The particle irradiation data ensemble (PIDE) is the largest database of cell survival data measured after exposure to ion beams and photon reference radiation. We report here on the updated version of the PIDE database and demonstrate how to investigate generic properties of radiation dose response using these sets of raw data. The database now contains information of over 1100 pairs of photon and ion dose response curves. It provides the originally published raw data of cell survival in addition to given linear quadratic (LQ) model parameters. If available, the raw data were used to derive LQ model parameters in the same way for all experiments. To demonstrate the extent of the database and the variability among experiments we focus on the dose response curves after ion and photon radiation separately in a first step. Furthermore, we discuss the capability and the limitations of the database for analyzing properties of low and high linear energy transfer (LET) radiation response based on multiple experiments. PIDE is freely available to the research community under www.gsi.de/bio-pide.

Dose build-up effects in the entrance channel of proton Bragg curves were investigated in detail by means of simulations and experiments. There are two relevant dose build-up effects. Firstly, the δ-electron build-up effect which takes place in the first few millimeters of the tissue until an equilibrium state of the forward-scattered δ-electrons is reached. Secondly, the target fragment build-up effect that covers the first centimeters in the entrance channel of the proton Bragg curve. These target fragments are created in inelastic interactions of the beam protons with the target nuclei and partially have low kinetic energies and/or high atomic numbers compared to the incident beam protons. Consequently, the target fragments possess high LET values and thus an increased RBE. However, the production cross sections relevant for target fragmentation in ion beam therapy still have large uncertainties. Therefore, in this work target fragmentation was investigated indirectly by measuring low-noise proton Bragg curves with the focus placed on their build-up regions. The measurements clearly show the magnitude and shape of the two different build-up effects. Additionally, with the application of a magnetic filter, it was possible to separate the measurement of the target fragment build-up effect from the δ-electron build-up effect. Corresponding FLUKA Monte Carlo simulations were carried out for the experimental setup. A comparison of the experimental results with the FLUKA predictions enabled the assessment of the precision of FLUKA models, e.g. the δ-electron production models and the nuclear event generators which are responsible for target fragmentation reactions. It could be shown that the relevant models worked well to reproduce both build-up effects.

Purpose The increased relative biological effectiveness (RBE) of ions is one of the key benefits of ion radiotherapy compared to conventional radiotherapy with photons. To account for the increased RBE of ions during the process of ion radiotherapy treatment planning, a robust model for RBE predictions is indispensable. Currently, at several ion therapy centers the local effect model I (LEM I) is applied to predict the RBE, which varies with biological and physical impacting factors. After the introduction of LEM I, several model improvements were implemented, leading to the current version, LEM IV, which is systematically tested in this study. Methods As a comprehensive RBE model should give consistent results for a large variety of ion species and energies, the particle irradiation data ensemble (PIDE) is used to systematically validate the LEM IV. The database covers over 1100 photon and ion survival experiments in form of their linear‐quadratic parameters for a wide range of ion types and energies. This makes the database an optimal tool to challenge the systematic dependencies of the RBE model. After appropriate filtering of the database, 571 experiments were identified and used as test data. Results The study confirms that the LEM IV reflects the RBE systematics observed in measurements well. It is able to reproduce the dependence of RBE on the linear energy transfer (LET) as well as on the αγ/βγ ratio for several ion species in a wide energy range. Additionally, the systematic quantitative analysis revealed precision capabilities and limits of the model. At lower LET values, the LEM IV tends to underestimate the RBE with an increasing underestimation with increasing atomic number of the ion. At higher LET values, the LEM IV overestimates the RBE for protons or helium ions, whereas the predictions for heavier ions match experimental data well. Conclusions The LEM IV is able to predict general RBE characteristics for several ion species in a broad energy range. The accuracy of the predictions is reasonable considering the small number of input parameters needed by the model. The detailed quantification of possible systematic deviations, however, enables to identify not only strengths but also limitations of the model. The gained knowledge can be used to develop model adjustments to further improve the model accuracy, which is on the way.