Keywords: Parkinson's Disease, Parkinson's Disease, Neuromelanin contrast MRI, AI, clinical trial, longitudinal
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.
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