Databases with multimodal brain imaging data (FDG-PET, VBM, DTI) will be created. From these data image features and network patterns will be extracted, to be used to create a supervised classification method for associating brain patterns to…
ID
Source
Brief title
Condition
- Movement disorders (incl parkinsonism)
Synonym
Research involving
Sponsors and support
Intervention
Outcome measures
Primary outcome
Network patterns will be extracted from the FDG PET data images. MRI
examinations are used for to specify a precise degree of atrophy (VBM analysis)
and tissue degeneration (DTI analysis). These PET and MRI output data will be
used to define a specific disease related pattern for IPD and MSA.
Secondary outcome
not applicable
Background summary
The differential diagnosis of patients with parkinsonian disorders solely based
on clinical criteria can be difficult, but is particularly important because
they differ in progression, prognosis and treatment responses. A new developed
FDG PET strategy uses multivariate analysis to identify disease-related spatial
covariance patterns. This metabolic network approach is useful to characterise
the unique metabolic patterns in neurodegenerative disorders. It has been
suggested only by one research group, so it is very important to test the
validity of described method in order to create a definite disease related
pattern. Furthermore, published literature about metabolic network activity in
neurodegenerative disorders did not include the precise degree of microscopic
tissue degeneration or atrophy using modern MRI techniques. Voxel based
morphometry (VBM), is a technique that objectively localizes focal grey and
white matter atrophy throughout the entire brain. Diffusion Tensor MRI (DT MRI)
is a quantitative technique that allows microscopic tissue abnormalities to be
assessed non-invasively. It will be necessary to include patterns of atrophy
and tissue degeneration in order to create a reliable and early disease related
pattern. These methods combined can be used to identify an early and specific
diagnosis in individual patients.
Study objective
Databases with multimodal brain imaging data (FDG-PET, VBM, DTI) will be
created. From these data image features and network patterns will be extracted,
to be used to create a supervised classification method for associating brain
patterns to various stages of neurodegenerative diseases.
Study design
In this observational case control study, 15 patients with idiopathic
Parkinson*s disease (IPD) and with 15 patients multiple system atrophy (MSA) as
well as 15 gender- and age matched healthy volunteers will be included. All
subjects will undergo neurological- and neuropsychological examination as well
as 1 FDG PET scan and 1 MRI scan according to protocol.
Study burden and risks
The risks and burden associated with participation are considered negligible
and minimal the since there is great experience in normal diagnostic work up
with these PET and MRI investigations and significant side effects are not
mentioned. This study can not be conducted without the participation of
sufficient subjects in each group. This study can contribute to a better
understanding and early diagnosis in patients with parkinsonian disorders.
Hanzeplein 1 postbus 30 001
9700 RB Groningen
NL
Hanzeplein 1 postbus 30 001
9700 RB Groningen
NL
Listed location countries
Age
Inclusion criteria
patients: fulfill the typical diagnostic criteria of IPD and MSA
volunteers: normal clinical and neuropsychological examination, > 50 years
Exclusion criteria
claustrophobia or other exclusion criteria for MRI scanning
patients: other systemic disease who can cause listed complaints.
Design
Recruitment
Followed up by the following (possibly more current) registration
No registrations found.
Other (possibly less up-to-date) registrations in this register
No registrations found.
In other registers
Register | ID |
---|---|
CCMO | NL25325.042.08 |