Back to Search Start Over

Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism

Authors :
David Eidelberg
Stanley Fahn
Katharina A Schindlbeck
Jean-Paul Vonsattel
Sarah A. O'Shea
Kathleen L. Poston
Chris C. Tang
Deepak K. Gupta
Vijay Dhawan
Yoon Young Choi
Source :
Eur J Nucl Med Mol Imaging
Publication Year :
2021

Abstract

PURPOSE: Up to 25% of patients diagnosed as idiopathic Parkinson’s disease (IPD) have an atypical parkinsonian syndrome (APS). We had previously validated an automated image-based algorithm to discriminate between IPD, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). While the algorithm was accurate with respect to the final clinical diagnosis after long term expert follow-up, its relationship to the initial referral diagnosis and to the neuropathological gold standard is not known. METHODS: Patients with an uncertain diagnosis of parkinsonism were referred for [(18)F]-fluorodeoxyglucose (FDG) PET to classify patients as IPD or as APS based on the automated algorithm. Patients were followed by a movement disorder specialist and subsequently underwent neuropathological examination. The image-based classification was compared to the neuropathological diagnosis in 15 patients with parkinsonism. RESULTS: At the time of referral to PET, the clinical impression was only 66.7% accurate. The algorithm correctly identified 80% of the cases as IPD or APS (p=0.02) and 87.5% of the APS cases as MSA or PSP (p=0.03). The final clinical diagnosis was 93.3% accurate (p

Details

Language :
English
Database :
OpenAIRE
Journal :
Eur J Nucl Med Mol Imaging
Accession number :
edsair.doi.dedup.....8390da4abaed1ba21c5babea31cb0fbb