Literature DB >> 15955501

FDG PET in the differential diagnosis of parkinsonian disorders.

Thomas Eckert1, Anna Barnes, Vijay Dhawan, Steve Frucht, Mark F Gordon, Andrew S Feigin, D Eidelberg.   

Abstract

The differential diagnosis of parkinsonian disorders can be challenging, especially early in the disease course. PET imaging with [(18)F]-fluorodeoxyglucose (FDG) has been used to identify characteristic patterns of regional glucose metabolism in patient cohorts with idiopathic Parkinson's disease (PD), as well as variant forms of parkinsonism such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBGD). In this study, we assessed the utility of FDG PET in the differential diagnosis of individual patients with clinical parkinsonism. 135 parkinsonian patients were referred for FDG PET to determine whether their diagnosis could be made accurately based upon their scans. Imaging-based diagnosis was obtained by visual assessment of the individual scans and also by computer-assisted interpretation. The results were compared with 2-year follow-up clinical assessments made by independent movement disorders specialists who were blinded to the original PET findings. We found that blinded computer assessment agreed with clinical diagnosis in 92.4% of all subjects (97.7% early PD, 91.6% late PD, 96% MSA, 85% PSP, 90.1% CBGD, 86.5% healthy control subjects). Concordance of visual inspection with clinical diagnosis was achieved in 85.4% of the patients scanned (88.4% early PD, 97.2% late PD, 76% MSA, 60% PSP, 90.9% CBGD, 90.9% healthy control subjects). This study demonstrates that FDG PET performed at the time of initial referral for parkinsonism accurately predicted the clinical diagnosis of individual patients made at subsequent follow-up. Computer-assisted methodologies may be particularly helpful in situations where experienced readers of FDG PET images are not readily available.

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Year:  2005        PMID: 15955501     DOI: 10.1016/j.neuroimage.2005.03.012

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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