The application of amorphous track models to study cell survival in heavy ions beams

In vitro modified microdosimetric kinetic model-based predictions for B14-150 cells survival in 450 MeV/u carbon ion beam with aluminum ridge filter for biologically optimized spread-out Bragg peak

The relative biological efficiency of particle irradiation could be predicted with a wide variety of radiobiological models for various end-points. We validate the forecast of modified Microdosimetric Kinetic Model in vitro using combined data of reference Co-60 radiation and carbon ion plateau data for specific cell line to optimize the survival function in spread-out Bragg Peak obtained with an especially designed ridge filter. We used Geant4 Monte-Carlo software to simulate the fragment contribution along Bragg curve inside water phantom, open-source toolkit Survival to predict the expected linear-quadratic model parameters for each fragment, and in-house software to form the total survival curve in spread-out Bragg Peak. The irradiation was performed at U-70 synchrotron with an especially designed Aluminum ridge filter under the control of PTW and in-house ionization chambers. The cell clonogenic assay was conducted with the B14-150 cell line. The data analysis was accomplished using scipy and CERN ROOT. The clonogenic assay represents the survival in spread-out Bragg Peak at different points and qualitatively follows the modeled survival curve very well. The quantitative difference is within 3σ, and the deviation might be explained by the uncertainties of physical modeling using Monte-Carlo methods. Overall, the obtained results are promising for further usage in radiobiological studies or carbon ion radiotherapy. Shaping the survival curve in the region of interest (i.e., spread-out Bragg Peak) is a comprehensive task that requires high-performance computing approaches. Nevertheless, the method's potential application is related to the development of next-generation treatment planning systems for ion beams. This can open a wide range of improvements in patient treatment outcome, provide new optimized fractionation regimes or optimized dose delivery schemes, and serve as an entrance point to the translational science approach.