A Pareto-based beam orientation optimization method for spot scanning intensity-modulated proton therapy.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Intensity-modulated proton therapy (IMPT) offers precise dose delivery.
• Optimizing noncoplanar beam orientations is crucial for improving IMPT efficacy.
• Manual plan optimization is time-consuming and relies on clinical expertise.

Purpose of the Study:

• To present a Pareto-based method for automated generation of optimal IMPT plans.
• To explore the potential of noncoplanar beam orientations in IMPT planning.
• To demonstrate a proof of principle for the developed optimization technique.

Main Methods:

• Developed a novel multicriteria beam orientation optimization (MCBOO) method.
• Employed a multicriteria bilevel optimization approach, integrating upper-level beam orientation and lower-level scalarization parameter optimization.
• Utilized differential evolution for optimization and aggregated Pareto optimal plans to construct a database.

Main Results:

• The MCBOO algorithm successfully generated Pareto optimal IMPT plans for three noncoplanar brain tumor cases.
• Selected MCBOO plans demonstrated significant dose reduction to multiple organs at risk compared to manual plans (10.8–12.9 Gy).
• MCBOO plans achieved comparable or better target coverage while managing trade-offs in organ-at-risk dose, with a maximum increase of 7.8–11.8 Gy to one OAR.

Conclusions:

• A novel MCBOO method automates the generation of Pareto optimal IMPT plans by exploring noncoplanar beam orientations.
• The developed method can identify optimal beam orientations and generate plans comparable to manually created ones.
• This approach offers valuable objective trade-offs for IMPT plan optimization.