A parametric ribcage geometry model accounting for variations among the adult population

• Published in: Journal of biomechanics Vol. 49; no. 13; pp. 2791 - 2798
• Main Authors: Wang, Yulong, Cao, Libo, Bai, Zhonghao, Reed, Matthew P., Rupp, Jonathan D., Hoff, Carrie N., Hu, Jingwen
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 06.09.2016; Elsevier Limited
• Subjects: Accounting; Adolescent; Adult; Adult population; Adults; Age; Aged; Aged, 80 and over; Body Mass Index; Body size (biology); Child; Child, Preschool; Colleges & universities; Estimating; Female; Finite Element Analysis; Finite element method; Geometry; Human characteristics; Humans; Identification; Infant; Infant, Newborn; Injuries; Linear Models; Male; Mathematical models; Medical imaging; Middle Aged; Models, Anatomic; Morphological variation; Morphology; Parametric model; Physical Medicine and Rehabilitation; Principal Component Analysis; Principal components analysis; Regression Analysis; Rib Cage - anatomy & histology; Rib Cage - diagnostic imaging; Ribcage; Sex; Thorax; Tomography, X-Ray Computed; Vertebrae; Young Adult; Morphological variation; Ribcage; Adult population; Parametric model; Human characteristics
• ISSN: 0021-9290; 1873-2380
• DOI: 10.1016/j.jbiomech.2016.06.020

The objective of this study is to develop a parametric ribcage model that can account for morphological variations among the adult population. Ribcage geometries, including 12 pair of ribs, sternum, and thoracic spine, were collected from CT scans of 101 adult subjects through image segmentation, landmark identification (1016 for each subject), symmetry adjustment, and template mesh mapping (26,180 elements for each subject). Generalized procrustes analysis (GPA), principal component analysis (PCA), and regression analysis were used to develop a parametric ribcage model, which can predict nodal locations of the template mesh according to age, sex, height, and body mass index (BMI). Two regression models, a quadratic model for estimating the ribcage size and a linear model for estimating the ribcage shape, were developed. The results showed that the ribcage size was dominated by the height (p=0.000) and age–sex-interaction (p=0.007) and the ribcage shape was significantly affected by the age (p=0.0005), sex (p=0.0002), height (p=0.0064) and BMI (p=0.0000). Along with proper assignment of cortical bone thickness, material properties and failure properties, this parametric ribcage model can directly serve as the mesh of finite element ribcage models for quantifying effects of human characteristics on thoracic injury risks.