Evaluation of an optimized [18F]fluoro‐deoxy‐glucose positron emission tomography voxel‐wise method to early support differential diagnosis in atypical Parkinsonian disorders. (28th February 2017)

• Record Type: Journal Article
• Authors: Caminiti, S. P.; Alongi, P.; Majno, L.; Volontè, M. A.; Cerami, C.; Gianolli, L.; Comi, G.; Perani, D.
• Is Part Of: European journal of neurology. Volume 24:Number 5(2017:May)
• Page Start: 687
• Page End: e26
• Publication Date: 2017-02-28
• Subjects: biomarkers -- corticobasal degeneration -- dementia with Lewy bodies -- hypometabolism -- multiple system atrophy -- progressive supranuclear palsy -- single subject -- Statistical Parametric Mapping; Neurology -- Periodicals; Nervous system -- Diseases -- Periodicals; 616.8
• DOI: 10.1111/ene.13269
• Languages: English
• ISSNs: 1351-5101

Abstract

Abstract : Background and purpose: Atypical Parkinsonian disorders (APD) frequently overlap in clinical presentations, making the differential diagnosis challenging in the early stages. The present study aimed to evaluate the accuracy of the [ 18 F]fluoro‐deoxy‐glucose positron emission tomography Statistical Parametric Mapping (SPM) optimized procedure in supporting the early and differential diagnosis of APD. Methods: Seventy patients with possible APD were retrospectively included from a large clinical cohort. The included patients underwent [ 18 F]fluoro‐deoxy‐glucose positron emission tomography within 3 months of the first clinical assessment and a diagnostic follow‐up. An optimized SPM voxel‐wise procedure was used to produce t‐maps of brain hypometabolism in single subjects, which were classified by experts blinded to any clinical information. We compared the accuracy of both the first clinical diagnosis and the SPM t‐map classifications with the diagnosis at follow‐up as the reference standard. Results: At first diagnosis, 60% of patients were classified as possible APD (progressive supranuclear palsy, corticobasal degeneration, dementia with Lewy bodies, multiple system atrophy) and about 40% as APD with uncertain diagnosis, providing 52% sensitivity, 97% specificity and 86% accuracy with respect to the reference standard. SPM t‐map classification showed 98% sensitivity, 99% specificity and 99% accuracy, and a significant agreement with the diagnosis at follow‐up ( P < 0.001). Conclusions: The SPM t‐map classification at entry predicted the second diagnosis at follow‐up. This indicates its significantly superior role for an early identification of APD subtypes, particularly in cases of uncertain diagnosis. The use of a metabolic biomarker at entry in the instrumental work‐up of APD may shorten the diagnostic time, producing benefits for treatment options and support to the patients.