Influence of secondary electron spectra on the enhanced effectiveness of ion beams

A detailed understanding of physical and biological effects resulting from radiation exposure is crucial in the field of radiation research. Besides the hazardous character of radiation in the context of radiation protection and space research, radiation is applied beneficially in cancer radiotherapy. The radiation effect depends on several factors such as dose, energy and type of radiation. Therefore, radiobiological models are essential to predict the corresponding biological effects. Such models are crucial for instance in particle therapy for the optimization of radiation treatment plans or in space research for risk assessment for astronauts. The LEM is a widely applied model for the prediction of cellular radiation effects and enables the prediction of the increased RBE of ion radiation in comparison to photon radiation. Over the years, the LEM was validated for several ion species and biological endpoints such as the prediction of cell survival in-vitro and in-vivo, the induction of secondary cancers, dose rate or cell cycle effects. In this work, a systematic validation was performed for the current version of the model, LEM IV, by comparing its RBE predictions for cell survival to 610 measurements of a comprehensive database. The analysis enabled a quantification of the systematic underestimation of RBE at larger ion energies, which was observed in previous model validations with single measurement datasets. Additionally, the LEM was further validated by predicting cell survival after mixed irradiations with ions and photons and comparing the results to measurement data. In order to analyze the origin of the observed model deviations in the critical high-energy regime, a more profound understanding of DNA lesion induction and interaction is necessary. In the LEM, the effect calculation after radiation exposure is based on the spatial distribution of DSB in the DNA. For the determination of the DSB distribution in an ion track, the number of DSB induced per dose unit is adopted from photon measurements. In this context the dose refers to energy depositions in nanometer-sized volumes. Thereby, the simplifying assumption is made that photon and ion radiation induce the same number of DSB per dose unit. The DSB are, however, predominantly induced by secondary electrons, which are ejected by the primary radiation species. Furthermore, it is well known that low-energetic electrons are more effective in DSB induction in comparison to high-energetic ones due to high ionization densities at electron track ends. Since the secondary energy spectra are substantially different for ions and photons, also different numbers of DSB per dose unit are expected. In this work, this difference was quantified determining the mean DSB induction effectiveness of different radiation species based on their secondary electron spectra. To assess the mean effectiveness of a secondary electron spectrum, a quantification of the DSB induction effectiveness of single electrons is crucial. Therefore, the probability for DSB induction was derived from the mean free path between two ionizations along an electron track assuming that at least two ionizations are necessary within a defined threshold distance in order to induce a DSB. The DSB induction model was successfully applied to determine the effectiveness of different ion species but also for several photon radiation qualities. Furthermore, these findings were incorporated in the LEM, leading to a new model version LEM V. The more precise description of the DSB induction in dependence of the primary radiation species led to more accurate RBE predictions for cell survival after ion irradiation. Especially the observed underestimation of RBE for higher energetic ions for LEM IV was improved, leading to more precise effect predictions not only for radiotherapy applications but also for radiation risk assessment in space research