title: Diffusion-weighted MRI as a predictor of extracapsular extension in prostate cancer.
abstract: OBJECTIVE
  The objective of our study was to evaluate the value of the apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) as a predictor of extracapsular extension (ECE) in patients with localized prostate cancer.
  
  
  METHODS
  Enrolled in this study were 167 patients who underwent preoperative DWI at 3 T followed by surgery. Univariate and multivariate analyses including clinical variables (serum prostate-specific antigen level, biopsy-based Gleason score, clinical stage, greatest percentage of cancer in all biopsy cores, and presence of perineural invasion) and tumor ADC data were performed for predicting ECE. Receiver operating characteristic curve analysis was also performed to investigate the diagnostic performance of the clinical variables and tumor ADC for predicting ECE.
  
  
  RESULTS
  Histopathologic results indicated that 23 (13.8%) patients had ECE. At univariate analysis, tumor ADC, biopsy-based Gleason score, the presence of perineural invasion, and greatest percentage of cancer in all biopsy cores were associated with ECE (p<0.05). Multivariate analysis revealed that the greatest percentage of cancer in all biopsy cores (p=0.001), biopsy-based Gleason score (p=0.015), and tumor ADC (p=0.032) were independent predictors of ECE. For predicting ECE, the area under the curve (AUC) of tumor ADC was 0.771, which is the second best AUC of all the variables evaluated.
  
  
  CONCLUSIONS
  As an imaging biomarker, tumor ADC may have potential for predicting ECE before surgery in patients with prostate cancer. Further studies investigating this possibility are warranted.
authors.affiliation: 1 All authors: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Gangnam-gu, Seoul 135-710, Republic of Korea.
authors.forename: Chan Kyo
authors.initials: CK
authors.lastname: Kim
authors.forename: Sung Yoon
authors.initials: SY
authors.lastname: Park
authors.forename: Jung Jae
authors.initials: JJ
authors.lastname: Park
authors.forename: Byung Kwan
authors.initials: BK
authors.lastname: Park
mesh_terms: D000368:Aged; D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D011379:Prognosis; D011467:Prostate / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity