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Author Notes:

Email: jwhu@umich.edu

Conceived and designed the experiments: ZL JH. Performed the experiments: ZL WL JZ JR CH JH. Analyzed the data: ZL BP JH. Contributed reagents/materials/analysis tools: MR JR CH JH. Wrote the paper: ZL BP MR JR JH.

The authors would also like to thank Dr. Carol Flannagan, Ms. Prabha Narayanaswamy and Mr. Yuchen Hua from University of Michigan Transportation Research Institute (UMTRI) for their helps on statistical analysis and skull thickness illustration.

The opinions expressed herein are those of the authors and do not necessarily represent those of the funding agencies.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The authors have declared that no competing interests exist.


Research Funding:

This project was supported by the National Institute of Justice (2012-DN-BX-K045) from the U.S., the Foundation of Zhejiang Key Laboratory of Automobile Safety Technology from China and China Postdoctoral Science Foundation (2014T70071).

This study was supported by the National Institute of Justice (2012-DN-BX-K045): MR JR JH; Foundation of Zhejiang Key Laboratory of Automobile Safety Technology from China: ZL WL; China Postdoctoral Science Foundation (2014T70071): ZL.


  • Science & Technology
  • Multidisciplinary Sciences
  • Science & Technology - Other Topics

A Statistical Skull Geometry Model for Children 0-3 Years Old


Journal Title:



Volume 10, Number 5


, Pages e0127322-e0127322

Type of Work:

Article | Final Publisher PDF


Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0-3 YO population. In this study, head CT scans from fifty-six 0-3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

Copyright information:

© 2015 Li et al.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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