A probability model for estimating age in young individuals relative to key legal thresholds: 15, 18 or 21-year

EASO practical guide on age assessment, 2nd edn (2018) European asylum support office. https://euaa.europa.eu/sites/default/files/easo-practical-guide-on-age-assesment-v3-2018.pdf

Report: Biological evaluation methods to assist in assessing the age of unaccompanied asylum‑seeking children. Interim age estimation science advisory committee, home office UK. Published 0 January 2023. https://www.gov.uk/government/publications/methods-to-assess-the-age-of-unaccompanied-asylum-seeking-children

Anderson M (1971) Use of the Greulich-Pyle “Atlas of Skeletal Development of the Hand and Wrist” in a clinical context. Am J Phys Anthropol 35:347–352. https://doi.org/10.1002/ajpa.1330350309

Article  CAS  PubMed  Google Scholar 

Bachs L, Bleka Ø, Dahlberg PS, Rolseth V, Delaveris G-JM (2020) BioAlder: a tool for using biological tests to assess the age of unaccompanied minor asylum-seekers. BioAlder Manual Version 3b. Oslo Universitetssykehus

Bleka O, Rolseth V, Dahlberg PS, Saade A, Saade M, Bachs L (2019) BioAlder: a tool for assessing chronological age based on two radiological methods. Int J Legal Med 133:1177–1189. https://doi.org/10.1007/s00414-018-1959-5

Article  PubMed  Google Scholar 

Rolseth V, Mosdol A, Dahlberg PS et al (2019) Age assessment by Demirjian’s development stages of the third molar: a systematic review. Eur Radiol 29:2311–2321. https://doi.org/10.1007/s00330-018-5761-z

Article  PubMed  Google Scholar 

Heldring N, Larsson A, Rezaie AR, Rasten-Almqvist P, Zilg B (2022) A probability model for assessing age relative to the 18-year old threshold based on magnetic resonance imaging of the knee combined with radiography of third molars in the lower jaw. Forensic Sci Int 330:111108. https://doi.org/10.1016/j.forsciint.2021.111108

Article  PubMed  Google Scholar 

Kramer JA, Schmidt S, Jurgens KU, Lentschig M, Schmeling A, Vieth V (2014) Forensic age estimation in living individuals using 3.0 T MRI of the distal femur. Int J Legal Med 128:509–514. https://doi.org/10.1007/s00414-014-0967-3

Article  PubMed  Google Scholar 

Schmeling A, Schulz R, Reisinger W, Muhler M, Wernecke KD, Geserick G (2004) Studies on the time frame for ossification of the medial clavicular epiphyseal cartilage in conventional radiography. Int J Legal Med 118:5–8. https://doi.org/10.1007/s00414-003-0404-5

Article  PubMed  Google Scholar 

Ankit R (n.d.) WebPlotDigitizer, ed 4.6. https://automeris.io

Mersmann O, Trautmann H, Steuer D, Bornkamp B (2023) Truncnorm: truncated normal distribution. R package version 1.0–9. https://CRAN.R-project.org/package=truncnorm

Boldsen JL, Milner GR, Konigsberg LW, Wood JW (2002) Transition analysis: a new method for estimating age from skeletons. Paleodemography. Cambridge University Press 2009:73–106. https://doi.org/10.1017/cbo9780511542428.005

Roberts GJ, McDonald F, Andiappan M, Lucas VS (2015) Dental Age Estimation (DAE): data management for tooth development stages including the third molar. Appropriate censoring of Stage H, the final stage of tooth development. J Forensic Leg Med 36:177–184. https://doi.org/10.1016/j.jflm.2015.08.013

Article  PubMed  Google Scholar 

Knell B, Ruhstaller P, Prieels F, Schmeling A (2009) Dental age diagnostics by means of radiographical evaluation of the growth stages of lower wisdom teeth. Int J Legal Med 123:465–469. https://doi.org/10.1007/s00414-009-0330-2

Article  CAS  PubMed  Google Scholar 

Olze A, Pynn BR, Kraul V et al (2010) Studies on the chronology of third molar mineralization in First Nations people of Canada. Int J Legal Med 124:433–437. https://doi.org/10.1007/s00414-010-0483-z

Article  PubMed  Google Scholar 

Bleka O, Wisloff T, Dahlberg PS, Rolseth V, Egeland T (2019) Advancing estimation of chronological age by utilizing available evidence based on two radiographical methods. Int J Legal Med 133:217–229. https://doi.org/10.1007/s00414-018-1848-y

Article  PubMed  Google Scholar 

Varkkola O, Ranta H, Metsaniitty M, Sajantila A (2011) Age assessment by the Greulich and Pyle method compared to other skeletal X-ray and dental methods in data from Finnish child victims of the Southeast Asian Tsunami. Forensic Sci Med Pathol 7:311–316. https://doi.org/10.1007/s12024-010-9173-x

Article  PubMed  Google Scholar 

Gelbrich B, Frerking C, Weiss S et al (2015) Combining wrist age and third molars in forensic age estimation: how to calculate the joint age estimate and its error rate in age diagnostics. Ann Hum Biol 42:389–396. https://doi.org/10.3109/03014460.2015.1046487

Article  PubMed  Google Scholar 

Kumari S, Sahu AK, Rajguru J, Bishnoi P, Garg AJ, Thakur R (2022) Age estimation by dental calcification stages and hand-wrist radiograph. Cureus 14:e29045. https://doi.org/10.7759/cureus.29045

Article  PubMed  PubMed Central  Google Scholar 

Akaike H (1992) Information theory and an extension of the maximum likelihood principle. In: Kotz S, Johnson NL (eds) Breakthroughs in statistics: foundations and basic theory. Springer, New York New York, NY, pp 610–624

Chapter  Google Scholar 

Team RC (2021) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria

Google Scholar 

Venables WN, Ripley BD (2002) Modern Applied Statistics with S, 4th edn. Springer, New York

Kellinghaus M, Schulz R, Vieth V, Schmidt S, Pfeiffer H, Schmeling A (2010) Enhanced possibilities to make statements on the ossification status of the medial clavicular epiphysis using an amplified staging scheme in evaluating thin-slice CT scans. Int J Legal Med 124:321–325. https://doi.org/10.1007/s00414-010-0448-2

Article  PubMed  Google Scholar 

Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag, New York. https://CRAN.R-project.org/package=ggplot2

Ensor J (2023) pmsampsize: sample size for development of a prediction model. R package version 1.1.3. https://CRAN.R-project.org/package=pmsampsize

Riley RD, Debray TPA, Collins GS et al (2021) Minimum sample size for external validation of a clinical prediction model with a binary outcome. Stat Med 40:4230–4251. https://doi.org/10.1002/sim.9025

Article  PubMed  Google Scholar 

Snell KIE, Archer L, Ensor J et al (2021) External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb. J Clin Epidemiol 135:79–89. https://doi.org/10.1016/j.jclinepi.2021.02.011

Article  PubMed  PubMed Central  Google Scholar 

Saade A, Baron P, Noujeim Z, Azar D (2017) Dental and skeletal age estimations in Lebanese children: a retrospective cross-sectional study. J Int Soc Prev Community Dent 7:90–97. https://doi.org/10.4103/jispcd.JISPCD_139_17

Article  PubMed  PubMed Central  Google Scholar 

Wittschieber D, Hahnemann ML, Mentzel HJ (2024) Forensic diagnostics of the skeletal age in the living - backgrounds and methodology. Rofo 196:254–261. https://doi.org/10.1055/a-2130-3162

Article  PubMed  Google Scholar 

Vila-Blanco N, Varas-Quintana P, Tomas I, Carreira MJ (2023) A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches. Int J Legal Med 137:1117–1146. https://doi.org/10.1007/s00414-023-02960-z

Article  PubMed  PubMed Central  Google Scholar 

Manzoor Mughal A, Hassan N, Ahmed A (2014) Bone age assessment methods: a critical review. Pak J Med Sci 30:211–215. https://doi.org/10.12669/pjms.301.4295

Article  PubMed  PubMed Central  Google Scholar 

Pattamapaspong N, Madla C, Mekjaidee K, Namwongprom S (2015) Age estimation of a Thai population based on maturation of the medial clavicular epiphysis using computed tomography. Forensic Sci Int 246(123):e1-5. https://doi.org/10.1016/j.forsciint.2014.10.044

Article  Google Scholar 

Houpert T, Rerolle C, Savall F, Telmon N, Saint-Martin P (2016) Is a CT-scan of the medial clavicle epiphysis a good exam to attest to the 18-year threshold in forensic age estimation? Forensic Sci Int 260(103):e1–e3. https://doi.org/10.1016/j.forsciint.2015.12.007

Article  Google Scholar 

Torimitsu S, Makino Y, Saitoh H et al (2019) Age estimation based on maturation of the medial clavicular epiphysis in a Japanese population using multidetector computed tomography. Leg Med (Tokyo) 37:28–32. https://doi.org/10.1016/j.legalmed.2018.12.003

Article  PubMed  Google Scholar 

Qiu L, Liu A, Dai X et al (2024) Machine learning and deep learning enabled age estimation on medial clavicle CT images. Int J Legal Med 138:487–498. https://doi.org/10.1007/s00414-023-03115-w

Article  PubMed  Google Scholar 

Schmeling A, Grundmann C, Fuhrmann A et al (2008) Criteria for age estimation in living individuals. Int J Legal Med 122:457–460. https://doi.org/10.1007/s00414-008-0254-2

Article  CAS  PubMed  Google Scholar 

Pechnikova M, Gibelli D, De Angelis D, de Santis F, Cattaneo C (2011) The “blind age assessment”: applicability of Greulich and Pyle, Demirjian and Mincer aging methods to a population of unknown ethnic origin. Radiol Med 116:1105–1114. https://doi.org/10.1007/s11547-011-0694-5

Article  CAS  PubMed  Google Scholar 

Schmeling A, Reisinger W, Loreck D, Vendura K, Markus W, Geserick G (2000) Effects of ethnicity on skeletal maturation: consequences for forensic age estimations. Int J Legal Med 113:253–258. https://doi.org/10.1007/s004149900102

Comments (0)

No login
gif