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fPET-based metabolic connectivity and cognition in Parkinson's disease patients

Description

Cognitive decline is one of the most common non-motor symptoms of Parkinson's disease (PD). Mild cognitive impairment (MCI) increases the risk of future dementia, has a significant impact on quality of life and is an enormous burden for family members. Studies on the pathophysiology and prognostic markers of this disease are therefore of great importance. In previous studies, functional magnetic resonance imaging (fMRI) has shown an association between altered functional network connectivity and cognitive impairment in PD patients. However, data from fMRI-based connectivity studies on correlates of non-motor symptoms of PD are currently very heterogeneous. In addition, functional connectivity based on fMRI data is a very indirect measure of neuronal activity. At this point, 18F-FDG PET studies should provide information for the identification of metabolic networks based on a more direct measure of neuronal activity due to the higher specificity of PET. Using innovative dynamic recording protocols, it will be possible to study metabolic connectivity in a time-resolved manner at the individual subject level. This work will be the first to investigate the use of metabolic connectivity at the individual subject level as a measure of network integrity and its association with cognitive parameters. If, in the future, it is possible to use these measurements to infer the stage of damage, the study would be of great use as a diagnostic tool for clinical confirmation and prediction of cognitive development in the course of the disease and, in particular, the development of Parkinson's dementia.

Mrs. Marina Ruppert-Junck, M.Sc.
Telephone: 06421/58 - 65299
Telefax: 06421/58 - 67055
marina.ruppert@*

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