AI based neuromelanin MRI analysis in a multi-site longitudinal Parkinson’s Disease study

Motivation: Neuromelanin (NM) MRI is a proposed biomarker of dopaminergic neurodegeneration in the substantia nigra pars compacta (SNpc). Goal(s): To automate post-hoc analysis on NM-MRI data acquired from a large multi-center clinical trial. Approach: A deep dynamic u-net model was built to segment the SNpc and the background region automatically and was used to analyze a large multi-center longitudinal PD dataset. Results: Within-subject change from baseline effects were significant at the population level for SNpc volume (left and right). These results suggest an AI-derived SNpc volume, estimating the atrophied hyperintense region on an NM-MRI scan, is a viable marker of disease progression in PD. Impact: The dynamic AI model on NM-MRI trained/tested on multiple sites/scanners accurately and robustly delineates the SNpc and may have applicability in trials where NM-MRI is used as a marker of nigrostriatal degeneration.