Computational modeling of cerebral diffusion-application to stroke imaging.

Water diffusion within the structure of a brain extracellular space is analyzed numerically for various diffusion parameters of brain tissue namely extracellular space porosity and tortuosity. An algorithm for predicting diffusion pattern of water molecules within human brain considering the mechanics of water diffusion within porous media is developed. The extracellular space is modeled as a homogeneous porous medium with uniform porosity and permeability. Discretization of the fluid flow, heat transfer and mass transport equations is achieved using a finite element scheme based on the Galerkin method of weighted residuals. Concentration maps are developed in this study for various clinical conditions. The effect of the space porosity and the turtousity on the heat and mass transport within the extracellular space are found to be significant. The results presented in this work play an important role in producing more effective imaging techniques for brain injury based on the apparent diffusion coefficient.