Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on...

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Carbon ion therapy offers enhanced biological effectiveness at the Bragg peak.
• Accurate modeling of physics and biological effects is crucial for intensity modulated carbon ion therapy (IMCT) treatment planning.
• Monte Carlo (MC) methods are ideal for this due to their precision.

Purpose of the Study:

• To develop a biological treatment plan optimization system for IMCT using the goCMC MC engine.
• To integrate biological dose calculations into the treatment planning process.
• To achieve clinically viable treatment planning times.

Main Methods:

• Implemented the repair-misrepair-fixation model for spatial distribution of linear-quadratic model parameters.
• Developed a treatment plan optimization module using a gradient-based algorithm to minimize biological effect discrepancies.
• Integrated the system into the Varian Eclipse treatment planning system via a client-server architecture.
• Tested the system on phantom and patient cases.

Main Results:

• The system generated treatment plans with biological spread-out Bragg peaks, effectively targeting tumors and sparing critical structures.
• Computation times were clinically viable: 0.6 hours for prostate, 0.2 hours for pancreas, and 0.3 hours for brain cases, utilizing 4 GPUs.
• Monte Carlo spot simulation was the primary determinant of computation time.

Conclusions:

• A biological treatment plan optimization system for IMCT was successfully developed, leveraging the goCMC MC engine.
• This represents the first achievement of full MC-based IMCT inverse planning within a clinically relevant timeframe.
• The system enables accurate and efficient biological treatment planning for carbon ion therapy.