Mesh Smoothing Algorithm Applied to a Finite Element Model of the Brain for Improved Brain-Skull Interface.

The brain-skull interface plays an important role in the strain and pressure response of the brain due to impact. In this study, a finite element (FE) model was developed from a brain atlas, representing an adult brain, by converting each 1mm isotropic voxel into a single element of the same size using a custom code developed in MATLAB. This model includes the brain (combined cerebrum and cerebellum), cerebrospinal fluid (CSF), ventricles, and a rigid skull. A voxel-based approach to develop a FE model causes the outer surface of each part to be stair-stepped, which may affect the stress and strain measurements at interfaces between parts. To improve the interaction between the skull, CSF, and brain surfaces, a previously developed mesh smoothing algorithm based on a Laplacian non-shrinking smoothing algorithm was applied to the FE model. This algorithm not only applies smoothing to the surface of the model, but also to the interfaces between the brain, CSF, and skull, while preserving volume and element quality. Warpage, jacobian, aspect ratio, and skew were evaluated and reveal that >99% of the elements retain good element quality. Future work includes implementation of contact definitions to accurately represent the brain-skull interface and to ultimately better understand and predict head injury.