title: Mathematical models for diffusion-weighted imaging of prostate cancer using b values up to 2000 s/mm(2) : correlation with Gleason score and repeatability of region of interest analysis.
abstract: OBJECTIVE
  To evaluate four mathematical models for diffusion weighted imaging (DWI) of prostate cancer (PCa) in terms of PCa detection and characterization.
  
  
  METHODS
  Fifty patients with histologically confirmed PCa underwent two repeated 3 Tesla DWI examinations using 12 equally distributed b values, the highest b value of 2000 s/mm(2) . Normalized mean signal intensities of regions-of-interest were fitted using monoexponential, kurtosis, stretched exponential, and biexponential models. Tumors were classified into low, intermediate, and high Gleason score groups. Areas under receiver operating characteristic curve (AUCs) were estimated to evaluate performance in PCa detection and Gleason score classifications. The fitted parameters were correlated with Gleason score groups by using the Spearman correlation coefficient (ρ). Coefficient of repeatability and intraclass correlation coefficient [specifically ICC(3,1)], were calculated to evaluate repeatability of the fitted parameters.
  
  
  RESULTS
  The AUC and ρ values were similar between parameters of monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models. The absolute ρ values for ADCm , ADCk , K, and ADCs were in the range from 0.31 to 0.53 (P < 0.01). Parameters of the biexponential model demonstrated low repeatability.
  
  
  CONCLUSIONS
  In region-of-interest based analysis, the monoexponential model for DWI of PCa using b values up to 2000 s/mm(2) was sufficient for PCa detection and characterization.
authors.affiliation: Department of Diagnostic Radiology, University of Turku, Turku, Finland.|Department of Information Technology, University of Turku, Turku, Finland.
authors.forename: Jussi
authors.initials: J
authors.lastname: Toivonen
authors.affiliation: Department of Information Technology, University of Turku, Turku, Finland.|Turku PET Centre, University of Turku, Turku, Finland.
authors.forename: Harri
authors.initials: H
authors.lastname: Merisaari
authors.affiliation: Department of Diagnostic Radiology, University of Turku, Turku, Finland.
authors.forename: Marko
authors.initials: M
authors.lastname: Pesola
authors.affiliation: Department of Pathology, University of Turku and Turku University Hospital, Turku, Finland.
authors.forename: Pekka
authors.initials: P
authors.lastname: Taimen
authors.affiliation: Department of Urology, Turku University Hospital, Turku, Finland.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Boström
authors.affiliation: Department of Information Technology, University of Turku, Turku, Finland.
authors.forename: Tapio
authors.initials: T
authors.lastname: Pahikkala
authors.affiliation: Department of Diagnostic Radiology, University of Turku, Turku, Finland.|Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland.
authors.forename: Hannu J
authors.initials: HJ
authors.lastname: Aronen
authors.affiliation: Department of Diagnostic Radiology, University of Turku, Turku, Finland.
authors.forename: Ivan
authors.initials: I
authors.lastname: Jambor
mesh_terms: D000368:Aged; D019540:Area Under Curve; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D015203:Reproducibility of Results
keywords: Gleason score; diffusion-weighted imaging; intraclass correlation coefficient; prostate cancer; repeatability