A Simpler Energy Transfer Efficiency Model to Predict Relative Biological Effect for Protons and Heavier Ions

Area of Science:

• Medical Physics
• Radiation Biology
• Radiotherapy

Background:

• Accurate prediction of relative biological effectiveness (RBE) is crucial for optimizing proton and heavy ion radiotherapy.
• Existing complex models for RBE prediction require significant computational resources and validation.

Purpose of the Study:

• To develop a simplified, semi-empirical model for predicting RBE of protons and heavier ions.
• To provide a complementary tool for estimating RBE, aiding clinical decision-making and risk assessment.

Main Methods:

• The model utilizes effective nuclear charge (Z) and radiosensitivity parameters (αL, βL) of low linear energy transfer (LET) radiation.
• It incorporates sequential saturation processes for the LET-RBE relationship turnover point (LETU) and ultimate α (αU) and β (βU) values.
• Iso-effective linear quadratic model equations are used to scale the estimated RBE based on input parameters and dose.

Main Results:

• The model was fitted to experimental data for various ions, including alpha particles, carbon ions, and ions from deuterons to Argon.
• It demonstrates the ability to predict RBE across a range of LET values, including those relevant to clinical practice and beyond.

Conclusions:

• The developed model offers a practical method to complement existing complex RBE prediction systems.
• It can serve as a valuable secondary check for clinicians, enhancing the safety and efficacy of particle beam radiotherapy.
• Further research and validation in dedicated facilities are recommended to refine RBE prediction models for clinical application.