title: Elastic registration of multimodal prostate MRI and histology via multiattribute combined mutual information.
abstract: OBJECTIVE
  By performing registration of preoperative multiprotocol in vivo magnetic resonance (MR) images of the prostate with corresponding whole-mount histology (WMH) sections from postoperative radical prostatectomy specimens, an accurate estimate of the spatial extent of prostate cancer (CaP) on in vivo MR imaging (MRI) can be retrospectively established. This could allow for definition of quantitative image-based disease signatures and lead to development of classifiers for disease detection on multiprotocol in vivo MRI. Automated registration of MR and WMH images of the prostate is complicated by dissimilar image intensities, acquisition artifacts, and nonlinear shape differences.
  
  
  METHODS
  The authors present a method for automated elastic registration of multiprotocol in vivo MRI and WMH sections of the prostate. The method, multiattribute combined mutual information (MACMI), leverages all available multiprotocol image data to drive image registration using a multivariate formulation of mutual information.
  
  
  RESULTS
  Elastic registration using the multivariate MI formulation is demonstrated for 150 corresponding sets of prostate images from 25 patient studies with T2-weighted and dynamic-contrast enhanced MRI and 85 image sets from 15 studies with an additional functional apparent diffusion coefficient MRI series. Qualitative results of MACMI evaluation via visual inspection suggest that an accurate delineation of CaP extent on MRI is obtained. Results of quantitative evaluation on 150 clinical and 20 synthetic image sets indicate improved registration accuracy using MACMI compared to conventional pairwise mutual information-based approaches.
  
  
  CONCLUSIONS
  The authors' approach to the registration of in vivo multiprotocol MRI and ex vivo WMH of the prostate using MACMI is unique, in that (1) information from all available image protocols is utilized to drive the registration with histology, (2) no additional, intermediate ex vivo radiology or gross histology images need be obtained in addition to the routinely acquired in vivo MRI series, and (3) no corresponding anatomical landmarks are required to be identified manually or automatically on the images.
authors.affiliation: Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey 08854, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Chappelow
authors.forename: B Nicolas
authors.initials: BN
authors.lastname: Bloch
authors.forename: Neil
authors.initials: N
authors.lastname: Rofsky
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Genega
authors.forename: Robert
authors.initials: R
authors.lastname: Lenkinski
authors.forename: William
authors.initials: W
authors.lastname: DeWolf
authors.forename: Anant
authors.initials: A
authors.lastname: Madabhushi
mesh_terms: D000465:Algorithms; D004548:Elasticity; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011467:Prostate / Q000473:pathology* / Q000601:surgery; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000473:pathology / Q000601:surgery