title: Evaluation of the PI-RADS scoring system for classifying mpMRI findings in men with suspicion of prostate cancer.
abstract: OBJECTIVE
  To evaluate the ESUR scoring system (PI-RADS) for multiparametric MRI of the prostate in clinical routine and to define a reliable way to generate an overall PI-RADS score.
  
  
  METHODS
  Retrospective analysis of all patients with a history of negative prebiopsies, who underwent 3 Tesla multiparametric MRI from October 2011 to April 2013 (n = 143): PI-RADS scores for each single modality were defined. To generate the overall PI-RADS score, an algorithm based approach summing up each single-modality score to a sum-score was compared to a more subjective approach, weighting the single modalities dependent on the radiologist's impression. Because of ongoing cancer suspicion 73 patients underwent targeted mpMRI-ultrasound image fusion rebiopsy. For this group thresholds for tumor incidences and malignancy were calculated.
  
  
  RESULTS
  39 (53%) out of 73 targeted rebiopsies were cancer positive. The PI-RADS score correlated well with tumor incidence (AUC of 0.86, 95% CI 0.78 to 0.94) and malignancy (AUC 0.84, 95% CI 0.68 to 0.99). Regarding the sum-score a threshold of ≥ 10 turned out to be reliable for cancer detection (sensitivity 90%, specificity 62%) and for ≥ 13 for indicating higher malignancy (Gleason ≥ 4 + 3) (sensitivity 80%, specificity 86%). To generate the overall PI-RADS score, the use of an algorithm based approach was more reliable than that of the approach based on the radiologist's impression.
  
  
  CONCLUSIONS
  The presented scoring system correlates well with tumor incidence and malignancy. To generate the overall PI-RADS score, it seems to be advisable to use an algorithm based instead of a subjective approach.
authors.affiliation: Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Daniel
authors.initials: D
authors.lastname: Junker
authors.affiliation: Department of Pathology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria ; Department of Urology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Georg
authors.initials: G
authors.lastname: Schäfer
authors.affiliation: Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Schöpfstraße 41/1, 6020 Innsbruck, Austria.
authors.forename: Michael
authors.initials: M
authors.lastname: Edlinger
authors.affiliation: Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Kremser
authors.affiliation: Department of Urology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Jasmin
authors.initials: J
authors.lastname: Bektic
authors.affiliation: Department of Urology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Horninger
authors.affiliation: Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Werner
authors.initials: W
authors.lastname: Jaschke
authors.affiliation: Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
authors.forename: Friedrich
authors.initials: F
authors.lastname: Aigner
mesh_terms: D001706:Biopsy; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000145:classification*; D008297:Male; D008875:Middle Aged; D011467:Prostate / Q000473:pathology; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D012372:ROC Curve; D012107:Research Design; D014465:Ultrasonics