0.0000). The correlation coefficient (r ^{2} ) was 0.49, which mean there is strong negative linear regression between age and TCI with the *r *^{2}, regarding predicting age using TCI value, after the following equation calculated, Predicted age = 3.78 - (0.064 TCI) showed that there is no significant difference between real age and estimated age. **Conclusion:** There is a strong negative liner relationship between TCIs of mandibular first molars with chronological age of Sulaimani population, and age of individuals can therefore be estimated with a good degree of accuracy using regression equations.
%0 Journal Article
%I Wolters Kluwer Medknow Publications
%@ 0975-1475