Simultaneous trajectory generation and volumetric modulated arc therapy optimization.

Area of Science:

• Radiation Oncology
• Medical Physics
• Computational Biology

Background:

• Trajectory-based treatment planning integrates gantry-couch motion with volumetric modulated arc therapy (VMAT).
• Current methods often optimize trajectory and plan separately, potentially missing optimal solutions.

Purpose of the Study:

• To implement and evaluate a novel optimization methodology for simultaneous trajectory and VMAT treatment plan optimization (simTr-VMAT).
• To assess the dosimetric benefits of simTr-VMAT compared to traditional coplanar VMAT.

Main Methods:

• Employed a column generation approach to iteratively construct treatment plans and determine optimal trajectories.
• Utilized a progressively increasing gantry-couch grid resolution for efficient angular space sampling.
• Validated the algorithm by comparing simTr-VMAT plans against 5000 random trajectories for lung, glioblastoma, and prostate patient cases.

Main Results:

• simTr-VMAT reduced mean dose to the heart and ipsilateral lung by 1.5 and 1.0 Gy for a lung patient.
• Improved target coverage and reduced mean dose to critical structures by 2-7 Gy for a glioblastoma patient.
• simTr-VMAT plans achieved high rankings (96.3-99.6 percentiles) compared to random trajectories, indicating superior efficiency.

Conclusions:

• The simTr-VMAT methodology yields treatment plans with equivalent or superior dosimetric outcomes compared to coplanar VMAT.
• Optimized trajectories generated by simTr-VMAT are among the most efficient found for each patient case.
• This approach offers a promising advancement in radiation therapy planning.