Different qualities of radiation are known to cause different biological effects at the same absorbed dose. Enhancements of the biological effectiveness are a direct consequence of the energy deposition clustering at the scales of DNA molecule and cell nucleus whilst absorbed dose is a macroscopic averaged quantity which does not take into account heterogeneities at the nanometer and micrometer scales. Microdosimetry aims to measure radiation quality at cellular or sub-cellular levels trying to increase the understanding of radiation damage mechanisms and effects. Existing microdosimeters rely on the well-established gas-based detectors or the more recent solid-state devices. They provide specific energy z spectra and other derived quantities as lineal energy (y) spectra assessed at the micrometer level. The interpretation of the radio-biological experimental data in the framework of different models has raised interest and various investigations have been performed to link in vitro and in vivo radiobiological outcomes with the observed microdosimetric data. A review of the major models based on experimental microdosimetry, with a particular focus on ion beam therapy applications and an emphasis on the microdosimetric kinetic model (MKM), will be presented in this work, enlightening the advantages of each one in terms of accuracy, initial assumptions, and agreement with experimental data. The MKM has been used to predict different kinds of radiobiological quantities such as the relative biological effects for cell inactivation or the oxygen enhancement ratio. Recent developments of the MKM will be also presented, including new non-Poissonian correction approaches for high linear energy transfer radiation, the inclusion of partial repair effects for fractionation studies, and the extension of the model to account for non-targeted effects. We will also explore developments for improving the models by including track structure and the spatial damage correlation information, by using the full fluence spectrum and by better accounting for the energy-deposition fluctuations at the intra- and inter-cellular level.

Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic fragments, secondary protons and fragments, is in fact challenging due to their very short range. However, considering their low residual energy and therefore high LET, the possible contribution of such heavy particles to the overall biological effect could be not negligible. In this context, we performed a systematic analysis aimed at an explicit assessment of the RBE (relative biological effectiveness, i.e., the ratio of photon to proton physical dose needed to achieve the same biological effect) contribution of target fragments in the biological dose calculations of proton fields. The TOPAS Monte Carlo code has been used to characterize the radiation field, i.e., for the scoring of primary protons and fragments in an exemplary water target. TRiP98, in combination with LEM IV RBE tables, was then employed to evaluate the RBE with a mixed field approach accounting for fragments’ contributions. The results were compared with that obtained by considering only primary protons for the pristine beam and spread out Bragg peak (SOBP) irradiations, in order to estimate the relative weight of target fragments to the overall RBE. A sensitivity analysis of the secondary particles production cross-sections to the biological dose has been also carried out in this study. Finally, our modeling approach was applied to the analysis of a selection of cell survival and RBE data extracted from published in vitro studies. Our results indicate that, for high energy proton beams, the main contribution to the biological effect due to the secondary particles can be attributed to secondary protons, while the contribution of heavier fragments is mainly due to helium. The impact of target fragments on the biological dose is maximized in the entrance channels and for small $\alpha /\beta$ values. When applied to the description of survival data, model predictions including all fragments allowed better agreement to experimental data at high energies, while a minor effect was observed in the peak region. An improved description was also obtained when including the fragments’ contribution to describe RBE data. Overall, this analysis indicates that a minor contribution can be expected to the overall RBE resulting from target fragments. However, considering the fragmentation effects can improve the agreement with experimental data for high energy proton beams.

The novel tool enables estimation of the risk of tumor relapse after chemotherapy in HL patients on the basis of basal and interim PET/CT scans including SUV and densitometric information.

Objective . Since the early years, particle therapy treatments have been associated with concerns for late toxicities, especially secondary cancer risk (SCR). Nowadays, this concern is related to patients for whom long-term survival is expected (e.g. breast cancer, lymphoma, paediatrics). In the aim to contribute to this research, we present a dedicated statistical and modelling analysis aiming at improving our understanding of the RBE for mutation induction ( RBE M ˜ ) for different particle species. Approach . We built a new database based on a systematic collection of RBE data for mutation assays of the gene encoding for the purine salvage enzyme hypoxanthine-guanine phosphoribosyltransferase from literature (105 entries, distributed among 3 cell lines and 16 particle species). The data were employed to perform statistical and modelling analysis. For the latter, we adapted the microdosimetric kinetic model (MKM) to describe the mutagenesis in analogy to lethal lesion induction. Main results . Correlation analysis between RBE for survival (RBE _S ) and RBE M ˜ reveals significant correlation between these two quantities ( ρ = 0.86, p < 0.05). The correlation gets stronger when looking at subsets of data based on cell line and particle species. We also show that the MKM can be successfully employed to describe RBE M ˜ , obtaining comparably good agreement with the experimental data. Remarkably, to improve the agreement with experimental data the MKM requires, consistently in all the analysed cases, a reduced domain size for the description of mutation induction compared to that adopted for survival. Significance . We were able to show that RBE _S and RBE M ˜ are strongly related quantities. We also showed for the first time that the MKM could be successfully applied to the description of mutation induction, representing an endpoint different from the more traditional cell killing. In analogy to the RBE _S , RBE M ˜ can be implemented into treatment planning system evaluations.

Objective. This study aims to perform a comprehensive microdosimetric characterization of a clinical helium ion beam at the Heidelberg ion-beam Therapy center, assessing radiation quality along a spread-out Bragg peak (SOBP) and providing experimental data to support the biological effectiveness of helium ions in clinical applications. Approach. Microdosimetric spectra were measured at several water depths within the SOBP using two solid-state detectors: a silicon and a synthetic single-crystal diamond detector. Microdosimetric quantities, including dose-mean lineal energy ( y D ) and frequency-mean lineal energy ( y F ), were derived. Monte Carlo simulations with the Geant4 toolkit replicated the experimental setup to validate the measured quantities. The modified microdosimetric kinetic model was also applied to estimate the relative biological effectiveness at 10% survival (RBE₁₀). SAOS-2 and U2OS clonogenic assays were performed under identical irradiation conditions at the same facility to benchmark the RBE predictions. Main results. The experimental results demonstrated a progressive increase in y D values along the beam path, peaking at the distal edge of the SOBP, consistent with the simulated dose-averaged linear energy transfer distribution. The RBE₁₀ values estimated by the two solid-state detectors showed good agreement with the experimental data from clonogenic assays, within the associated uncertainties. Significance. These findings underscore the utility of advanced solid-state detectors for helium beam characterization and highlight the importance of microdosimetry in improving radiobiological modeling. The results provide further evidence supporting the clinical potential of helium ion therapy, particularly for tumors requiring high precision and maximal healthy tissue sparing.