A mixed integer programming approach to minibeam aperture optimization for multi-collimator proton minibeam...

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Optimization

Background:

• Multi-collimator proton minibeam radiation therapy (MC-pMBRT) enables precise dose shaping for cancer treatment.
• Current minibeam aperture optimization (MAO) is manual, inefficient, and lacks guaranteed optimality.

Purpose of the Study:

• Introduce a novel mixed integer programming (MIP) approach for automated MAO in MC-pMBRT.
• Optimize MC-pMBRT plan quality by enhancing dose distributions and peak-valley dose ratio (PVDR).

Main Methods:

• A two-step MIP approach jointly optimizes dose distributions and PVDR, selecting optimal multi-slit collimators (MSCs) per beam angle.
• Employs iterative convex relaxation (ICR) and alternating direction method of multipliers (ADMM) for efficient problem-solving.

Main Results:

• The MIP-MAO method significantly improved conformity index (CI) for targets and PVDR for organs-at-risk (OAR) compared to conventional methods.
• Demonstrated enhanced CI from 0.61 to 0.70 in head-and-neck cases and 0.78 to 0.83 in abdominal cases.
• Reduced mean doses in the body and OAR, indicating improved treatment safety.

Conclusions:

• A novel MIP approach for MAO in MC-pMBRT offers significant improvements in plan quality.
• The MIP-MAO method provides superior PVDR and target conformity compared to heuristic approaches.
• This computational method enhances the efficiency and effectiveness of MC-pMBRT treatment planning.