International Journal of Legal Medicine

, Volume 130, Issue 4, pp 1143–1148 | Cite as

Age estimation based on pelvic ossification using regression models from conventional radiography

Original Article
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Abstract

To establish regression models for age estimation from the combination of the ossification of iliac crest and ischial tuberosity. One thousand three hundred and seventy-nine conventional pelvic radiographs at the West China Hospital of Sichuan University between January 2010 and June 2012 were evaluated retrospectively. The receiver operating characteristic analysis was performed to measure the value of estimation of 18 years of age with the classification scheme for the iliac crest and ischial tuberosity. Regression analysis was performed, and formulas for calculating approximate chronological age according to the combination developmental status of the ossification for the iliac crest and ischial tuberosity were developed. The areas under the receiver operating characteristic (ROC) curves were above 0.9 (p < 0.001), indicating a good prediction of the grading systems, and the cubic regression model was found to have the highest R-square value (R 2 = 0.744 for female and R 2 = 0.753 for male). The present classification scheme for apophyseal iliac crest ossification and the ischial tuberosity may be used for age estimation. And the present established cubic regression model according to the combination developmental status of the ossification for the iliac crest and ischial tuberosity can be used for age estimation.

Keywords

Ossification Iliac crest Ischial tuberosity Age estimation Regression analysis 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No.81373252) and the Applied Basic Research Programs of Science and Technology Commission Foundation of Sichuan Province (No. 2013JY0148).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflicts of interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Kui Zhang
    • 1
  • Xiao-ai Dong
    • 1
  • Fei Fan
    • 1
  • Zhen-hua Deng
    • 1
  1. 1.Department of Forensic Pathology, West China School of Preclinical and Forensic MedicineSichuan UniversityChengduPeople’s Republic of China

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