title: Comparison between population average and experimentally measured arterial input function in predicting biopsy results in prostate cancer.
abstract: OBJECTIVE
  To test whether individually measured arterial input function (AIF) provides more accurate prostate cancer diagnosis then population average AIF when dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data are acquired with limited temporal resolution.
  
  
  METHODS
  Twenty-six patients with a high clinical suspicion for prostate cancer and no prior treatment underwent DCE MRI examination at 3.0 T before biopsy. DCE MRI data were fitted to a pharmacokinetic model using three forms of AIF: an individually measured, a local population average, and a literature double exponential population average. Receiver operating characteristic (ROC) analysis was used to correlate MRI with the biopsy results. Goodness of fit (chi(2)) for the three AIFs was compared using nonparametric Mann-Whitney test.
  
  
  RESULTS
  Average volume transfer constant (K(trans)) values were significantly higher in tumor than in normal peripheral zone for all three AIFs. The individually measured and the local population average AIFs had the highest sensitivity (76%), whereas the double exponential AIF had the highest specificity (82%). The areas under the ROC curves were not significantly different between any of the AIFs (0.81, 0.76, and 0.81 for the individually measured, local population average, and double exponential AIFs, respectively). chi(2) was not significantly different for the three AIFs; however, it was significantly higher in enhancing than in nonenhancing regions for all three AIFs.
  
  
  CONCLUSIONS
  These results suggest that, when DCE MRI data are acquired with limited temporal resolution, experimentally measured individual AIF is not significantly better than population average AIF in predicting the biopsy results in prostate cancer.
authors.affiliation: MRI Research Centre, University of British Columbia, Vancouver, BC, Canada.
authors.forename: Ran
authors.initials: R
authors.lastname: Meng
authors.forename: Silvia D
authors.initials: SD
authors.lastname: Chang
authors.forename: Edward C
authors.initials: EC
authors.lastname: Jones
authors.forename: S Larry
authors.initials: SL
authors.lastname: Goldenberg
authors.forename: Piotr
authors.initials: P
authors.lastname: Kozlowski
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008954:Models, Biological; D011471:Prostatic Neoplasms / Q000098:blood supply / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity