title: The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis.
abstract: The aim of this meta-analysis was to predict the grades of cerebral gliomas using quantitative apparent diffusion coefficient (ADC) values.
  
  
  
  A comprehensive search of the PubMed, EMBASE, Web of Science, and Cochrane Library databases was performed up to 8, 2016. The quality assessment of diagnostic accuracy studies (QUADAS 2) was used to evaluate the quality of studies. Statistical analyses included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio' (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy values of the included studies using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.3), and Meta-Disc 1.4 software programs.
  
  
  
  Fifteen studies were analyzed and included a total of 821 patients and 821 lesions. In regards to the diagnostic accuracy of ADC maps, the pooled SEN, SPE, PLR, NLR, and DOR with 95%CIs were 0.82 [95%CI: 0.76, 0.87] and 0.75 [95%CI: 0.67, 0.81], 3.24 [95%CI: 2.48, 4.24], 0.24 [95%CI: 0.17, 0.33], and 13.60 [95%CI: 8.37, 22.07], respectively. The SROC curve showed an AUC of 0.85. Deeks testing confirmed no significant publication bias in all studies.
  
  
  
  Our findings indicate that quantitative ADC values have high accuracy in separating high-grade from low-grade cerebral gliomas. Further studies using a standardized methodology may help guide the use of ADC values for clinical decision-making.
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China. Electronic address: 18202990355@139.com.
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China.
authors.forename: Zhiqian
authors.initials: Z
authors.lastname: Min
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China.
authors.forename: Min
authors.initials: M
authors.lastname: Tang
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China.
authors.forename: Sipan
authors.initials: S
authors.lastname: Chen
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Lei
authors.affiliation: The Department of MRI, Shaanxi Provincial People's hospital, Beilin District, Xi'an City 710000,Shaanxi Province, China. Electronic address: zxl.822@163.com.
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Zhang
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D038524:Diffusion Magnetic Resonance Imaging; D005910:Glioma / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D060787:Neoplasm Grading
keywords: DWI; Glioma; Grade; MRI, ADC values; Meta analysis