Registration of Clinical Volumes to Beams-Eye-View Images for Real-Time Tracking
JH Bryant1*, J Rottmann1, JH Lewis1, PJ Keall2, RI Berbeco1, (1) Brigham and Women's Hospital, Dana-Farber Cancer Center and Harvard Medical School, Boston, MA (2) Sydney Medical School, University of Sydney, New South Wales, Australia.WE-A-134-11 Wednesday 8:00AM - 9:55AM Room: 134
Purpose: To develop the 2D/3D registration of cine mode electronic portal imaging device (EPID) images acquired during radiotherapy treatment to the planning computed tomography (CT) images and combine it with relative, markerless EPID tumor tracking. Together the methods will provide an automatic absolute tracking between physician defined volumes such as the gross tumor volume (GTV) the treatment field.
Methods: During treatment of lung SBRT cases, EPID images were continuously acquired. The relative motion was tracked using a markerless multitemplate algorithm whose accuracy was previously confirmed and assessed with manual tracking. Each image then underwent an intensity based 2D/3D registration to the planning CT. In order to minimize the effect of motion blur, the end-of-exhale phase of the four dimensional computed tomography (4DCT) was used. The volume was converted from Hounsfield units into electron density by a calibration curve and DRRs were generated for the beam geometry. Using normalized cross correlation (NCC) between the DRR and EPID image, the best in plane rigid transformation was found. It was then applied to contours in the planning CT, mapping them into the EPID image domain. The best breathing phase for the registration was found with a large set of patient data.
Results: The success of 2D/3D registration proved accurate only over certain phases of the breathing cycle. By registering at this time and using relative tracking, we successfully track target volumes in the EPID images throughout the entire treatment delivery.
Conclusions: Through the combination of relative tracking and phase dependent EPID/4DCT registration, it is possible to track clinical volumes on EPID images. This knowledge of tumor volumes relative to the treatment field provides powerful information for future applications like motion management, adaptive radiotherapy and delivered dose calculations.