title: Comparison of different mathematical models of diffusion-weighted prostate MR imaging.
abstract: OBJECTIVE
  To evaluate which mathematical model (monoexponential, biexponential, statistical, kurtosis) fits best to the diffusion-weighted signal in prostate magnetic resonance imaging (MRI).
  
  
  METHODS
  24 prostate 3-T MRI examinations of young volunteers (YV, n=8), patients with biopsy proven prostate cancer (PC, n=8) and an aged matched control group (AC, n=8) were included. Diffusion-weighted imaging was performed using 11 b-values ranging from 0 to 800 s/mm(2).
  
  
  RESULTS
  Monoexponential apparent diffusion coefficient (ADC) values were significantly (P<.001) lower in the peripheral (PZ) zone (1.18±0.16 mm(2)/s) and the central (CZ) zone (0.73±0.13 mm(2)/s) of YV compared to AC (PZ 1.92±0.17 mm(2)/s; CZ 1.35±0.21 mm(2)/s). In PC ADC(mono) values (0.61±0.06 mm(2)/s) were significantly (P<.001) lower than in the peripheral of central zone of AC. Using the statistical analysis (Akaike information criteria) in YV most pixels were best described by the biexponential model (82%), the statistical model, respectively kurtosis (93%) each compared to the monoexponential model. In PC the majority of pixels was best described by the monoexponential model (57%) compared to the biexponential model.
  
  
  CONCLUSIONS
  Although a more complex model might provide a better fitting when multiple b-values are used, the monoexponential analyses for ADC calculation in prostate MRI is sufficient to discriminate prostate cancer from normal tissue using b-values ranging from 0 to 800 s/mm(2).
authors: Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany. michael.quentin@med.uni-duesseldorf.de
authors: Michael
authors: M
authors: Quentin
authors: Dirk
authors: D
authors: Blondin
authors: Janina
authors: J
authors: Klasen
authors: Rotem Shlomo
authors: RS
authors: Lanzman
authors: Falk-Roland
authors: FR
authors: Miese
authors: Christian
authors: C
authors: Arsov
authors: Peter
authors: P
authors: Albers
authors: Gerald
authors: G
authors: Antoch
authors: Hans-Jörg
authors: HJ
authors: Wittsack
mesh_terms: D000328:Adult; D000368:Aged; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D008962:Models, Theoretical; D016011:Normal Distribution; D011467:Prostate / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000473:pathology; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012984:Software