Trimmer sequencing time minimization during dynamically collimated proton therapy using a colony of cooperating...

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Optimization

Background:

• Proton therapy utilizes dynamic collimation systems (DCS) for precise, energy layer-specific beam shaping.
• DCS integration with pencil beam scanning enhances treatment plan conformity but increases delivery time due to slower trimmer movement.

Purpose of the Study:

• To develop and evaluate a novel ant colony optimization (ACO) method for minimizing DCS trimmer sequencing time.
• To maintain high target conformity while reducing the additional treatment time associated with trimmer motion.

Main Methods:

• Ant colony optimization (ACO) algorithm integrated into a treatment planning system to determine efficient trimmer sequencing and beamlet scanning patterns.
• Comparison of ACO-derived patterns against an analytical approximation of contour-like scanning.
• Parameter tuning of ACO to ensure convergence and efficient optimization.

Main Results:

• ACO successfully optimized trimmer sequencing patterns, reducing additional treatment time to approximately 60 seconds per field.
• The optimization process maintained a high degree of target conformity.
• ACO-based optimization demonstrated faster convergence and efficiency compared to analytical contour-like methods.

Conclusions:

• Ant colony optimization (ACO) is an effective technique for optimizing dynamic collimation system (DCS) sequencing in proton therapy.
• This novel application of ACO significantly reduces treatment delivery time by minimizing trimmer movement duration.
• The method successfully balances treatment efficiency with the required high target conformity in proton therapy.