Derivation of a comprehensive semi-empirical proton RBE model from published experimental cell survival data...

Area of Science:

• Radiation Oncology
• Radiobiology
• Medical Physics

Background:

• Accurate modeling of proton relative biological effectiveness (RBE) is crucial for optimizing radiation therapy.
• Existing models often lack comprehensive validation across diverse biological systems and irradiation conditions.
• Understanding the dependence of RBE on linear energy transfer (LET) and dose is essential for precise treatment planning.

Purpose of the Study:

• To develop a comprehensive proton RBE model utilizing accumulated cell survival data from the literature.
• To establish a robust model that accounts for variations in cell type and radiation characteristics.
• To provide a tool for improved clinical application of proton therapy.

Main Methods:

• Compiled eligible cell survival data from the Particle Irradiation Data Ensemble (PIDE) database, encompassing 72 datasets across four cell lines.
• Developed a novel cell survival model based on the Poisson equation, defining alpha (α) and beta (β) parameters for damage generation and repair.
• Employed a multi-curve fitting (MCF) approach to integrate cell survival data and derive LET-dependent α and β parameters for each cell line.

Main Results:

• Derived specific α and β parameters for four cell lines, revealing distinct responses to varying LET.
• Established linear relationships between α, β, and LET, enabling prediction of RBE across a range of conditions.
• The comprehensive RBE model demonstrated dependence on LET, α, β, and dose per fraction, showing potential for clinical utility.

Conclusions:

• A reliable and comprehensive proton RBE model was successfully developed, integrating extensive cell survival data.
• The model's dependence on LET, α, β, and dose per fraction offers enhanced predictive power for proton therapy.
• This RBE model holds significant promise for optimizing clinical proton beam radiation treatments.