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The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: A meta-analysis

BACKGROUND: The purpose of this meta-analysis was to evaluate the diagnostic accuracy of perfusion magnetic resonance imaging (MRI) as a method for differentiating glioma recurrence from pseudoprogression. METHODS: The PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were searched...

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Detalles Bibliográficos
Autores principales: Wan, Bing, Wang, Siqi, Tu, Mengqi, Wu, Bo, Han, Ping, Xu, Haibo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5369914/
https://www.ncbi.nlm.nih.gov/pubmed/28296759
http://dx.doi.org/10.1097/MD.0000000000006333
Descripción
Sumario:BACKGROUND: The purpose of this meta-analysis was to evaluate the diagnostic accuracy of perfusion magnetic resonance imaging (MRI) as a method for differentiating glioma recurrence from pseudoprogression. METHODS: The PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were searched comprehensively for relevant studies up to August 3, 2016 according to specific inclusion and exclusion criteria. The quality of the included studies was assessed according to the quality assessment of diagnostic accuracy studies (QUADAS-2). After performing heterogeneity and threshold effect tests, pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Publication bias was evaluated visually by a funnel plot and quantitatively using Deek funnel plot asymmetry test. The area under the summary receiver operating characteristic curve was calculated to demonstrate the diagnostic performance of perfusion MRI. RESULTS: Eleven studies covering 416 patients and 418 lesions were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.88 (95% confidence interval [CI] 0.84–0.92), 0.77 (95% CI 0.69–0.84), 3.93 (95% CI 2.83–5.46), 0.16 (95% CI 0.11–0.22), and 27.17 (95% CI 14.96–49.35), respectively. The area under the summary receiver operating characteristic curve was 0.8899. There was no notable publication bias. Sensitivity analysis showed that the meta-analysis results were stable and credible. CONCLUSION: While perfusion MRI is not the ideal diagnostic method for differentiating glioma recurrence from pseudoprogression, it could improve diagnostic accuracy. Therefore, further research on combining perfusion MRI with other imaging modalities is warranted.