| Literature DB >> 24861634 |
Xiangnan Shi1, Libo Cao2, Matthew P Reed3, Jonathan D Rupp4, Carrie N Hoff5, Jingwen Hu6.
Abstract
In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject׳s ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks.Entities:
Keywords: Principal component analysis; Regression; Rib cage geometry; Vulnerable populations
Mesh:
Year: 2014 PMID: 24861634 DOI: 10.1016/j.jbiomech.2014.04.045
Source DB: PubMed Journal: J Biomech ISSN: 0021-9290 Impact factor: 2.712