Physical parameter optimization scheme for radiobiological studies of charged particle therapy

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Optimizing spatial distribution of physical quantities is crucial for charged particle therapy.
• Current methods may lack flexibility in tailoring dose and linear energy transfer (LETd) distributions.
• Proton, Helium-4, and Carbon-12 ion beams are commonly used in particle therapy.

Purpose of the Study:

• To develop an easy-to-implement method for optimizing the spatial distribution of physical quantities in charged particle therapy.
• To demonstrate the method's feasibility and flexibility using proton, 4He, and 12C ion beams.
• To achieve high-accuracy optimization of dose and dose-averaged LETd distributions within target regions.

Main Methods:

• Developed an optimization algorithm using Python to determine optimal weights of constituent particle beams.
• Generated pristine dose Bragg curves and LETd using Geant4 Monte Carlo simulations.
• Applied the method to achieve various dose spread-out Bragg peak (SOBP) profiles and LETd distributions.

Main Results:

• Achieved high-accuracy spatial distribution optimization with relative differences within ±1.0% for dose.
• Successfully generated flat and sloped dose SOBPs for protons, 4He, and 12C ions.
• Obtained a flat LETd distribution for protons with a relative difference within ±2.0%.

Conclusions:

• The developed method provides an effective and flexible approach for optimizing physical quantities in charged particle therapy.
• The 1D optimization algorithms are extendable to 2D and 3D, and can be adapted for biological dose optimization.
• This strategy enhances precision in treatment planning, potentially improving therapeutic outcomes.