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The diagnostic value of SNpc using NM-MRI in Parkinson's disease: meta-analysis.
- Source :
-
Neurological Sciences . Dec2019, Vol. 40 Issue 12, p2479-2489. 11p. 1 Diagram, 3 Charts, 3 Graphs. - Publication Year :
- 2019
-
Abstract
- The main purpose of this study was to systematically evaluate the accuracy of neuromelanin-sensitive magnetic resonance imaging (NM-MRI) in Parkinson's disease (PD) diagnosis using a meta-analysis method. In PubMed, Web of Science, Embase, and Google Scholar, the literatures were searched for the diagnostic value of neuromelanin-sensitive magnetic resonance imaging in PD. The literatures were screened in the light of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data analysis was processed by Stata 12.0 software to obtain meta-analysis, heterogeneity analysis, and publication bias. Meta-analysis results showed by using NM-MRI observed substantia nigra pars compacta (SNpc) on PD, the pooled diagnostic sensitivity and specificity were 0.82 (95% CI, 0.74-0.87) and 0.82 (95% CI, 0.73-0.89), respectively. And the pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 4.58 (95% CI, 3.08-6.82) and 0.22 (95% CI, 0.16-0.31), respectively. Moreover, subgroup analysis according to the measurement criteria of SNpc showed the SNpc volume should be used as good a marker for diagnosing PD. Finally, Fagan test demonstrated that when PLR was equal to 5, the posterior probability is significantly enhanced to 53%, compared with prior probability (20%). As for NLR (0.22), the prior probability is 20%, while the posterior probability remarkably dropped to 5%. In conclusion, SNpc signal detected by NM-MRI exhibited high sensitivity and specificity for diagnosis of PD, which was a high-performance imaging diagnostic method for PD. We recommend NM-MRI imaging technology to be widely used in Parkinson's diagnosis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15901874
- Volume :
- 40
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Neurological Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 139600132
- Full Text :
- https://doi.org/10.1007/s10072-019-04014-y