The biological effectiveness of proton beams relative to photon beams in radiation therapy has been taken to be 1.1 throughout the history of proton therapy. While potentially appropriate as an average value, actual relative biological effectiveness (RBE) values may differ. This Task Group report outlines the basic concepts of RBE as well as the biophysical interpretation and mathematical concepts. The current knowledge on RBE variations is reviewed and discussed in the context of the current clinical use of RBE and the clinical relevance of RBE variations (with respect to physical as well as biological parameters). The following task group aims were designed to guide the current clinical practice: Assess whether the current clinical practice of using a constant RBE for protons should be revised or maintained. Identifying sites and treatment strategies where variable RBE might be utilized for a clinical benefit. Assess the potential clinical consequences of delivering biologically weighted proton doses based on variable RBE and/or LET models implemented in treatment planning systems. Recommend experiments needed to improve our current understanding of the relationships among in vitro, in vivo, and clinical RBE, and the research required to develop models. Develop recommendations to minimize the effects of uncertainties associated with proton RBE for well‐defined tumor types and critical structures.

If the production of sublethal damage is considered independent of LET, there will be a risk that non-corrected evaluation of RBE will lead to an over- or under-estimate of RBE at low doses per fractions (the clinically relevant region).

Glioblastoma multiforme (GBM) is among the most lethal of human malignancies. Most GBM tumors are refractory to cytotoxic therapies. Glioma stem cells (GSCs) significantly contribute to GBM progression and post-treatment tumor relapse, therefore serving as a key therapeutic target; however, GSCs are resistant to conventional radiation therapy. Proton therapy is one of the newer cancer treatment modalities and its effects on GSCs function remain unclear. Here, by utilizing patient-derived GSCs, we show that proton radiation generates greater cytotoxicity in GSCs than x-ray photon radiation. Compared with photon radiation, proton beam irradiation induces more single and double strand DNA breaks, less H2AX phosphorylation, increased Chk2 phosphorylation, and reduced cell cycle recovery from G2 arrest, leading to caspase-3 activation, PARP cleavage, and cell apoptosis. Furthermore, proton radiation generates a large quantity of reactive oxygen species (ROS), which is required for DNA damage, cell cycle redistribution, apoptosis, and cytotoxicity. Together, these findings indicate that proton radiation has a higher efficacy in treating GSCs than photon radiation. Our data reveal a ROS-dependent mechanism by which proton radiation induces DNA damage and cell apoptosis in GSCs. Thus, proton therapy may be more efficient than conventional x-ray photon therapy for eliminating GSCs in GBM patients.

The linear-quadratic (LQ) model of radiobiological effect is well established in conventional, i.e., external beam, radiotherapy. Because the model is derived from sound biophysical principles, it is also emerging as the standard formalism for assessing biological responses for the whole range of radiotherapy treatments. A central feature of LQ methodology is the quantity known as the biologically effective dose (BED), which may be used to quantify the radiobiological impact of a treatment on both tumors and normal tissues. The BEDs commonly associated with conventional therapy may thus be compared to those expected from novel radiotherapy treatments, such as targeted radionuclide therapy. This approach also provides a mechanism for designing targeted treatments which are therapeutically equivalent to external beam treatments. In this paper the LQ methodology is outlined and worked examples are provided which demonstrate the tentative link between targeted radiotherapy doses and those used in conventional radiotherapy. The incorporation of an allowance for relative biological effectiveness (RBE) effects is also discussed. The complexity of the subject and the potentially large number of variables does place a restriction on overall predictive accuracy and the necessary caveats are outlined.

The aim is to demonstrate the potential impact of changes in the value of the β parameter in the linear quadratic (LQ) model on the calculation of clinical relative biological effectiveness (RBE) values used for high linear energy transfer (LET) radiotherapy. The parameter RBE(min) is introduced into the LQ formulation to account for possible changes in the β radiosensitivity coefficient with changing LET. The model is used to fit fractionated data under two conditions, where RBE(min) = 1 and RBE(min) ≠ 1. Nonlinear regression and analysis of variance are used to test the hypothesis that the inclusion of a non-unity value of RBE(min) better predicts the total iso-effective dose required at low number of fractions for fast neutrons, carbon ions, π-meson and proton fractionation data obtained for various tissues from previous publications. For neutrons the assumption of RBE(min) ≠ 1 provided a better fit in 89% of the cases, whereas for carbon ions RBE(min) ≠ 1 provided a better fit only for normal tissue at the spread-out Bragg peak. The results provide evidence of the impact that variations in the β parameter may have when calculating clinically relevant RBE values, especially when using high doses per fraction (i.e. hypofractionation) of high-LET radiations.

Purpose This work introduces the concept of segment‐averaged linear energy transfer (LET) as a new approach to average distributions of LET of proton beams based on a revisiting of microdosimetry theory. The concept of segment‐averaged LET is then used to generate an analytical model from Monte Carlo simulations data to perform fast and accurate calculations of LET distributions for proton beams. Methods and material The distribution of energy imparted by a proton beam into a representative biological structure or site is influenced by the distributions of (a) LET, (b) segment length, which is the section of the proton track in the site, and (c) energy straggling of the proton beam. The distribution of LET is thus generated by the LET of each component of the beam in the site. However, the situation when the LET of each single proton varies appreciably along its path in the site is not defined. Therefore, a new distribution can be obtained if the particle track segment is decomposed into smaller portions in which LET is roughly constant. We have called “segment distribution” of LET the one generated by the contribution of each portion. The average of that distribution is called segment‐averaged LET. This quantity is obtained in the microdosimetry theory from the average and standard deviation of the distributions of energy imparted to the site, segment length, and energy imparted per collision. All this information is calculated for protons of clinically relevant energies by means of Geant4‐DNA microdosimetric simulations. Finally, a set of analytical functions is proposed for each one of the previous quantities. The presented model functions are fitted to data from Geant4‐DNA simulations for monoenergetic beams from 100 keV to 100 MeV and for spherical sites of 1, 5, and 10 μm in diameter. Results The average differences along the considered energy range between calculations based on our analytical models and MC for segment‐averaged dose‐averaged restricted LET are −0.2 ± 0.7 keV/μm for the 1 μm case, 0.0 ± 0.9 keV/μm for the 5 μm case, and −0.3 ± 1.1 keV/μm for the 10 μm case, respectively. All average differences are below the average standard deviation (1σ) of the MC calculations. Conclusions A new way of averaging LET for a proton beam is performed to incorporate the effects produced by the variation of stopping power of each individual proton along microscopic biological structures. An analytical model based on MC simulations allows for fast and accurate calculations of segment‐averaged dose‐averaged restricted LET for proton beams, which otherwise would need to be calculated from exhaustive MC simulations of clinical plans.

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In two fast neutron data sets, comprising in vitro and in vivo experiments, an inverse relationship is found between the low-linear energy transfer (LET) α/β ratio and the maximum value of relative biological effect (RBE(max)), while the minimum relative biological effect (RBE(min)) is linearly related to the square root of the low-LET α/β ratio. RBE(max) is the RBE at near zero dose and can be represented by the ratio of the α parameters at high- and low-LET radiation exposures. RBE(min) is the RBE at very high dose and can be represented by the ratio of the square roots of the β parameters at high- and low-LET radiation exposures. In principle, it may be possible to use the low-LET α/β ratio to predict RBE(max) and RBE(min, )providing that other LET-related parameters, which reflect intercept and slopes of these relationships, are used. These two limits of RBE determine the intermediate values of RBE at any dose per fraction; therefore, it is possible to find the RBE at any dose per fraction. Although these results are obtained from fast neutron experiments, there are implications for charged particle therapy using protons (when RBE is scaled downwards) and for heavier ion beams (where the magnitude of RBE is similar to that for fast neutrons). In the case of fast neutrons, late reacting normal tissue systems and very slow growing tumours, which have the smallest values of the low-LET α/β ratio, are predicted to have the highest RBE values at low fractional doses, but the lowest values of RBE at higher doses when they are compared with early reacting tissues and fast growing tumour systems that have the largest low-LET α/β ratios.