Literature DB >> 23458166

Age estimation from radiographic images of the knee.

Lucina Hackman1, Sue Black.   

Abstract

This study examines the reliability of age estimation utilizing the Pyle and Hoerr atlas in relation to a modern Scottish population. The knee radiographs of 442 individuals (168 females, 274 males) were age assessed using the Pyle and Hoerr atlas. Analysis showed that there was a strong correlation between chronological age and estimated age (females R²=0.968, males R²=0.952). For females, the atlas method was most accurate between the ages of 9 and 15 years of age with an underage of 2.27 months and an overage of 2.38 months. For males, the atlas consistently overestimated age from the age of 9 years to the age of 16 years from between 0.14 and 8.81 months. The standard deviation for females was 9.86 months and for males was 10.75 months. This study showed that the Pyle and Hoerr atlas can be applied to a modern population with small modifications.
© 2013 American Academy of Forensic Sciences.

Mesh:

Year:  2013        PMID: 23458166     DOI: 10.1111/1556-4029.12077

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  6 in total

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2.  Variability in developmental timings of the knee in young American children as assessed through Pyle and Hoerr's radiographic atlas.

Authors:  Maureen Schaefer; Lucina Hackman; John Gallagher
Journal:  Int J Legal Med       Date:  2015-01-17       Impact factor: 2.686

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Journal:  Int J Legal Med       Date:  2014-08-19       Impact factor: 2.686

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Authors:  Ivan Galić; Frane Mihanović; Alice Giuliodori; Federica Conforti; Mariano Cingolani; Roberto Cameriere
Journal:  Int J Legal Med       Date:  2016-03-30       Impact factor: 2.686

5.  A biochemical approach for assessing cutoffs at the age thresholds of 14 and 18 years: a pilot study on the applicability of bone specific alkaline phosphatase on an Italian sample.

Authors:  Marco Tisè; Luigi Ferrante; Stefano Mora; Adriano Tagliabracci
Journal:  Int J Legal Med       Date:  2016-05-12       Impact factor: 2.686

6.  Pediatric age estimation from radiographs of the knee using deep learning.

Authors:  Aydin Demircioğlu; Anton S Quinsten; Michael Forsting; Lale Umutlu; Kai Nassenstein
Journal:  Eur Radiol       Date:  2022-03-01       Impact factor: 7.034

  6 in total

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