Random forest analysis of midbrain hypometabolism using [¹⁸F]-FDG PET identifies Parkinson's disease at the subject-level.

ABSTRACT: Parkinson's disease (PD) is currently diagnosed largely on the basis of expert judgement with neuroimaging serving only as a supportive tool. In a recent study, we identified a hypometabolic midbrain cluster, which includes parts of the substantia nigra, as the best differentiating metabolic feature for PD-patients based on group comparison of [¹⁸F]-fluorodeoxyglucose ([¹⁸F]-FDG) PET scans. Longitudinal analyses confirmed progressive metabolic changes in this region and, an independent study showed great potential of nigral metabolism for diagnostic workup of parkinsonian syndromes. In this study, we applied a machine learning approach to evaluate midbrain metabolism measured by [¹⁸F]-FDG PET as a diagnostic marker for PD. In total, 51 mid-stage PD-patients

SUBMITTER: Ruppert-Junck MC 

PROVIDER: S-EPMC10879348 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature