title: Diffusion-weighted magnetic resonance imaging of the prostate:  improved robustness with stretched exponential modeling.
abstract: OBJECTIVE
  This study aimed to compare the intraclass correlation coefficients of parameters estimated with stretched exponential and biexponential diffusion models of in vivo diffusion-weighted magnetic resonance imaging (MRI) of the prostate.
  
  
  METHODS
  After the institutional review board issued a waiver of informed consent for this Health Insurance Portability and Accountability Act-compliant study, 25 patients with biopsy-proven prostate cancer underwent 3T endorectal MRI and diffusion-weighted MRI of the prostate at 10 b values (0, 45, 75, 105, 150, 225, 300, 600, 900, and 1200 s/mm). The full set of b values was collected twice within a single acquisition. Intraclass correlation coefficients were calculated for intra-acquisition variability. From the biexponential model, the quantitative parameters diffusion coefficient (D), perfusion coefficient (D*), and perfusion fraction (f) were estimated. From the stretched exponential model, the quantitative parameters Kohlrausch decay constant (DK) and alpha (α) were estimated.
  
  
  RESULTS
  For the 25 patient data sets, the average intraclass correlation coefficients for DK and α were 95.8%, and 64.1%, respectively, whereas those for D, D*, and f were 84.4%, 25.3%, and 41.3%, respectively.
  
  
  CONCLUSIONS
  The stretched exponential diffusion model captures the nonlinear effects of intravoxel incoherent motion in the prostate. The parameters derived from this model are more reliable and reproducible than the parameters derived from the standard, widely used biexponential diffusion/perfusion model.
authors.affiliation: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA. mazahery@mskcc.org
authors.forename: Yousef
authors.initials: Y
authors.lastname: Mazaheri
authors.forename: Asim
authors.initials: A
authors.lastname: Afaq
authors.forename: Daniel B
authors.initials: DB
authors.lastname: Rowe
authors.forename: Yonggang
authors.initials: Y
authors.lastname: Lu
authors.forename: Amita
authors.initials: A
authors.lastname: Shukla-Dave
authors.forename: Jarrett
authors.initials: J
authors.lastname: Grover
mesh_terms: D000328:Adult; D000368:Aged; D003198:Computer Simulation / Q000706:statistics & numerical data; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011467:Prostate / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D015203:Reproducibility of Results; D012189:Retrospective Studies