ESTRO 36 Abstract Book

S201 ESTRO 36 2017 _______________________________________________________________________________________________

received an inadequate therapeutic dose. Concerning the low number of locoregional relapses in AC patients after definitive CRT one has to balance increased skin side effects by including the AILD into the standard CTV against a rigid oncological-anatomical interpretation of the local lymphatic drainage.

homogeneity.

Award Lecture: Company Award Lectures

OC-0376 Trajectory Optimization in Radiotherapy Using Sectioning (TORUS) C. Locke 1 , K. Bush 1 1 Stanford Cancer Center, Radiation Oncology, Stanford, USA Purpose or Objective One of the most challenging problems in trajectory optimization for radiotherapy is properly handling the synchronization of the medical accelerator’s dynamic delivery. The initial coarse sampling of control points implemented in a Progressive Resolution Optimization type approach (VMAT) routinely results in MLC aperture forming contention issues as the sampling resolution increases. IMRT based solutions such as 4Pi avoid MLC synchronization issues through use of a static gantry, but inevitably suffer from longer treatment times. This work presents an appoach to optimize continuous, beam-on radiation trajectories thorough exploration of the anatomical topology present in the patient and formation of a novel dual metric graph optimization problem. Material and Methods This work presents a novel perspective on trajectory optimization in radiotherapy using the concept of sectioning (TORUS). TORUS avoids degradation of 3D dose optimization quality by mapping the connectedness of target regions from the BEV perspective throughout the space of deliverable coordinates. This connectedness information is then incorporated into a graph optimization problem to define ideal trajectories. The unique usage of two distance functions in this graph optimization permits the TORUS algorithm to generate efficient dynamic trajectories for delivery while maximing the angular flux through all PTV voxels. 3D dose optimization is performed for trajectories using the Varian’s Photon Optimizer (version 13.6.23). Results The TORUS algorithm is applied to three example treatments: chest-wall, scalp, and the TG-119 C-shape phantom. When restricted to only coplanar trajectories for the chest-wall (dose distributions shown in Figure 1) and scalp cases, the TORUS trajectories are found to outperform both 7 field IMRT and 2 arc VMAT plans in delivery time, organ at risk sparing, conformality, and homogeneity. When the coplanar restriction is removed for the TG-119 phantom and the static non-coplanar trajectories are optimized, TORUS trajectories have superior sparing of the central core avoidance with shorter delivery times, with similar conformality and

Conclusion The TORUS algorithm is able to automatically generate trajectories having improved plan quality and delivery time over standard IMRT and VMAT treatments. TORUS offers an exciting and promising avenue forward toward increasing our dynamic capabilities in radiation delivery. OC-0377 Limited interfractional variabi lity of respiration-induced tumor motion in esophageal cancer RT P. Jin 1 , M.C.C.M. Hulshof 1 , N. Van Wieringen 1 , A. Bel 1 , T. Alderliesten 1 1 Academic Medical Center, Radiation Oncology, Amsterdam, The Netherlands Purpose or Objective Respiration-induced tumor motion is one of the major sources of intrafractional uncertainties in esophageal cancer RT. However, the variability thereof during the treatment course is unclear. In this study, we investigated the interfractional variability of respiration-induced esophageal tumor motion using fiducial markers and 4D- CBCT. Material and Methods We included 24 patients with in total 65 markers implanted in/around the primary esophageal tumor. Per patient, a 3D planning CT (pCT) and 7–28 (median: 8) 3D- CBCTs were acquired. Using the fluoroscopy projection images of the 3D-CBCTs, 10-breathing-phase 4D-CBCTs were retrospectively reconstructed. First, for each 4D- CBCT, the 10 phases were rigidly registered to the pCT based on the vertebra. Next, each marker in each phase was registered to its corresponding marker in the pCT to