Phuwadon Duangto1, Apirum Janhom2, Sukon Prasitwattanaseree3, Pasuk Mahakkanukrauh4, Anak Iamaroon5. 1. Graduate Program in Forensic Osteology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand. Electronic address: pete_anatomy@hotmail.com. 2. Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand. Electronic address: ajanhom@gmail.com. 3. Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; Excellence Center in Osteology Research and Training Center (ORTC), Chiang Mai University, Chiang Mai 50200, Thailand; Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand. Electronic address: sprasitwattanaseree@gmail.com. 4. Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; Excellence Center in Osteology Research and Training Center (ORTC), Chiang Mai University, Chiang Mai 50200, Thailand; Department of Anatomy, Faculty of Medicine, Chiang Mai University, Chiang Mai50200, Thailand. Electronic address: pasuk034@gmail.com. 5. Forensic Osteology Research Center (FORC), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand; Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand; Excellence Center in Osteology Research and Training Center (ORTC), Chiang Mai University, Chiang Mai 50200, Thailand. Electronic address: iamaroon@yahoo.com.
Abstract
UNLABELLED: The aims of this study were to develop new prediction models for dental age estimation and to test the accuracy of the resulting models in comparison with the Demirjian et al. and the Willems et al. methods in Thai children and adolescents. Digital panoramic radiographs of 1,134 Thai individuals (487 males and 647 females) aged from 6 to 15 years were selected and evaluated for dental age estimation. Quadratic regression was used to generate new models. The results showed that the new prediction models indicated a strong correlation coefficient between the dental maturity score and the chronological age in both sexes (r=0.951 for males, r=0.945 for females). The new age prediction models were: y=0.006297x(2) - 0.804930x+32.591843 for males and y=0.010677x(2) - 1.538823x+61.955056 for females, where y is the dental age, x is the dental maturity score according to Demirjian et al. METHOD: Moreover, these new models were tested showing the greatest accuracy for estimating the age in Thai samples using the mean difference values between the dental and the chronological ages (-0.04 years for males, 0.02 years for females) when compared with the Demirjian et al. and the Willems et al. METHODS: In addition, the new models revealed a high percentage of accuracy in the absolute difference values between the dental and the chronological ages within 1 year (76.26% and 74.49% for males and females, respectively). Furthermore, our results in mean difference values indicated that the Demirjian et al. method (0.11 and 0.10 years for males and females, respectively) was more accurate than the Willems et al. method (-0.37 and -0.39 years for males and females, respectively) in Thai samples. In conclusion, the new age prediction models in this study provide accurate age estimation in both sexes, suggesting that these models be applied for forensic age estimation, especially in Thai children and adolescents.
UNLABELLED: The aims of this study were to develop new prediction models for dental age estimation and to test the accuracy of the resulting models in comparison with the Demirjian et al. and the Willems et al. methods in Thai children and adolescents. Digital panoramic radiographs of 1,134 Thai individuals (487 males and 647 females) aged from 6 to 15 years were selected and evaluated for dental age estimation. Quadratic regression was used to generate new models. The results showed that the new prediction models indicated a strong correlation coefficient between the dental maturity score and the chronological age in both sexes (r=0.951 for males, r=0.945 for females). The new age prediction models were: y=0.006297x(2) - 0.804930x+32.591843 for males and y=0.010677x(2) - 1.538823x+61.955056 for females, where y is the dental age, x is the dental maturity score according to Demirjian et al. METHOD: Moreover, these new models were tested showing the greatest accuracy for estimating the age in Thai samples using the mean difference values between the dental and the chronological ages (-0.04 years for males, 0.02 years for females) when compared with the Demirjian et al. and the Willems et al. METHODS: In addition, the new models revealed a high percentage of accuracy in the absolute difference values between the dental and the chronological ages within 1 year (76.26% and 74.49% for males and females, respectively). Furthermore, our results in mean difference values indicated that the Demirjian et al. method (0.11 and 0.10 years for males and females, respectively) was more accurate than the Willems et al. method (-0.37 and -0.39 years for males and females, respectively) in Thai samples. In conclusion, the new age prediction models in this study provide accurate age estimation in both sexes, suggesting that these models be applied for forensic age estimation, especially in Thai children and adolescents.
Authors: Ivan Bedek; Jelena Dumančić; Tomislav Lauc; Miljenko Marušić; Ivana Čuković-Bagić Journal: Int J Legal Med Date: 2019-04-30 Impact factor: 2.686