ongitudinal ultra-high field imaging in Parkinson*s Disease: Tracking the disease course
- Conditions
- Parkinson's disease10028037
- Registration Number
- NL-OMON54720
- Lead Sponsor
- niversiteit Maastricht
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- Not specified
- Target Recruitment
- 190
Inclusion criteria for Parkinson's disease patients:
-18 years of age or older.
-Recently diagnosed idiopathic Parkinson's Disease according to the UK Brain
Bank Criteria (<=3 year after diagnosis)., Inclusion criteria for healthy
controls:
-The age and sex of healthy control subjects should not significantly differ
from the age and sex of the PD patients
Exclusion criteria for all subjects:
-Subjects with contra-indications for a MRI scan as defined in the MRI
screenings form of Scannexus (Appendix E), such as claustrophobia or subjects
carrying incompatible metallic devices such as pacemakers and certain
mechanical valves.
-Advanced cognitive impairment (MoCA <24) or dementia according to the DSM V
criteria at baseline.
-Subjects with other neurodegenerative diseases.
Study & Design
- Study Type
- Observational invasive
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method <p>The main study endpoint will be the structural and functional changes of the PD<br /><br>brain as compared to HC, which will be assessed on 7T ultra-high field MR<br /><br>images. We will also use quantitative MRI approaches, since this enables us to<br /><br>detect small structural and anatomical differences which cannot be detected on<br /><br>qualitative MRI acquisitions. Our aim is to create a diagnostic tool, based on<br /><br>MRI characteristics, which can distinguish PD patients from HC.</p><br>
- Secondary Outcome Measures
Name Time Method <p>A secondary study endpoint will be the detection of differences in imaging<br /><br>characteristics between clinically dissimilar subtypes of PD. We aim to<br /><br>correlate clinical phenotype, genetic characteristics and progression of<br /><br>symptoms to functional and structural MRI variations. This requires a<br /><br>longitudinal follow-up, which enables us to establish in what manner<br /><br>progression of clinical symptoms is related to certain neuroimaging<br /><br>characteristics. Furthermore, our aim is to develop a patient specific<br /><br>prognostic model based on MRI characteristics, which can (partially) predict<br /><br>the disease course for the individual patient.<br /><br>Moreover, we aim to assess the potential of brain-enriched EV miRNAs in blood<br /><br>to distinguish PD from the healthy population. </p><br>