A parametric head geometry model accounting for variation among adolescent and young adult populations

Background and objective: Modeling the size and shape of human skull and scalp is essential for head injury assessment, design of helmets and head-borne equipment, and many other safety applications. Finite element (FE) head models are important tools to assess injury risks and design personal protective equipment. However, current FE head models are mainly developed based on the midsize male, failing to account for the significant morphological variation that exists in the skull and brain. The objective of this study was to develop a statistical head geometry model that accounts for size and shape variations among the adolescent and young adult population.Methods: To represent subject-specific geometry using a homologous mesh, threshold-based segmentation of head CT scans of 101 subjects between 14 and 25 years of age was performed, followed by landmarking, mesh morphing, and projection. Skull and scalp statistical geometry models were then developed as functions of age, sex, stature, BMI, head length, head breadth, and tragion-to-top of head using generalized Procrustes analysis (GPA), principal component analysis (PCA) and multivariate regression analysis.Results: The statistical geometry models account for a high percentage of morphological variations in scalp geometry (R 2 = 0.63), outer skull geometry (R 2 = 0.66), inner skull geometry (R 2 = 0.55), and skull thickness (error < 1 mm)Conclusions: Skull and scalp statistical geometry models accounts for size and shape variations among the adolescent and young adult population were developed as functions of subject covariates. These models may serve as the geometric basis to develop individualized head FE models for injury assessment and design of head-borne equipment.(c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This study aimed to develop a statistical head geometry model that considers the size and shape variations among the adolescent and young adult population. Head CT scans of 101 subjects between the ages of 14 and 25 were used for threshold-based segmentation, landmarking, mesh morphing, and projection. Statistical geometry models of the skull and scalp were developed as functions of age, sex, stature, BMI, head length, head breadth, and tragion-to-top of head using generalized Procrustes analysis (GPA), principal component analysis (PCA), and multivariate regression analysis. These models can serve as the geometric basis to develop individualized head FE models for injury assessment and the design of head-borne equipment.