Determination of fast neutron RBE using a fully mechanistic computational model

Area of Science:

• Biophysics
• Radiation Biology
• Computational Biology

Background:

• Estimating the relative biological effectiveness (RBE) of high-linear energy transfer (LET) particles is crucial for radiation therapy and protection.
• Existing models often struggle to accurately capture the complex biophysical interactions at the cellular level.

Purpose of the Study:

• To present and validate a computational model for estimating RBE of high-LET particles.
• To simulate DNA damage induction and its relation to RBE using Monte Carlo methods.

Main Methods:

• Utilized Monte Carlo simulations of particle interactions with an atomic-resolution DNA model.
• Emulated lethal damage as the interaction of two sublethal lesions (double-strand breaks).
• Employed the Geant4-DNA package for simulations using liquid water as the transport medium.

Main Results:

• The model successfully reproduced the general trend of RBE as a function of neutron energy (0.1–14 MeV).
• It accurately predicted the experimentally observed RBE peak around 0.4 MeV.
• Results showed good agreement with some experimental data, though RBE was underestimated above 5 MeV.

Conclusions:

• The developed model provides a valuable tool for understanding and predicting RBE for high-LET particles.
• Model limitations, particularly with heavy ion tracking at lower energies, require further development.
• The findings support the use of computational models in radiobiology research.