title: The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis.
abstract: OBJECTIVE
  To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) as a single non-invasive method in detecting prostate cancer (PCa) and to deduce its clinical utility.
  
  
  METHODS
  A systematic literature search was performed to identify relevant original studies. Quality of included studies was assessed by QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). Data were extracted to calculate sensitivity and specificity as well as running the test of heterogeneity and threshold effect. The summary receiver operating characteristic (SROC) curve was drawn and area under SROC curve (AUC) served as a determination of the diagnostic performance of DWI for the detection of PCa.
  
  
  RESULTS
  A total of 21 studies were included, with 27 subsets of data available for analysis. The pooled sensitivity and specificity with corresponding 95% confidence interval (CI) were 0.62 (95% CI 0.61-0.64) and 0.90 (95% CI 0.89-0.90), respectively. Pooled positive likelihood ratio and negative likelihood ratio were 5.83 (95% CI 4.61-7.37) and 0.30 (95% CI 0.23-0.39), respectively. The AUC was 0.8991. Significant heterogeneity was observed. There was no notable publication bias.
  
  
  CONCLUSIONS
  DWI is an informative MRI modality in detecting PCa and shows moderately high diagnostic accuracy. General clinical application was limited because of the absence of standardized DW-MRI techniques.
  
  
  CONCLUSIONS
  • DWI provides incremental information for the detection and evaluation of PCa • DWI has moderately high diagnostic accuracy in detecting PCa • Patient condition, imaging protocols and study design positively influence diagnostic performance • General clinical application requires optimization of image acquisition and interpretation.
authors.affiliation: Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan province, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Jie
authors.forename: Liu
authors.initials: L
authors.lastname: Rongbo
authors.forename: Tan
authors.initials: T
authors.lastname: Ping
mesh_terms: D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D012372:ROC Curve; D015203:Reproducibility of Results