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 [F-18]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 [F-18]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.