A semi-automatic method of generating subject-specific pediatric head finite element models for impact dynamic responses to head injury

Abstract

To account for the effects of head realistic morphological feature variation on the impact dynamic responses to head injury, it is necessary to develop multiple subject-specific pediatric head finite element (FE) models based on computed tomography (CT) or magnetic resonance imaging (MRI) scans. However, traditional manual model development is very time-consuming. In this study, a new automatic method was developed to extract anatomical points from pediatric head CT scans to represent pediatric head morphological features (head size/shape, skull thickness, and suture/fontanel width). Subsequently, a geometry-adaptive mesh morphing method based on radial basis function was developed that can automatically morph a baseline pediatric head FE model into target FE models with geometries corresponding to the extracted head morphological features. In the end, five subject-specific head FE models of approximately 6-month-old (6MO) were automatically generated using the developed method. These validated models were employed to investigate differences in the head dynamic responses among subjects with different head morphologies. The results show that variations in head morphological features have a relatively large effect on pediatric head dynamic response. The results of this study indicate that pediatric head morphological variation had better be taken into account when reconstructing pediatric head injury due to traffic/fall accidents or child abuses using computational models as well as predicting head injury risk for children with obvious difference in head size and morphologies.