title: Semiautomatic registration of digital histopathology images to in vivo MR images in molded and unmolded prostates.
abstract: OBJECTIVE
  To evaluate a semiautomatic software-based method of registering in vivo prostate MR images to digital histopathology images using two approaches: (i) in which the prostates were molded to simulate distortion due to the endorectal imaging coil before fixation, and (ii) in which the prostates were not molded.
  
  
  METHODS
  T2-weighted MR images and digitized whole-mount histopathology images were acquired for 26 patients with biopsy-confirmed prostate cancer who underwent radical prostatectomy. Ten excised prostates were molded before fixation. A semiautomatic method was used to align MR images to histopathology. Percent overlap between MR and histopathology images, as well as distances between corresponding anatomical landmarks were calculated and used to evaluate the registration technique for molded and unmolded cases.
  
  
  RESULTS
  The software successfully morphed histology-based prostate images into corresponding MR images. Percent overlap improved from 80.4 ± 5.8% before morphing to 99.7 ± 0.62% post morphing. Molded prostates had a smaller distance between landmarks (1.91 ± 0.75 mm) versus unmolded (2.34 ± 0.68 mm), P < 0.08.
  
  
  CONCLUSIONS
  Molding a prostate before fixation provided a better alignment of internal structures within the prostate, but this did not reach statistical significance. Software-based morphing allowed for nearly complete overlap between the pathology slides and the MR images.
authors.affiliation: Departments of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Olga
authors.initials: O
authors.lastname: Starobinets
authors.forename: Richard
authors.initials: R
authors.lastname: Guo
authors.forename: Jeffry P
authors.initials: JP
authors.lastname: Simko
authors.forename: Kyle
authors.initials: K
authors.lastname: Kuchinsky
authors.forename: John
authors.initials: J
authors.lastname: Kurhanewicz
authors.forename: Peter R
authors.initials: PR
authors.lastname: Carroll
authors.forename: Kirsten L
authors.initials: KL
authors.lastname: Greene
authors.forename: Susan M
authors.initials: SM
authors.lastname: Noworolski
mesh_terms: D000465:Algorithms; D002370:Casts, Surgical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D066298:In Vitro Techniques; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique
keywords: MRI; histopathology; prostate cancer; registration