Imaging pressure gradients and stress fields driving ISF flow in the brain by assimilating DENSE pulsatile motion data into a poroelastic model.

Motivation: Interstitial fluid (ISF) flow in the brain is important for brain function and therapies. Very slow ISF flow is difficult to directly measure, however, the driving forces can be estimated from pulsatile motion fields. Goal(s): We assimilate pulsatile motions from DENSE sequences into a poroelastic computational model which allows fluid pressure gradient and solid stress fields to be extracted. Approach: Generalized least squares and Galerkin weighted residual methods were used to fit a pulsatile blood pressure field to the data and compute stresses/pressure gradients. Results: Stress and pressure images show good symmetry and distributions are as expected from anatomical considerations. Impact: Imaging the pulsatile fluid pressure gradients and solid stress fields provides new insights into the forces which drive flow of interstitial fluid in the brain, which is of critical importance in Alzheimer’s disease and currently very difficult to directly measure.