Geometric Scaling Factors for the Pediatric Brainstem

This article presents a method designed to improve geometric scaling factors used to model brainstem injury that adapts current adult brain models to a pediatric model. The authors stress that injuries caused by motor vehicle crashes (MVCs) are the leading cause of death for children in the United States as well as the leading cause of head injury. Improved finite element models that integrate the correct shape of the pediatric brain with current injury prediction metrics would improve occupant response prediction for the pediatric occupant. The method used to assess shape change for this study was a geometric morphometric analysis technique. In this method, a sliding landmark form of a general Procrustes analysis was selected for its ability to compare curved structures with few true landmarks. The method was then tested on a dataset of 59 individuals ranging in age from newborn to 21 years of age, with groups specified at newborn, three months, six months, one year, three years, six years, ten years, fifteen years, and twenty-one years of age. Data was collected by outlining the structure on transverse and sagittal scans of magnetic resonance images and then creating a landmark dataset with a user-defined number of points for each individual. A General Procrustes Analysis was completed for this data set to determine the shape differences between the age groups. The model was then used to calculate the dimensions of the brainstem for each of the specified age groups. The final step was taking the dimensions of the predicted twenty-one year old model as the base and calculating a geometric scaling factor for shape, without including changes in size, for each age group. The authors conclude by stressing the importance of continuing to expand the size of the dataset to better represent the large variation in human anatomy and thus improve the predictive capabilities of this technique.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00678856
• Authors:
  • Danelson, Kerry A
  • Yu, Mao
  • Gayzik, F Scott
  • Geer, Carol P
  • Slice, Dennis E
  • Stitzel, Joel D
• Publication Date: 2008

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 153-158
• Serial:
  • Biomedical Sciences Instrumentation
  • Volume: 44
  • Publisher: Instrument Society of America
  • ISSN: 0067-8856

Subject/Index Terms

• TRT Terms: Anatomical models; Anatomy; Brain; Crash injuries; Crash tests; Crash victim simulation; Nuclear magnetic resonance; Occupant kinetics; Shape
• Uncontrolled Terms: Head and neck injuries; Prognosis
• Subject Areas: Highways; Safety and Human Factors; I84: Personal Injuries;

Filing Info

• Accession Number: 01128500
• Record Type: Publication
• Files: TRIS
• Created Date: May 18 2009 8:37AM