title: Fully automated prostate segmentation on MRI: comparison with manual segmentation methods and specimen volumes.
abstract: OBJECTIVE
  The objective of our study was to compare calculated prostate volumes derived from tridimensional MR measurements (ellipsoid formula), manual segmentation, and a fully automated segmentation system as validated by actual prostatectomy specimens.
  
  
  METHODS
  Ninety-eight consecutive patients (median age, 60.6 years; median prostate-specific antigen [PSA] value, 6.85 ng/mL) underwent triplane T2-weighted MRI on a 3-T magnet with an endorectal coil while undergoing diagnostic workup for prostate cancer. Prostate volume estimates were determined using the formula for ellipsoid volume based on tridimensional measurements, manual segmentation of triplane MRI, and automated segmentation based on normalized gradient fields cross-correlation and graph-search refinement. Estimates of prostate volume based on ellipsoid volume, manual segmentation, and automated segmentation were compared with prostatectomy specimen volumes. Prostate volume estimates were compared using the Pearson correlation coefficient and linear regression analysis. The Dice similarity coefficient was used to quantify spatial agreement between manual segmentation and automated segmentation.
  
  
  RESULTS
  The Pearson correlation coefficient revealed strong positive correlation between prostatectomy specimen volume and prostate volume estimates derived from manual segmentation (R = 0.89-0.91, p < 0.0001) and automated segmentation (R = 0.88-0.91, p < 0.0001). No difference was observed between manual segmentation and automated segmentation. Mean partial and full Dice similarity coefficients of 0.92 and 0.89, respectively, were achieved for axial automated segmentation.
  
  
  CONCLUSIONS
  Prostate volume estimates obtained with a fully automated 3D segmentation tool based on normalized gradient fields cross-correlation and graph-search refinement can yield highly accurate prostate volume estimates in a clinically relevant time of 10 seconds. This tool will assist in developing a broad range of applications including routine prostate volume estimations, image registration, biopsy guidance, and decision support systems.
authors.affiliation: 1 Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182, Bldg 10, Rm B69, Bethesda, MD 20892-1088.
authors.forename: Baris
authors.initials: B
authors.lastname: Turkbey
authors.forename: Sergei V
authors.initials: SV
authors.lastname: Fotin
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Huang
authors.forename: Yin
authors.initials: Y
authors.lastname: Yin
authors.forename: Dagane
authors.initials: D
authors.lastname: Daar
authors.forename: Omer
authors.initials: O
authors.lastname: Aras
authors.forename: Marcelino
authors.initials: M
authors.lastname: Bernardo
authors.forename: Brian E
authors.initials: BE
authors.lastname: Garvey
authors.forename: Juanita
authors.initials: J
authors.lastname: Weaver
authors.forename: Hrishikesh
authors.initials: H
authors.lastname: Haldankar
authors.forename: Naira
authors.initials: N
authors.lastname: Muradyan
authors.forename: Maria J
authors.initials: MJ
authors.lastname: Merino
authors.forename: Peter A
authors.initials: PA
authors.lastname: Pinto
authors.forename: Senthil
authors.initials: S
authors.lastname: Periaswamy
authors.forename: Peter L
authors.initials: PL
authors.lastname: Choyke
mesh_terms: D000328:Adult; D000368:Aged; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000473:pathology; D012189:Retrospective Studies; D047368:Tumor Burden