A statistical human rib cage geometry model accounting for variations by age, sex, stature and body mass index

• Published in: Journal of biomechanics Vol. 47; no. 10; pp. 2277 - 2285
• Main Authors: Shi, Xiangnan, Cao, Libo, Reed, Matthew P., Rupp, Jonathan D., Hoff, Carrie N., Hu, Jingwen
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 18.07.2014; Elsevier Limited
• Subjects: Accuracy; Adolescent; Adult; Age; Aged; Aged, 80 and over; Body Mass Index; Body Size; Female; Females; Geometry; Humans; Injuries; Linear Models; Male; Medical imaging; Middle Aged; Models, Anatomic; Multivariate Analysis; Physical Medicine and Rehabilitation; Population; Principal Component Analysis; Principal components analysis; Radiography, Thoracic; Regression; Regression Analysis; Rib cage geometry; Ribs - physiology; Sex Characteristics; Studies; Thorax - physiology; Tomography, X-Ray Computed; Vulnerable populations; Young Adult; United States > US; Regression; Rib cage geometry; Vulnerable populations; Principal component analysis
• ISSN: 0021-9290; 1873-2380; 1873-2380
• DOI: 10.1016/j.jbiomech.2014.04.045

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.