A numerical method to optimise the spatial dose distribution in carbon ion radiotherapy planning

Area of Science:

• Medical Physics
• Computational Physics
• Radiation Oncology

Background:

• Accurate dose delivery is crucial for effective carbon ion therapy.
• Optimizing beam composition is complex due to particle interactions and energy loss.
• Monte Carlo simulations are vital for modeling particle transport in treatment planning.

Purpose of the Study:

• To develop and validate a numerical algorithm for optimizing carbon ion beam entrance spectra.
• To ensure a pre-defined dose-depth profile within the spread-out Bragg peak.
• To integrate this optimization into a carbon ion therapy planning system.

Main Methods:

• Utilizing a physical beam transport model based on SHIELD-HIT10A Monte Carlo code data.
• Employing the L-BFGS-B algorithm for multi-dimensional minimization of dose profile deviations.
• Using multi-dimensional interpolation to calculate energy-fluence spectra for primary and secondary ions.

Main Results:

• Successfully optimized carbon ion beam spectra to match desired dose-depth profiles.
• Calculated energy-fluence spectra for ions using interpolation algorithms.
• Demonstrated the integration of the optimization algorithm with Katz's cellular Track Structure Theory (TST).

Conclusions:

• The developed algorithm is an essential tool for carbon ion therapy planning.
• The approach enables precise control over dose delivery in radiation therapy.
• The open-source libamtrack platform facilitates access to these computational tools.