title: Apparent diffusion coefficient for prostate cancer imaging: impact of B values.
abstract: OBJECTIVE
  The purpose of this article is to investigate the effect of b values on apparent diffusion coefficient (ADC) values estimated from 1.5-T diffusion-weighted MRI (DWI) of the prostate acquired with an endorectal coil in distinguishing prostate cancer from normal-tissue regions of interest (ROIs) and the correlation of ADC values with the tumor Gleason score.
  
  
  METHODS
  Pretreatment DWI studies were analyzed retrospectively in 51 consecutive patients with prostate cancer with either two (b=0 and 1000 s/mm2; n=26 patients) or five (b=0, 50, 200, 1500, and 2000 s/mm2; n=25 patients) b values. In 45 normal peripheral-zone ROIs and 65 prostate cancer ROIs (14 in the central gland), ADC values were estimated by use of several combinations of two or five b values and a monoexponential model. We used the area under the receiver operating characteristic curve to characterize the effectiveness of ADC values in distinguishing prostate cancer from normal-tissue ROIs, and we calculated Spearman rank-order correlation between ADC values and the Gleason score.
  
  
  RESULTS
  ADC values were often significantly different (p<0.001) when estimated from different combinations of two or five b values. However, except when both b values were less than or equal to 200 mm2/s or greater than or equal to 1500 mm2/s, the AUC value for distinguishing prostate cancer from normal-tissue ROIs was similar (0.88-0.93). The correlation coefficients between ADC values and the Gleason score were between -0.30 and -0.68.
  
  
  CONCLUSIONS
  The choice of b values can significantly affect ADC estimates. ADC values can produce a similar discriminant performance in distinguishing prostate cancer from normal-tissue ROIs and in correlation with the Gleason score, but an appropriate ADC cutoff value needs to be selected specifically for each b-value combination.
authors.affiliation: 1 School of Electronic and Information Engineering, Beijing Jiaotong University, No. 3 Shangyuancun, Haidan District, Beijing, China, 100084.
authors.forename: Yahui
authors.initials: Y
authors.lastname: Peng
authors.forename: Yulei
authors.initials: Y
authors.lastname: Jiang
authors.forename: Tatjana
authors.initials: T
authors.lastname: Antic
authors.forename: Ila
authors.initials: I
authors.lastname: Sethi
authors.forename: Christine
authors.initials: C
authors.lastname: Schmid-Tannwald
authors.forename: Scott
authors.initials: S
authors.lastname: Eggener
authors.forename: Aytekin
authors.initials: A
authors.lastname: Oto
mesh_terms: D000368:Aged; D000465:Algorithms; 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; D011471:Prostatic Neoplasms / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity