title: Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI.
abstract: OBJECTIVE
  To investigate the added value of computer-aided diagnosis (CAD) on the diagnostic accuracy of PIRADS reporting and the assessment of cancer aggressiveness.
  
  
  METHODS
  Multi-parametric MRI and histopathological outcome of MR-guided biopsies of a consecutive set of 130 patients were included. All cases were prospectively PIRADS reported and the reported lesions underwent CAD analysis. Logistic regression combined the CAD prediction and radiologist PIRADS score into a combination score. Receiver-operating characteristic (ROC) analysis and Spearman's correlation coefficient were used to assess the diagnostic accuracy and correlation to cancer grade. Evaluation was performed for discriminating benign lesions from cancer and for discriminating indolent from aggressive lesions.
  
  
  RESULTS
  In total 141 lesions (107 patients) were included for final analysis. The area-under-the-ROC-curve of the combination score was higher than for the PIRADS score of the radiologist (benign vs. cancer, 0.88 vs. 0.81, p = 0.013 and indolent vs. aggressive, 0.88 vs. 0.78, p < 0.01). The combination score correlated significantly stronger with cancer grade (0.69, p = 0.0014) than the individual CAD system or radiologist (0.54 and 0.58).
  
  
  CONCLUSIONS
  Combining CAD prediction and PIRADS into a combination score has the potential to improve diagnostic accuracy. Furthermore, such a combination score has a strong correlation with cancer grade.
  
  
  CONCLUSIONS
  • Computer-aided diagnosis helps radiologists discriminate benign findings from cancer in prostate MRI. • Combining PIRADS and computer-aided diagnosis improves differentiation between indolent and aggressive cancer. • Adding computer-aided diagnosis to PIRADS increases the correlation coefficient with respect to cancer grade.
authors.affiliation: Department of Radiology, Radboud University Medical Center, 766, Postbus 9101, 6500HB, Nijmegen, The Netherlands. Geert.Litjens@radboudumc.nl.
authors.forename: Geert J S
authors.initials: GJ
authors.lastname: Litjens
authors.affiliation: Department of Radiology, Radboud University Medical Center, 766, Postbus 9101, 6500HB, Nijmegen, The Netherlands.
authors.forename: Jelle O
authors.initials: JO
authors.lastname: Barentsz
authors.affiliation: Department of Radiology, Radboud University Medical Center, 766, Postbus 9101, 6500HB, Nijmegen, The Netherlands.
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
authors.affiliation: Department of Radiology, Radboud University Medical Center, 766, Postbus 9101, 6500HB, Nijmegen, The Netherlands.
authors.forename: Henkjan J
authors.initials: HJ
authors.lastname: Huisman
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D001707:Biopsy, Needle / Q000379:methods; D015331:Cohort Studies; D003287:Contrast Media; D003936:Diagnosis, Computer-Assisted / Q000706:statistics & numerical data*; D038524:Diffusion Magnetic Resonance Imaging / Q000706:statistics & numerical data; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D053783:Magnetic Resonance Imaging, Interventional / Q000379:methods; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011471:Prostatic Neoplasms / Q000145:classification / Q000473:pathology*; D012372:ROC Curve; D012680:Sensitivity and Specificity; D016896:Treatment Outcome
chemical_list: D003287:Contrast Media
keywords: Computer-aided diagnosis; Diagnostic performance; Magnetic resonance imaging; Observer study; Prostate cancer