Program Information
Trajectory Optimization in Radiotherapy Using Sectioning (TORUS)
C Locke*, K Bush , Stanford University, Stanford, CA
Presentations
TU-D-108-5 (Tuesday, August 1, 2017) 11:00 AM - 12:15 PM Room: 108
Purpose: One of the most challenging problems in trajectory optimization for radiotherapy is 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. This work presents an approach to optimize continuous, beam-on radiation trajectories through exploration of the anatomical topology present in the patient and formation of a novel dual-metric graph optimization problem.
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 information is incorporated into a graph optimization problem to define ideal trajectories. The unique usage of two distance functions in this graph optimization permits TORUS to generate efficient dynamic trajectories for delivery while maximizing the angular flux through all PTV voxels.
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 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 homogeneity.
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.
Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by a Master Research Agreement with Varian Medical Systems.
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