title: Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy.
abstract: OBJECTIVE
  Adding magnetic resonance (MR)-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound (US) by using MR-US registration. A common approach is to use surface-based registration. The authors hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular nonrigid surface-based registration method. The authors developed a novel method by extending a nonrigid surface-based registration algorithm with biomechanical finite element (FE) modeling to better predict internal deformations of the prostate.
  
  
  METHODS
  Data were collected from ten patients and the MR and TRUS images were rigidly registered to anatomically align prostate orientations. The prostate was manually segmented in both images and corresponding surface meshes were generated. Next, a tetrahedral volume mesh was generated from the MR image. Prostate deformations due to the TRUS probe were simulated using the surface displacements as the boundary condition. A three-dimensional thin-plate spline deformation field was calculated by registering the mesh vertices. The target registration errors (TREs) of 35 reference landmarks determined by surface and volume mesh registrations were compared.
  
  
  RESULTS
  The median TRE of a surface-based registration with biomechanical regularization was 2.76 (0.81-7.96) mm. This was significantly different than the median TRE of 3.47 (1.05-7.80) mm for regular surface-based registration without biomechanical regularization.
  
  
  CONCLUSIONS
  Biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to a regular nonrigid surface-based registration algorithm and can help to improve the effectiveness of MR guided TRUS biopsy procedures.
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Wendy J M
authors.initials: WJ
authors.lastname: van de Ven
authors.affiliation: Centre for Medical Image Computing, University College London, London WC1E 6BT, United Kingdom.
authors.forename: Yipeng
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Jelle O
authors.initials: JO
authors.lastname: Barentsz
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
authors.affiliation: Centre for Medical Image Computing, University College London, London WC1E 6BT, United Kingdom.
authors.forename: Dean
authors.initials: D
authors.lastname: Barratt
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen 6525 GA, The Netherlands.
authors.forename: Henkjan J
authors.initials: HJ
authors.lastname: Huisman
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D020342:Finite Element Analysis; D006801:Humans; D061705:Image-Guided Biopsy / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008954:Models, Biological; D011467:Prostate / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000601:surgery; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery; D014463:Ultrasonography