PET imaging found to distinguish between parkinsonian disorders
Another report this week from David Eidelberg and colleagues demonstrates imaging-based classification was predictive of idiopathic Parkinson's disease, multiple system atrophy and progressive supranuclear palsy in patients two to six years prior to diagnosis.
Patients with parkinsonian features and unclear clinical diagnosis were screened between 1998 and 2006 using 18FDG-PET along with spatial convergence analysis, and accuracy of the initial classification was determined by comparison with the final clinical diagnosis. The findings are as follows:
- Image-based classification for idiopathic Parkinson’s disease had 84% sensitivity, 97% specificity, 98% positive predictive value (PPV), and 82% negative predictive value (NPV).
- Imaging classifications were also accurate for multiple system atrophy (85% sensitivity, 96% specificity, 97% PPV, and 83% NPV) and progressive supranuclear palsy (88% sensitivity, 94% specificity, 91% PPV, and 92% NPV).
This study supports functional PET imaging as a biomarker for early detection of Parkinson's disease, and may have a large impact both in enabling early therapeutic intervention as well as in finding participants for clinical trials.
Chris C Tang,* Kathleen L Poston,* Thomas Eckert, Andrew Feigin, Steven Frucht, Mark Gudesblatt, Vijay Dhawan, Martin Lesser, Jean-Paul Vonsattel, Stanley Fahn, David Eidelberg. Differential diagnosis of parkinsonism: a metabolic imaging study using pattern analysis. Lancet Neurology. Published Online January 11, 2010
DOI:10.1016/S1474-4422(10)70002-8