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Abstract
Differential diagnosis of parkinsonism early upon symptom onset is often challenging for clinicians and stressful for patients. Several neuroimaging methods have been previously evaluated; however specific routines remain to be established. The aim of this study was to systematically assess the diagnostic accuracy of a previously developed 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) based automated algorithm in the diagnosis of parkinsonian syndromes, including unpublished data from a prospective cohort. A series of 35 patients prospectively recruited in a movement disorder clinic in Stockholm were assessed, followed by systematic literature review and meta-analysis. In our cohort, automated image-based classification method showed excellent sensitivity and specificity for Parkinson Disease (PD) vs. atypical parkinsonian syndromes (APS), in line with the results of the meta-analysis (pooled sensitivity and specificity 0.84; 95% CI 0.79–0.88 and 0.96; 95% CI 0.91 –0.98, respectively). In conclusion, FDG-PET automated analysis has an excellent potential to distinguish between PD and APS early in the disease course and may be a valuable tool in clinical routine as well as in research applications.
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Details
1 Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Danderyd’s Hospital, Department of Neurology, Stockholm, Sweden (GRID:grid.412154.7) (ISNI:0000 0004 0636 5158)
2 Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Academic Specialist Center, Center of Neurology, Stockholm, Sweden (GRID:grid.4714.6)
3 The Feinstein Institute for Medical Research, Center for Neurosciences, Manhasset, USA (GRID:grid.250903.d) (ISNI:0000 0000 9566 0634)
4 Karolinska Institutet, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
5 Karolinska University Hospital, Department of Nuclear Medicine, Stockholm, Sweden (GRID:grid.24381.3c) (ISNI:0000 0000 9241 5705)
6 Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Academic Specialist Center, Center of Neurology, Stockholm, Sweden (GRID:grid.4714.6); Karolinska University Hospital, Department of Neurology, Stockholm, Sweden (GRID:grid.24381.3c) (ISNI:0000 0000 9241 5705)