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Meta-Analysis
. 2022 Feb 17;12(1):2763.
doi: 10.1038/s41598-022-06663-0.

A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism

Paraskevi-Evita Papathoma #  1   2 , Ioanna Markaki #  3   4 , Chris Tang  5 , Magnus Lilja Lindström  6 , Irina Savitcheva  7 , David Eidelberg  5 , Per Svenningsson  1   8   9
Affiliations
Meta-Analysis

A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism

Paraskevi-Evita Papathoma et al. Sci Rep. .

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positron emission tomography (FDG-PET) based automated algorithm in the diagnosis of parkinsonian syndromes, including unpublished data from a prospective cohort.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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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Assessment of risk of bias and concerns regarding applicability of the included studies using the Quality Assessment of Diagnostic Accuracy Studies Tool 2.
Figure 2
Figure 2
Flowchart of the successive steps of the systematic review process.
Figure 3
Figure 3
Forest plot of the included studies presenting sensitivity and specificity of each study along with the combined measures—first level of classification model, PD vs APS.
Figure 4
Figure 4
Level-1 classification algorithm for PD: Summary ROC plot with mean operating sensitivity and specificity point.
Figure 5
Figure 5
Level-2 classification algorithm for MSA: Summary ROC plot with mean operating sensitivity and specificity point.
Figure 6
Figure 6
Level-2 classification algorithm for PSP: Summary ROC plot with mean operating sensitivity and specificity point.
See this image and copyright information in PMC

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