Deep learning of 3D T2-weighted MRI provides support for arachnoid granulation hypertrophy in patients with Parkinson’s disease

We apply novel deep learning algorithms using non-contrasted T2-weighted MRI to test hypotheses regarding arachnoid granulation (AG) hypertrophy in patients with Parkinson’s disease (PD). Using this method, we identify AGs protruding into the superior sinus lumen, which may serve as a site of CSF egress implicated in the neurofluid clearance system. Results suggest a significant increase in AG volume in the parietal and frontal lobes of PD participants compared to age-matched healthy controls, potentially indicative of reduced neurofluid clearance efficiency secondary to macromolecular aggregation along the CSF circuit.