title: Diffusion-weighted imaging of prostate cancer using a statistical model based on the gamma distribution.
abstract: OBJECTIVE
  To assess the adequacy of a statistical model based on the gamma distribution for diffusion signal decays of prostate cancer (PCa) using b-values ranging up to 2000 sec/mm(2) , and to evaluate the differences in gamma model parameters for PCa, benign prostatic hyperplasia (BPH), and peripheral zone (PZ).
  
  
  METHODS
  Twenty-six patients with histologically proven PCa underwent diffusion-weighted magnetic resonance imaging using five b-values (0, 500, 1000, 1500, 2000 sec/mm(2) ). The acquired signal decay curves were fit with both gamma and truncated Gaussian models and a statistical comparison between the two fits was performed. The acquired parameters using the gamma model (mean, standard deviation, the area fraction for D < 1.0 mm(2) /s [Frac<1.0], the area fraction of D > 3.0 mm(2) /s [Frac>3.0]) were compared between PCa, BPH, and PZ.
  
  
  RESULTS
  The gamma model provided a statistically improved fit over the truncated Gaussian model in PCa. The mean and the standard deviation were significantly lower in PCa than in BPH and PZ (P < 0.01). Frac<1.0 was significantly higher in PCa than in BPH and PZ, and Frac>3.0 was significantly lower in PCa than in BPH and PZ (P < 0.01).
  
  
  CONCLUSIONS
  A statistical model based on the gamma distribution proved suitable for describing diffusion signal decay curves of PCa. This approach may provide better correlation between diffusion signal decay and histological information in the prostate gland.
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Shinmoto
authors.affiliation: Department of Diagnostic Radiology, Keio University School of Medicine, Tokyo, Japan.
authors.forename: Koichi
authors.initials: K
authors.lastname: Oshio
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Chiharu
authors.initials: C
authors.lastname: Tamura
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Shigeyoshi
authors.initials: S
authors.lastname: Soga
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Teppei
authors.initials: T
authors.lastname: Okamura
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Kentaro
authors.initials: K
authors.lastname: Yamada
authors.affiliation: Department of Radiology, National Defense Medical College, Saitama, Japan.
authors.forename: Tastumi
authors.initials: T
authors.lastname: Kaji
authors.affiliation: Department of Radiology, Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.|Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Robert V
authors.initials: RV
authors.lastname: Mulkern
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011470:Prostatic Hyperplasia / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016008:Statistical Distributions
keywords: diffusion-weighted imaging; magnetic resonance imaging; non-Gaussian diffusion; prostate neoplasms; statistical model