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

Kui Zhang1, Xiao-Ai Dong1, Fei Fan1

  • 1Department of Forensic Pathology, West China School of Preclinical and Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.

International Journal of Legal Medicine
|May 13, 2016
PubMed
Summary
This summary is machine-generated.

This study developed regression models for age estimation using pelvic radiographs. The models combine iliac crest and ischial tuberosity ossification for accurate chronological age determination.

Keywords:
Age estimationIliac crestIschial tuberosityOssificationRegression analysis

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Area of Science:

  • Forensic Anthropology
  • Radiology
  • Human Osteology

Background:

  • Accurate age estimation is crucial in forensic and clinical contexts.
  • Traditional methods for age assessment have limitations, especially in late adolescence and early adulthood.
  • Pelvic ossification centers, specifically the iliac crest and ischial tuberosity, offer potential for age estimation.

Purpose of the Study:

  • To establish reliable regression models for chronological age estimation.
  • To evaluate the efficacy of combining iliac crest and ischial tuberosity ossification data.
  • To develop formulas for calculating age based on combined developmental status.

Main Methods:

  • Retrospective analysis of 1379 pelvic radiographs.
  • Utilized receiver operating characteristic (ROC) analysis to assess age estimation accuracy at 18 years.
  • Performed cubic regression analysis to develop age estimation formulas.

Main Results:

  • ROC analysis demonstrated good predictive value for the grading systems (Area under ROC curve > 0.9).
  • Cubic regression models achieved high R-squared values (0.744 for females, 0.753 for males).
  • Formulas integrating iliac crest and ischial tuberosity ossification were successfully developed.

Conclusions:

  • The classification scheme for iliac crest and ischial tuberosity ossification is effective for age estimation.
  • The established cubic regression model provides a viable method for chronological age determination.
  • This combined ossification approach offers improved accuracy in age estimation.