title: Diagnostic significance of apparent diffusion coefficient values with diffusion weighted MRI in breast cancer: a meta- analysis.
abstract: OBJECTIVE
  Apparent diffusion coefficient (ADC) values of nodes in diffusion-weighted imaging (DWI) are widely used in differentiating metastatic from non-metastatic lymph nodes. The purpose of this meta-analysis was to demonstrate whether DWI could contribute to the precise diagnosis of breast cancer (BC) with and without lymph node metastasis (LNM).
  
  
  METHODS
  English and Chinese electronic databases were searched for relevant studies followed by a comprehensive literature search. Two reviewers independently assessed the methodological quality of the included trials based on the quality assessment of diagnostic accuracy studies (QUADAS). Summary odds ratios (ORs) and corresponding 95% confidence intervals (95% CIs) were calculated.
  
  
  RESULTS
  Final analysis of 624 BC subjects (patients with LNM = 254, patients without LNM = 370) were incorporated into the current meta-analysis from 9 eligible cohort studies. Combined ORs of ADCs suggested that ADC values in BC patients without LNM were higher than in patients with LNM (OR=0.56, 95%CI: 0.11-1.01, p=0.015). Subgroup analysis stratified by country indicated a low ADC value in BC patients with LNM rather than those without LNM among Chinese (OR=1.27, 95%CI: 0.89-1.66, p<0.001), Italians (OR=0.75, 95%CI: 0.13-1.38, p=0.018), and Egyptians (OR=1.27, 95%CI: 0.71-1.84, p<0.001). The findings of subgroup analysis by MRI machine type revealed that ADC values from diffusion MRI may be potential diagnostic indicators for BC using Non-Philips 1.5T (OR=1.10, 95%CI: 0.84-1.36, p<0.001).
  
  
  CONCLUSIONS
  The main findings of our meta-analysis demonstrated that increased signal intensity on DWI and decreased signals on ADC are helpful in diagnosis of BC patients with or without LNM. DWI could therefore be an important imaging investigation in patients suspected of BC.
authors.affiliation: Department of Radiology, Harbin Medical University Cancer Hospital, China E-mail : sunjianghong703@126.com.
authors.forename: Jiang-Hong
authors.initials: JH
authors.lastname: Sun
authors.forename: Li
authors.initials: L
authors.lastname: Jiang
authors.forename: Fei
authors.initials: F
authors.lastname: Guo
authors.forename: Xiu-Shi
authors.initials: XS
authors.lastname: Zhang
mesh_terms: D001943:Breast Neoplasms / Q000175:diagnosis*; D015331:Cohort Studies; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D012680:Sensitivity and Specificity