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CT-assisted age estimation from the medial clavicular epiphysis in the Greek population according to Schmeling and Kellinghaus classification
Region Östergötland, Center for Diagnostics, Clinical pathology. Univ Crete, Greece.
Univ Crete, Greece.
Region Östergötland, Center for Diagnostics, Clinical pathology.
Univ Hosp Heraklion, Greece; Fdn Res & Technol FORTH, Greece; Univ Crete, Greece.
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2025 (English)In: Legal Medicine, ISSN 1344-6223, E-ISSN 1873-4162, Vol. 73, article id 102589Article in journal (Refereed) Published
Abstract [en]

Examining the clavicle by macroscopic or radiologic techniques is a well-established method in forensic age estimation in living and dead individuals. The present study examined 196 CT (computed tomography scan) images of native patients from the archive of the medical imaging laboratory of the University Hospital in Heraklion, Crete, in Greece. The ossification of the medial clavicular epiphysis was classified according to Schmeling et al. and the extended amplified staging system of Kellinghaus et al. Next, a stage transition analysis was carried out according to the Bayesian model. Probability density functions were calculated using informative priors for age distribution in the total population, deceased and violently deceased individuals. Our study showed that when the medial clavicular epiphysis’ ossification is sorted in stages 4 and 5 in Greek males and females, the cumulative probability of adulthood (≥18 years) is nearly 1. As far as Greek males are concerned, in stage 3c, the cumulative probability of adulthood (≥18 years) is 0.86, and in Greek females in stage 3c, the cumulative probability of adulthood (≥18 years) is 0.97. This is the first study of age estimation based on the ossification of the sternal clavicular end using CT in a Greek population.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD , 2025. Vol. 73, article id 102589
Keywords [en]
Clavicle; Medial clavicular epiphysis; Age estimation; CT (computed tomography scan); Greece; Transition analysis; Bayesian model
National Category
Medical Genetics and Genomics
Identifiers
URN: urn:nbn:se:liu:diva-211683DOI: 10.1016/j.legalmed.2025.102589ISI: 001416068000001PubMedID: 39883973Scopus ID: 2-s2.0-85216355732OAI: oai:DiVA.org:liu-211683DiVA, id: diva2:1938103
Available from: 2025-02-17 Created: 2025-02-17 Last updated: 2025-02-17

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