Physics-informed AI extracts brain fluid flow speeds from MRI data

Researchers at the University of Rochester, Brown University and the University of Copenhagen reported in Science Advances a physics-informed AI method that estimates fluid flow velocity and tissue permeability from MRI data, a measurement the source says MRI alone does not capture for flows this slow. Trained on videos of dye spreading through brain tissue, the models found two glymphatic clearance pathways: fluid moving at a few microns per second in open regions around the brain, and roughly 50 times slower inside dense tissue. The team is establishing baseline measurements in mice and aims to extend the technique to human brains.