title: Trajectory optimization in radiotherapy using sectioning (TORUS).
abstract: OBJECTIVE
  A challenging problem in trajectory optimization for radiotherapy is properly handling the synchronization of the medical accelerators 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 new 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 maximizing the angular flux through all PTV voxels. 3D dose optimization is performed for trajectories using a commercial TPS progressive resolution optimizer.
  
  
  RESULTS
  The TORUS algorithm is applied to three example treatments: chest wall, scalp, and the TG-119 C-shape phantom. When static collimator coplanar trajectories are generated 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. For the TG-119 phantom, when static couch and collimator non-coplanar trajectories are optimized, TORUS trajectories have superior sparing of the central core avoidance with shorter delivery times, with similar dose conformality and homogeneity.
  
  
  CONCLUSIONS
  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 dynamic capabilities in radiation delivery.
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305-5847, USA.
authors.forename: Christopher Barry
authors.initials: CB
authors.lastname: Locke
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305-5847, USA.
authors.forename: Karl Kenneth
authors.initials: KK
authors.lastname: Bush
mesh_terms: D000465:Algorithms; D006801:Humans; D055585:Physical Phenomena; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted; D050397:Radiotherapy, Intensity-Modulated
keywords: IMRT; VMAT; optimization; radiation therapy; trajectory; treatment planning