Calculating biological dose distributions in hadrontherapy using GATE: the BioDose actor

Objective.The, a new tool implemented in the GATE Monte Carlo platform, aims to calculate the biological dose and its associated uncertainty for hadrontherapy treatment plans. This tool is designed to facilitate the validation of biophysical models and optimize clinical treatment planning by providing accurate biological dose distributions.Approach.Theutilizes pre-calculated databases of the linear-quadratic coefficients (and) of cell survival curves, derived from biophysical models such as the modified MicroKinetic Model (mMKM) and the nanodosimetry and oxidative stress model. These databases cover hydrogen, helium, lithium, carbon, and oxygen ions, with energy ranges from 0.1 MeV uto 1000 MeV u. The algorithm computes the biological dose using the linear-quadratic coefficients and their uncertainties, while optimizing Monte Carlo simulation parameters. Two step-size limitation methods in Geant4 (StepLimiter and StepFunction) were evaluated to balance accuracy and computation time in spread out Bragg peak (SOBP) dose distributions for proton and carbon-ion beams.Main results.The StepFunction method proved more efficient than the StepLimiter, achieving a 30.6-fold acceleration factor for protons and a 2-fold acceleration factor for carbon ions while maintaining a maximum relative difference of 2% in SOBP. Optimal parameters for StepFunction were identified as (,) for the clinical proton beam and (,) for the clinical carbon-ion beam. The calculatedandcoefficients and relative biological effectiveness values (1.2-1.5 for protons, 2-3 for carbon ions) aligned with literature. Application to a clinical carbon-ion treatment plan created by Raystation allowed us to validate theand to demonstrate the tool's capability to generate physical and biological dose maps and dose volume histograms.Significance.Theenables direct comparison of biophysical models, supporting the integration of biological dose calculations into clinical practice. By optimizing simulation parameters, it reduces computation time without compromising accuracy, thus enhancing the feasibility of biological dose-based treatment planning in hadrontherapy.