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A replication study...
A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism
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- Papathoma, PE (author)
- Karolinska Institutet
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- Markaki, I (author)
- Karolinska Institutet
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Tang, C (author)
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Lindstrom, ML (author)
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Savitcheva, I (author)
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Eidelberg, D (author)
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- Svenningsson, P (author)
- Karolinska Institutet
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(creator_code:org_t)
- 2022-02-17
- 2022
- English.
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1, s. 2763-
- Related links:
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https://www.nature.c...
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http://kipublication...
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https://doi.org/10.1...
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Abstract
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- 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positron emission tomography (FDG-PET) based automated algorithm in the diagnosis of parkinsonian syndromes, including unpublished data from a prospective cohort.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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