Neuromelanin-MRI using 2D GRE and deep learning: considerations for improving the visualization of substantia nigra and locus coeruleus

An optimized clinically feasible neuromelanin-MRI imaging protocol for visualising the SN and LC simultaneously using deep learning reconstruction is presented. We optimize flip-angle for optimal combined SN and LC depiction. We also experimented with combinations of anisotropic and isotropic in-plane resolution, partial vs full echoes and the number of averages. Phantom and in-vivo experiments on three healthy volunteers illustrate that high-resolution imaging combined with deep-learning denoising shows good depiction of the SN and LC with a clinically feasible sequence of around 7 minutes.Comment: An article based on ECR and ISMRM abstracts, with more text & figure

Quantitative MRI protocol and decision model for a ‘one stop shop’ early-stage Parkinsonism diagnosis: Study design

Differentiating among early-stage parkinsonisms is a challenge in clinical practice. Quantitative MRI can aid the diagnostic process, but studies with singular MRI techniques have had limited success thus far. Our objective is to develop a multi-modal MRI method for this purpose. In this review we describe existing methods and present a dedicated quantitative MRI protocol, a decision model and a study design to validate our approach ahead of a pilot study. We present example imaging data from patients and a healthy control, which resemble related literature