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Optimizing highly noncoplanar VMAT trajectories: the NoVo method.

Marco Langhans1,2,3, Jan Unkelbach1, Thomas Bortfeld1

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We developed NoVo, a new method for noncoplanar volumetric modulated arc therapy (VMAT) plans. NoVo optimizes treatment trajectories, significantly reducing computation time and improving plan quality compared to existing methods.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Imaging

Background:

  • Noncoplanar beam arrangements are established in intensity modulated radiation therapy (IMRT) and stereotactic radiosurgery (SRS).
  • Noncoplanar trajectories for volumetric modulated arc therapy (VMAT) are less common due to limited machine availability and complex beam angle selection.
  • Automated beam angle selection for VMAT remains challenging due to the nonconvex nature of the problem.

Purpose of the Study:

  • To introduce NoVo (Noncoplanar VMAT Optimization), a novel method for generating noncoplanar VMAT treatment plans.
  • To address the computational challenges in selecting optimal noncoplanar beam trajectories for VMAT.
  • To evaluate the performance of NoVo against established methods and a recent noncoplanar VMAT algorithm.

Main Methods:

  • NoVo computes an initial solution considering all possible beam directions, then iteratively eliminates beams based on fluence contributions.
  • Beam angles are scored using geometrical considerations for rapid assessment of beam space utility.
  • A custom pathfinding algorithm identifies an optimized, continuous trajectory through promising beam angles.
  • The selected trajectory is used to optimize the final VMAT plan.

Main Results:

  • NoVo produced plans closest to the ideal "all-angles" solution for lung cases and second-best for brain and liver cases.
  • The method significantly reduced solution time by employing geometrical scoring and an iterative reduction process.
  • Compared to a recent noncoplanar VMAT algorithm, NoVo decreased computation time by 2-3 times.
  • NoVo improved objective function values by 24% (lung), 49% (brain), and 6% (liver) compared to coplanar VMAT.

Conclusions:

  • NoVo offers an efficient and effective approach for generating high-quality noncoplanar VMAT plans.
  • The method addresses the beam angle selection problem, improving upon existing VMAT optimization techniques.
  • NoVo demonstrates potential for wider clinical adoption of noncoplanar VMAT due to its speed and plan quality improvements.