Voxel based comparison of glucose metabolism in the differential diagnosis of the multiple system atrophy using statistical parametric mapping
A differential diagnosis of idiopathic parkinsonian disease (IPD) and multiple system atrophy (MSA) is difficult due to their common signs and symptoms. The aim of this 18F-2-fluoro-2 deoxyglucose ( 18F-FDG) positron emission tomography (PET) study was to compare the regional cerebral glucose metabo...
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Veröffentlicht in: | Neuroscience research 2005-07, Vol.52 (3), p.211-219 |
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Sprache: | eng |
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Zusammenfassung: | A differential diagnosis of idiopathic parkinsonian disease (IPD) and multiple system atrophy (MSA) is difficult due to their common signs and symptoms. The aim of this
18F-2-fluoro-2 deoxyglucose (
18F-FDG) positron emission tomography (PET) study was to compare the regional cerebral glucose metabolism in MSA with that in IPD by statistical parametric mapping (SPM) and image registration.
The
18F-FDG PET images of MSA and IPD patients were assessed by SPM and image registration to determine metabolic patterns that may be useful in differentiating between the two groups. Eleven patients with MSA, eight patients with IPD and 22 healthy controls participated in the study.
The IPD patients were found to have a significant glucose hypometabolism in comparison with the healthy controls in the prefrontal, lateral frontal, and parietotemporal cortices, and the cingulate and caudate areas (
p
≤
0.01, 100 voxel-level). In patients with MSA, hypometabolism was observed in the putamen, pons, and cerebellum in comparison with the healthy controls and IPD patients.
The voxel-based analysis of
18F-FDG PET images showed detailed differences between IPD and MSA, which may be useful in differentiating the two disease entities, as evidenced by the correlation of glucose metabolism with disease severity and dopamine agonist medication. The mapping analysis of
18F-FDG PET images might be a useful adjunctive method of a differential diagnosis for parkinsonism in a clinical setting. |
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ISSN: | 0168-0102 1872-8111 |
DOI: | 10.1016/j.neures.2005.03.010 |