title: Neural network prediction of prostate tissue composition based on magnetic resonance imaging analysis. A pilot study.
abstract: OBJECTIVE
  To develop a neural network model that estimates prostate histology using magnetic resonance imaging (MRI).
  
  
  METHODS
  Fifty-three men with lower urinary tract symptoms (average age = 63.8 +/- 8.9 years) underwent a prostate MRI (T2) and sextant biopsy of the prostate. Masson Trichome and immunohistochemical prostate-specific antigen staining of the biopsy material were used to calculate the amount of stroma and epithelium in the inner gland (central plus transition zone). MRIs were normalized to the mean intensity of the obturator internus muscle for comparative analyses. Gray scale and texture features were extracted from the inner gland in the midsection transverse MRI slice. Clinical and image variables were used in two neural networks predicting a high amount of stroma and a high amount of epithelium, respectively.
  
  
  RESULTS
  The positive and negative predictive values of the stroma and epithelium neural networks were 95%, 69% and 65%, 92%, respectively.
  
  
  CONCLUSIONS
  These data suggest that the combined use of these neural networks may predict patient response to medical therapy targeting prostatic stroma or epithelium.
authors.affiliation: Departments of Urology and Radiology and the Applied Physics Laboratory, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
authors.forename: I
authors.initials: I
authors.lastname: Simon
authors.forename: P B
authors.initials: PB
authors.lastname: Snow
authors.forename: L S
authors.initials: LS
authors.lastname: Marks
authors.forename: W A
authors.initials: WA
authors.lastname: Christens-Barry
authors.forename: J I
authors.initials: JI
authors.lastname: Epstein
authors.forename: D A
authors.initials: DA
authors.lastname: Bluemke
authors.forename: A W
authors.initials: AW
authors.lastname: Partin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000726:Androgen Antagonists / Q000627:therapeutic use; D004311:Double-Blind Method; D004847:Epithelial Cells / Q000473:pathology; D018120:Finasteride / Q000627:therapeutic use; D006801:Humans; D019044:Image Cytometry / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D010865:Pilot Projects; D010936:Plant Extracts / Q000627:therapeutic use; D011446:Prospective Studies; D011467:Prostate / Q000473:pathology*; D011470:Prostatic Hyperplasia / Q000188:drug therapy / Q000473:pathology; D012189:Retrospective Studies; D028024:Serenoa; D017154:Stromal Cells / Q000473:pathology
chemical_list: D000726:Androgen Antagonists; D010936:Plant Extracts; D018120:Finasteride; C040972:saw palmetto extract