Dental age estimation in Somali children and sub-adults combining permanent teeth and third molar development

• Published in: International journal of legal medicine Vol. 133; no. 4; pp. 1207 - 1215
• Main Authors: Metsäniitty, Mari, Waltimo-Sirén, Janna, Ranta, Helena, Fieuws, Steffen, Thevissen, Patrick
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2019; Springer Nature B.V
• Subjects: Adolescent; Adults; Age; Age Determination by Teeth - methods; Bayesian analysis; Child; Child, Preschool; Children; Chronology; Dentition, Permanent; Female; Females; Finland; Forensic Medicine; Forensic odontology; Humans; Image Processing, Computer-Assisted - methods; Male; Males; Medical Law; Medicine; Medicine & Public Health; Molar, Third - diagnostic imaging; Molar, Third - growth & development; Original; Original Article; Performance prediction; Radiographs; Radiography, Dental, Digital - methods; Somalia; Teeth; Young Adult; Somalia; Finland; Dental development; Forensic odontology; Somali; Bayesian age estimation; Forensic age estimation; Age determination
• ISSN: 0937-9827; 1437-1596
• DOI: 10.1007/s00414-019-02053-w

Estimation of an individual’s age has important applications in forensics. In young individuals, it often relies on separate evaluations of permanent teeth (PT) and third molars (TM) development. Here, we analysed the age prediction performance of combined information from PT and TM in an unusual sample of healthy Somalis, born and living in Finland. PT development was staged according to Demirjian et al. ( Hum Biol , 1973) and TM development according to Köhler et al. ( Ann Anat , 1994), using panoramic radiographs from 803 subjects (397 males, 406 females) aged 3–23 years. A sex-specific Bayesian age-estimation model for the multivariate distribution of the stages conditional on age was fitted on PT, TM and PT and TM combined. The age-estimation performances were validated and quantified. The approach combining PT and TM only overestimated age with an ME of − 0.031 years in males and − 0.011 years in females, indicating the best age prediction performance.