title: Multiparametric MRI for prostate cancer localization in correlation to whole-mount histopathology.
abstract: OBJECTIVE
  To prospectively evaluate multiparametric magnetic resonance imaging (MRI) for accurate localization of intraprostatic tumor nodules, with whole-mount histopathology as the gold standard.
  
  
  METHODS
  Seventy-five patients with biopsy-proven, intermediate, and high-risk prostate cancer underwent preoperative T2-weighted (T2w), dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MRI at 1.5T. Localization of suspicious lesions was recorded for each of 24 standardized regions of interest on the different MR images and correlated with the pathologic findings. Generalized estimating equations (GEE) were used to estimate the sensitivity, specificity, accuracy, positive, and negative predictive value for every MRI modality, as well as to evaluate the influence of Gleason score and pT-stage. Tumor volume measurements on histopathological specimens were correlated with those on the different MR modalities (Pearson correlation).
  
  
  RESULTS
  DW MRI had the highest sensitivity for tumor localization (31.1% vs. 27.4% vs. 44.5% for T2w, DCE, and DW MRI, respectively; P < 0.005), with more aggressive or more advanced tumors being more easily detected with this imaging modality. Significantly higher sensitivity values were obtained for the combination of T2w, DCE, and DW MRI (58.8%) as compared to each modality alone or any combination of two modalities (P < 0.0001). Tumor volume can most accurately be assessed by means of DW MRI (r = 0.75; P < 0.0001).
  
  
  CONCLUSIONS
  Combining T2w, DCE, and DW imaging significantly improves prostate cancer localization.
authors.affiliation: Department of Radiation Oncology, University Hospitals Leuven, Leuven, Belgium. sofie.isebaert@med.kuleuven.be
authors.forename: Sofie
authors.initials: S
authors.lastname: Isebaert
authors.forename: Laura
authors.initials: L
authors.lastname: Van den Bergh
authors.forename: Karin
authors.initials: K
authors.lastname: Haustermans
authors.forename: Steven
authors.initials: S
authors.lastname: Joniau
authors.forename: Evelyne
authors.initials: E
authors.lastname: Lerut
authors.forename: Liesbeth
authors.initials: L
authors.lastname: De Wever
authors.forename: Frederik
authors.initials: F
authors.lastname: De Keyzer
authors.forename: Tom
authors.initials: T
authors.lastname: Budiharto
authors.forename: Pieter
authors.initials: P
authors.lastname: Slagmolen
authors.forename: Hendrik
authors.initials: H
authors.lastname: Van Poppel
authors.forename: Raymond
authors.initials: R
authors.lastname: Oyen
mesh_terms: D000368:Aged; D000465:Algorithms; D001707:Biopsy, Needle / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011300:Preoperative Care / Q000379:methods; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic