A statistical geometrical description of the human liver for probabilistic occupant models

Realistic numerical assessments of liver injury risk for the entire occupant population require incorporating inter-subject variations into numerical models. Statistical shape models of the abdominal organs have been shown to be useful tools for the investigation of the organ variations and could be applied to the development of statistical computational models. The main objective of this study was to establish a standard procedure to quantify the shape variations of a human liver in a seated posture, and construct three-dimensional (3D) statistical shape boundary models. Statistical shape analysis was applied to construct shape models of 15 adult human livers. Principal component analysis (PCA) was then utilized to obtain the modes of variation, the mean model, and a set of statistical boundary shape models, which were constructed using the q-hyper-ellipsoid approach. The first five modes of a human liver accounted for the major anatomical variations. The modes were highly correlated to the height, thickness, width, and curvature of the liver, and the concavity of the right lobe. The mean model and the principal components were utilized to construct four boundary models of human liver. The statistical boundary model approach presented in this study could be used to develop probabilistic finite element (FE) models. In the future, the probabilistic liver models could be used in FE simulations to better understand the variability in biomechanical responses and abdominal injuries under impact loading.