title: Multiparametric MRI maps for detection and grading of dominant prostate tumors.
abstract: OBJECTIVE
  To develop an image-based technique capable of detection and grading of prostate cancer, which combines features extracted from multiparametric MRI into a single parameter map of cancer probability.
  
  
  METHODS
  A combination of features extracted from diffusion tensor MRI and dynamic contrast enhanced MRI was used to characterize biopsy samples from 29 patients. Support vector machines were used to separate the cancerous samples from normal biopsy samples and to compute a measure of cancer probability, presented in the form of a cancer colormap. The classification results were compared with the biopsy results and the classifier was tuned to provide the largest area under the receiver operating characteristic (ROC) curve. Based solely on the tuning of the classifier on the biopsy data, cancer colormaps were also created for whole-mount histopathology slices from four radical prostatectomy patients.
  
  
  RESULTS
  An area under ROC curve of 0.96 was obtained on the biopsy dataset and was validated by a "leave-one-patient-out" procedure. The proposed measure of cancer probability shows a positive correlation with Gleason score. The cancer colormaps created for the histopathology patients do display the dominant tumors. The colormap accuracy increases with measured tumor area and Gleason score.
  
  
  CONCLUSIONS
  Dynamic contrast enhanced imaging and diffusion tensor imaging, when used within the framework of supervised classification, can play a role in characterizing prostate cancer.
authors.affiliation: Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada. moradi@ece.ubc.ca
authors.forename: Mehdi
authors.initials: M
authors.lastname: Moradi
authors.forename: Septimiu E
authors.initials: SE
authors.lastname: Salcudean
authors.forename: Silvia D
authors.initials: SD
authors.lastname: Chang
authors.forename: Edward C
authors.initials: EC
authors.lastname: Jones
authors.forename: Nicholas
authors.initials: N
authors.lastname: Buchan
authors.forename: Rowan G
authors.initials: RG
authors.lastname: Casey
authors.forename: S Larry
authors.initials: SL
authors.lastname: Goldenberg
authors.forename: Piotr
authors.initials: P
authors.lastname: Kozlowski
mesh_terms: D000368:Aged; D000465:Algorithms; D003287:Contrast Media; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D019786:Gadolinium DTPA; 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; D013382:Subtraction Technique
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA