title: Registration of clinical volumes to beams-eye-view images for real-time tracking.
abstract: OBJECTIVE
  The authors combine the registration of 2D beam's eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV).
  
  
  METHODS
  During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position.
  
  
  RESULTS
  The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery.
  
  
  CONCLUSIONS
  Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.
authors.affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Jonathan H
authors.initials: JH
authors.lastname: Bryant
authors.affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Joerg
authors.initials: J
authors.lastname: Rottmann
authors.affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: John H
authors.initials: JH
authors.lastname: Lewis
authors.affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Pankaj
authors.initials: P
authors.lastname: Mishra
authors.affiliation: Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney, New South Wales 2006, Australia.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
authors.affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Ross I
authors.initials: RI
authors.lastname: Berbeco
mesh_terms: D002138:Calibration; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000532:radiotherapy; D004583:Electrons; D045853:Exhalation; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging / Q000528:radiation effects; D010363:Pattern Recognition, Automated / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D047368:Tumor Burden