Direct Comparison between Protons and Alpha-particles of the Same LET: I. Irradiation Methods and Inactivation of Asynchronous V79, HeLa and C3H 10T½ Cells

Cell-cycle dependence on the biological effects of boron neutron capture therapy and its modification by polyvinyl alcohol

Boron neutron capture therapy (BNCT) is a unique radiotherapy of selectively eradicating tumor cells using boron compounds (e.g., 4-borono-L-phenylalanine [BPA]) that are heterogeneously taken up at the cellular level. Such heterogenicity potentially reduces the curative efficiency. However, the effects of temporospatial heterogenicity on cell killing remain unclear. With the technical combination of radiation track detector and biophysical simulations, this study revealed the cell cycle-dependent heterogenicity of BPA uptake and subsequent biological effects of BNCT on HeLa cells expressing fluorescent ubiquitination-based cell cycle indicators, as well as the modification effects of polyvinyl alcohol (PVA). The results showed that the BPA concentration in the S/G2/M phase was higher than that in the G1/S phase and that PVA enhances the biological effects both by improving the uptake and by canceling the heterogenicity. These findings might contribute to a maximization of therapeutic efficacy when BNCT is combined with PVA and/or cell cycle-specific anticancer agents.

An updated variable RBE model for proton therapy

Objective.While a constant relative biological effectiveness (RBE) of 1.1 forms the basis for clinical proton therapy, variable RBE models are increasingly being used in plan evaluation. However, there is substantial variation across RBE models, and several newin vitrodatasets have not yet been included in the existing models. In this study, an updatedin vitroproton RBE database was collected and used to examine current RBE model assumptions, and to propose an up-to-date RBE model as a tool for evaluating RBE effects in clinical settings.Approach.A proton database (471 data points) was collected from the literature, almost twice the size of the previously largest model database. Each data point included linear-quadratic model parameters and linear energy transfer (LET). Statistical analyses were performed to test the validity of commonly applied assumptions of phenomenological RBE models, and new model functions were proposed forRBEmaxandRBEmin(RBE at the lower and upper dose limits). Previously published models were refitted to the database and compared to the new model in terms of model performance and RBE estimates.Main results.The statistical analysis indicated that the intercept of theRBEmaxfunction should be a free fitting parameter and RBE estimates were clearly higher for models with free intercept.RBEminincreased with increasing LET, while a dependency ofRBEminon the reference radiation fractionation sensitivity (α/βx) did not significantly improve model performance. Evaluating the models, the new model gave overall lowest RMSE and highest R2 score. RBE estimates in the distal part of a spread-out-Bragg-peak in water (α/βx= 2.1 Gy) were 1.24-1.51 for original models, 1.25-1.49 for refits and 1.42 for the new model.Significance.An updated RBE model based on the currently largest database among published phenomenological models was proposed. Overall, the new model showed better performance compared to refitted published RBE models.

RadPhysBio: A Radiobiological Database for the Prediction of Cell Survival upon Exposure to Ionizing Radiation

Based on the need for radiobiological databases, in this work, we mined experimental ionizing radiation data of human cells treated with X-rays, γ-rays, carbon ions, protons and α-particles, by manually searching the relevant literature in PubMed from 1980 until 2024. In order to calculate normal and tumor cell survival α and β coefficients of the linear quadratic (LQ) established model, as well as the initial values of the double-strand breaks (DSBs) in DNA, we used WebPlotDigitizer and Python programming language. We also produced complex DNA damage results through the fast Monte Carlo code MCDS in order to complete any missing data. The calculated α/β values are in good agreement with those valued reported in the literature, where α shows a relatively good association with linear energy transfer (LET), but not β. In general, a positive correlation between DSBs and LET was observed as far as the experimental values are concerned. Furthermore, we developed a biophysical prediction model by using machine learning, which showed a good performance for α, while it underscored LET as the most important feature for its prediction. In this study, we designed and developed the novel radiobiological 'RadPhysBio' database for the prediction of irradiated cell survival (α and β coefficients of the LQ model). The incorporation of machine learning and repair models increases the applicability of our results and the spectrum of potential users.

Calculation of biological effectiveness of SOBP proton beams: a TOPAS Monte Carlo study

Objective.This study aims to investigate the biological effectiveness of Spread-Out Bragg-Peak (SOBP) proton beams with initial kinetic energies 50-250 MeV at different depths in water using TOPAS Monte Carlo code.Approach.The study modelled SOBP proton beams using TOPAS time feature. Various LET-based models and Repair-Misrepair-Fixation model were employed to calculate Relative Biological Effectiveness (RBE) for V79 cell lines at different on-axis depths based on TOPAS. Microdosimetric Kinetic Model and biological weighting function-based models, which utilize microdosimetric distributions, were also used to estimate the RBE. A phase-space-based method was adopted for calculating microdosimetric distributions.Main results.The trend of variation of RBE with depth is similar in all the RBE models, but the absolute RBE values vary based on the calculation models. RBE sharply increases at the distal edge of SOBP proton beams. In the entrance region of all the proton beams, RBE values at 4 Gy i.e. RBE(4 Gy) resulting from different models are in the range of 1.04-1.07, comparable to clinically used generic RBE of 1.1. Moving from the proximal to distal end of the SOBP, RBE(4 Gy) is in the range of 1.15-1.33, 1.13-1.21, 1.11-1.17, 1.13-1.18 and 1.17-1.21, respectively for 50, 100, 150, 200 and 250 MeV SOBP beams, whereas at the distal dose fall-off region, these values are 1.68, 1.53, 1.44, 1.42 and 1.40, respectively.Significance.The study emphasises application of depth-, dose- and energy- dependent RBE values in clinical application of proton beams.

The impact of DNA double-strand break repair pathways throughout the carbon ion spread-out Bragg peak beam

Following carbon ion beam irradiation in mammalian cells, such as used in carbon ion radiotherapy (CIRT), it has been suggested that the balance between whether nonhomologous end joining (NHEJ) or homologous recombination (HR) is utilized depends on the DNA double-strand break (DSB) complexity. Here, we quantified DSB distribution and identified the importance of each DSB repair pathway at increasing depths within the carbon ion spread-out Bragg peak (SOBP) beam range. Chinese hamster ovary (CHO) cell lines were irradiated in a single biological system capable of incorporating the full carbon ion SOBP beam range. Cytotoxicity and DSB distribution/repair kinetics were examined at increasing beam depths using cell survival as an endpoint and γ-H2AX as a surrogate marker for DSBs. We observed that proximal SOBP had the highest number of total foci/cell and lowest survival, while distal SOBP had the most dense tracks. Both NHEJ- and HR-deficient CHO cells portrayed an increase in radiosensitivity throughout the full carbon beam range, although NHEJ-deficient cells were the most radiosensitive cell line from beam entrance up to proximal SOBP and demonstrated a dose-dependent decrease in ability to repair DSBs. In contrast, HR-deficient cells had the greatest ratio of survival fraction at entrance depth to the lowest survival fraction within the SOBP and demonstrated a linear energy transfer (LET)-dependent decrease in ability to repair DSBs. Collectively, our results provide insight into treatment planning and potential targets to inhibit, as HR was a more beneficial pathway to inhibit than NHEJ to enhance the cell killing effect of CIRT in targeted tumor cells within the SOBP while maintaining limited unwanted damage to surrounding healthy cells.

Roadmap: helium ion therapy

Helium ion beam therapy for the treatment of cancer was one of several developed and studied particle treatments in the 1950s, leading to clinical trials beginning in 1975 at the Lawrence Berkeley National Laboratory. The trial shutdown was followed by decades of research and clinical silence on the topic while proton and carbon ion therapy made debuts at research facilities and academic hospitals worldwide. The lack of progression in understanding the principle facets of helium ion beam therapy in terms of physics, biological and clinical findings persists today, mainly attributable to its highly limited availability. Despite this major setback, there is an increasing focus on evaluating and establishing clinical and research programs using helium ion beams, with both therapy and imaging initiatives to supplement the clinical palette of radiotherapy in the treatment of aggressive disease and sensitive clinical cases. Moreover, due its intermediate physical and radio-biological properties between proton and carbon ion beams, helium ions may provide a streamlined economic steppingstone towards an era of widespread use of different particle species in light and heavy ion therapy. With respect to the clinical proton beams, helium ions exhibit superior physical properties such as reduced lateral scattering and range straggling with higher relative biological effectiveness (RBE) and dose-weighted linear energy transfer (LET_d) ranging from ∼4 keVμm^-1to ∼40 keVμm^-1. In the frame of heavy ion therapy using carbon, oxygen or neon ions, where LET_dincreases beyond 100 keVμm^-1, helium ions exhibit similar physical attributes such as a sharp lateral penumbra, however, with reduced radio-biological uncertainties and without potentially spoiling dose distributions due to excess fragmentation of heavier ion beams, particularly for higher penetration depths. This roadmap presents an overview of the current state-of-the-art and future directions of helium ion therapy: understanding physics and improving modeling, understanding biology and improving modeling, imaging techniques using helium ions and refining and establishing clinical approaches and aims from learned experience with protons. These topics are organized and presented into three main sections, outlining current and future tasks in establishing clinical and research programs using helium ion beams-A. Physics B. Biological and C. Clinical Perspectives.

Biological Effects of Monoenergetic Carbon Ions and Their Associated Secondary Particles

DNA double-strand breaks (DSBs) are the main factor behind carbon-ion radiation therapy (CIRT)-induced cell death. Nuclear interactions along the beam path between the primary carbon ions and targets result in nuclear fragmentation of carbon ions and recoiled particles. These secondary particles travel further distances past the Bragg peak to the tail region, leading to unwanted biological effects that may result in cytotoxicity in critical organs and secondary induced tumors following CIRT. Here, we confirmed that the density of the DSB distributions increases as the cell survival decreases at the Bragg peak and demonstrated that by visualizing DSBs, the various LET fragmentation ions and recoiled particles produced differences in their biological effects in the post-Bragg peak tail regions. This suggests that the density of the DSBs within the high-LET track structures, rather than only their presence, is important for inducing cell death. These results are essential for CIRT treatment planning to limit the amount of healthy cell damage and reducing both the late effect and the secondary tumor-associated risk.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

Technical note: Providing proton fields down to the few-MeV level at clinical pencil beam scanning facilities for radiobiological experiments

PURPOSE

The adequate performance of radiobiological experiments using clinical proton beams typically requires substantial preparations to provide the appropriate setup for specific experiments. Providing radiobiologically interesting low-energy protons is a particular challenge, due to various physical effects that become more pronounced with larger absorber thickness and smaller proton energy. This work demonstrates the generation of decelerated low-energy protons from a clinical proton beam.

METHODS

Monte Carlo simulations of proton energy spectra were performed for energy absorbers with varying thicknesses to reduce the energy of the clinical proton beam down to the few-MeV level corresponding to μ m-ranges. In this way, a setup with an optimum thickness of the absorber with a maximum efficiency of the proton fluence for the provisioning of low-energy protons is supposed to be found. For the specific applications of 2.5-3.3 MeV protons and α -particle range equivalent protons, the relative depth dose was measured and simulated together with the dose-averaged linear energy transfer (LETd) distribution.

RESULTS

The resulting energy spectra from Monte Carlo simulations indicate an optimal absorber thickness for providing low-energy protons with maximum efficiency of proton fluence at an user-requested energy range for experiments. For instance, providing energies lower than 5 MeV, an energy spectrum with a relative total efficiency of 38.6 % to the initial spectrum was obtained with the optimal setup. The measurements of the depth dose, compared to the Monte Carlo simulations, showed that the dosimetry of low-energy protons works and protons with high LETd down to the range of α -particles can be produced.

CONCLUSIONS

This work provides a method for generating all clinically and radiobiologically relevant energies - especially down to the few-MeV level - at one clinical facility with pencil beam scanning. Thereby, it enables radiobiological experiments under environmentally uniform conditions.

A forty-year journey from "classical" biophysics and radiobiology to hadrontherapy, space radiation and low dose rate underground radiobiology

PURPOSE

As a biologist who, since the beginning of her involvement in science, has collaborated closely with physicists, I want to share my forty years of experience describing the events that introduced me to the world of charged particle radiation biology as well as that of low doses/dose rates, with related implications in medicine and radiation protection.

CONCLUSION

The main features of my experience can be summarized in the development of an interdisciplinary culture and in the interest in technological advances for the study of biological responses to radiation in different scenarios, relevant for public health. Mine was a journey that began by chance, but which led me to a world that proved to be of great interest to me. With the current advances in science, the new generations of scientists have new opportunities that I wish them to face with the same interest and enthusiasm that I felt for such an interdisciplinary field as that of radiation biology.

Mechanistic Modeling of the Relative Biological Effectiveness of Boron Neutron Capture Therapy

Accurate dosimetry and determination of the biological effectiveness of boron neutron capture therapy (BNCT) is challenging because of the mix of different types and energies of radiation at the cellular and subcellular levels. In this paper, we present a computational, multiscale system of models to better assess the relative biological effectiveness (RBE) and compound biological effectiveness (CBE) of several neutron sources as applied to BNCT using boronophenylalanine (BPA) and a potential monoclonal antibody (mAb) that targets HER-2-positive cells with Trastuzumab. The multiscale model is tested against published in vitro and in vivo measurements of cell survival with and without boron. The combined dosimetric and radiobiological model includes an analytical formulation that accounts for the type of neutron source, the tissue- or cancer-specific dose–response characteristics, and the microdistribution of boron. Tests of the model against results from published experiments with and without boron show good agreement between modeled and experimentally determined cell survival for neutrons alone and in combination with boron. The system of models developed in this work is potentially useful as an aid for the optimization and individualization of BNCT for HER-2-positive cancers, as well as other cancers, that can be targeted with mAb or a conventional BPA compound.

Fitting the Generalized Target Model to Cell Survival Data of Proton Radiation Reveals Dose-Dependent RBE and Inspires an Alternative Method to Estimate RBE in High-Dose Regions

The imprecise estimation of the relative biological effectiveness (RBE) of proton radiation has been one of the main challenges for further calculating the biologically effective dose in proton therapy. Since dose levels can greatly influence the proton RBE, the relationship between the two should be clarified first. In addition, since the dose-response curves are usually too complex to readily assess RBE in high-dose regions, a reliable and simple method is needed to predict the RBE of proton radiation accurately in clinically relevant doses. The standard linear-quadratic (LQ) model is widely used to determine the RBE of particles for clinical applications. However, there has been some debate over its use when modeling the cell survival curves in high-dose regions, since those survival curves usually show linear behavior in the semilogarithmic plot. By considering both cellular repair effects and indirect effects of radiation, we have proposed a generalized target model with linear-quadratic linear (LQL) characteristics. For the more accurate evaluation of proton RBE in radiotherapy, here we used this generalized target model to fit the cell survival data in V79 and C3H 10T1/2 cells exposed to proton radiation with different LETs. The fitting results show that the generalized target model works as well as the LQ model in general. Based on the fitting parameters of the generalized target model, the RBE of six given doses D_T (RBE_T) could be calculated in the corresponding cell lines with different LETs. The results show that the RBE_T gradually decreases with increased dose in both cell types. In addition, inspired by the calculation method of the maximum values of RBE (RBE_M) in the low-dose region, a novel method was proposed for estimating the RBE in the high-dose region (RBE_H) based on the slope ratio of the dose-response curves in this region. Linear regression analysis indicated a significant linear correlation between the proposed RBE_H and the RBE_T in high-dose regions, which suggests that the current method can be used as an alternative tool, which is both simple and robust, to estimate RBE in high-dose regions.

Monte Carlo simulations of a low energy proton beamline for radiobiological experiments

BACKGROUND

In order to determine the relative biological effectiveness (RBE) of protons with high accuracy, radiobiological experiments with detailed knowledge of the linear energy transfer (LET) are needed. Cell survival data from high LET protons are sparse and experiments with low energy protons to achieve high LET values are therefore required. The aim of this study was to quantify LET distributions from a low energy proton beam by using Monte Carlo (MC) simulations, and to further compare to a proton beam representing a typical minimum energy available at clinical facilities.

MATERIALS AND METHODS

A Markus ionization chamber and Gafchromic films were employed in dose measurements in the proton beam at Oslo Cyclotron Laboratory. Dose profiles were also calculated using the FLUKA MC code, with the MC beam parameters optimized based on comparisons with the measurements. LET spectra and dose-averaged LET (LET_d) were then estimated in FLUKA, and compared with LET calculated from an 80 MeV proton beam.

RESULTS

The initial proton energy was determined to be 15.5 MeV, with a Gaussian energy distribution of 0.2% full width at half maximum (FWHM) and a Gaussian lateral spread of 2 mm FWHM. The LET_d increased with depth, from approximately 5 keV/μm in the entrance to approximately 40 keV/μm in the distal dose fall-off. The LET_d values were considerably higher and the LET spectra were much narrower than the corresponding spectra from the 80 MeV beam.

CONCLUSIONS

MC simulations accurately modeled the dose distribution from the proton beam and could be used to estimate the LET at any position in the setup. The setup can be used to study the RBE for protons at high LET_d, which is not achievable in clinical proton therapy facilities.

NanOx, a new model to predict cell survival in the context of particle therapy

Particle therapy is increasingly attractive for the treatment of tumors and the number of facilities offering it is rising worldwide. Due to the well-known enhanced effectiveness of ions, it is of utmost importance to plan treatments with great care to ensure tumor killing and healthy tissues sparing. Hence, the accurate quantification of the relative biological effectiveness (RBE) of ions, used in the calculation of the biological dose, is critical. Nevertheless, the RBE is a complex function of many parameters and its determination requires modeling. The approaches currently used have allowed particle therapy to thrive, but still show some shortcomings. We present herein a short description of a new theoretical framework, NanOx, to calculate cell survival in the context of particle therapy. It gathers principles from existing approaches, while addressing some of their weaknesses. NanOx is a multiscale model that takes the stochastic nature of radiation at nanometric and micrometric scales fully into account, integrating also the chemical aspects of radiation-matter interaction. The latter are included in the model by means of a chemical specific energy, determined from the production of reactive chemical species induced by irradiation. Such a production represents the accumulation of oxidative stress and sublethal damage in the cell, potentially generating non-local lethal events in NanOx. The complementary local lethal events occur in a very localized region and can, alone, lead to cell death. Both these classes of events contribute to cell death. The comparison between experimental data and model predictions for the V79 cell line show a good agreement. In particular, the dependence of the typical shoulders of cell survival curves on linear energy transfer are well described, but also the effectiveness of different ions, including the overkill effect. These results required the adjustment of a number of parameters compatible with the application of the model in a clinical scenario thereby showing the potential of NanOx. Said parameters are discussed in detail in this paper.

Data-driven RBE parameterization for helium ion beams

Helium ion beams are expected to be available again in the near future for clinical use. A suitable formalism to obtain relative biological effectiveness (RBE) values for treatment planning (TP) studies is needed. In this work we developed a data-driven RBE parameterization based on published in vitro experimental values. The RBE parameterization has been developed within the framework of the linear-quadratic (LQ) model as a function of the helium linear energy transfer (LET), dose and the tissue specific parameter (α/β)ph of the LQ model for the reference radiation. Analytic expressions are provided, derived from the collected database, describing the RBEα = αHe/αph and Rβ = βHe/βph ratios as a function of LET. Calculated RBE values at 2 Gy photon dose and at 10% survival (RBE10) are compared with the experimental ones. Pearson's correlation coefficients were, respectively, 0.85 and 0.84 confirming the soundness of the introduced approach. Moreover, due to the lack of experimental data at low LET, clonogenic experiments have been performed irradiating A549 cell line with (α/β)ph = 5.4 Gy at the entrance of a 56.4 MeV u(-1)He beam at the Heidelberg Ion Beam Therapy Center. The proposed parameterization reproduces the measured cell survival within the experimental uncertainties. A RBE formula, which depends only on dose, LET and (α/β)ph as input parameters is proposed, allowing a straightforward implementation in a TP system.

A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data

Proton therapy treatments are currently planned and delivered using the assumption that the proton relative biological effectiveness (RBE) relative to photons is 1.1. This assumption ignores strong experimental evidence that suggests the RBE varies along the treatment field, i.e. with linear energy transfer (LET) and with tissue type. A recent review study collected over 70 experimental reports on proton RBE, providing a comprehensive dataset for predicting RBE for cell survival. Using this dataset we developed a model to predict proton RBE based on dose, dose average LET (LETd) and the ratio of the linear-quadratic model parameters for the reference radiation (α/β)x, as the tissue specific parameter. The proposed RBE model is based on the linear quadratic model and was derived from a nonlinear regression fit to 287 experimental data points. The proposed model predicts that the RBE increases with increasing LETd and decreases with increasing (α/β)x. This agrees with previous theoretical predictions on the relationship between RBE, LETd and (α/β)x. The model additionally predicts a decrease in RBE with increasing dose and shows a relationship between both α and β with LETd. Our proposed phenomenological RBE model is derived using the most comprehensive collection of proton RBE experimental data to date. Previously published phenomenological models, based on a limited data set, may have to be revised.

Variation in RBE for Survival of V79-4 Cells as a Function of Alpha-Particle (Helium Ion) Energy

High linear energy transfer (LET) α particles are important with respect to the carcinogenic risk associated with human exposure to ionizing radiation, most notably to radon and its progeny. Additionally, the potential use of alpha-particle-emitting radionuclides in radiotherapy is increasingly being explored. Within the body the emitted alpha particles slow down, traversing a number of cells with a range of energies and therefore with varying efficiencies at inducing biological response. The LET of the particle typically rises from between ~70-90 keV μm(-1) at the start of the track (depending on initial energy) to a peak of ~237 keV μm(-1) towards the end of the track, before falling again at the very end of its range. To investigate the variation in biological response with incident energy, a plutonium-238 alpha-particle irradiator was calibrated to enable studies with incident energies ranging from 4.0 MeV down to 1.1 MeV. The variation in clonogenic survival of V79-4 cells was determined as a function of incident energy, along with the relative variation in the initial yields of DNA double-strand breaks (DSB) measured using the FAR assay. The clonogenic survival data also extends previously published data obtained at the Medical Research Council (MRC), Harwell using the same cells irradiated with helium ions, with energies ranging from 34.9 MeV to 5.85 MeV. These studies were performed in conjunction with cell morphology measurements on live cells enabling the determination of absorbed dose and calculation of the average LET in the cell. The results show an increase in relative biological effectiveness (RBE) for cell inactivation with decreasing helium ion energy (increasing LET), reaching a maximum for incident energies of ~3.2 MeV and corresponding average LET of 131 keV μm(-1), above which the RBE is observed to fall at lower energies (higher LETs). The effectiveness of single alpha-particle traversals (relevant to low-dose exposure) at inducing cell inactivation was observed to increase with decreasing energy to a peak of ~68% survival probability for incident energies of ~1.8 MeV (average LET of 190 keV μm(-1)) producing ~0.39 lethal lesions per track. However, the efficiency of a single traversal will also vary significantly with cell morphology and angle of incidence, as well as cell type.

A critical study of different Monte Carlo scoring methods of dose average linear-energy-transfer maps calculated in voxelized geometries irradiated with clinical proton beams

We compare unrestricted dose average linear energy transfer (LET) maps calculated with three different Monte Carlo scoring methods in voxelized geometries irradiated with proton therapy beams with three different Monte Carlo scoring methods. Simulations were done with the Geant4 (Geometry ANd Tracking) toolkit. The first method corresponds to a step-by-step computation of LET which has been reported previously in the literature. We found that this scoring strategy is influenced by spurious high LET components, which relative contribution in the dose average LET calculations significantly increases as the voxel size becomes smaller. Dose average LET values calculated for primary protons in water with voxel size of 0.2 mm were a factor ~1.8 higher than those obtained with a size of 2.0 mm at the plateau region for a 160 MeV beam. Such high LET components are a consequence of proton steps in which the condensed-history algorithm determines an energy transfer to an electron of the material close to the maximum value, while the step length remains limited due to voxel boundary crossing. Two alternative methods were derived to overcome this problem. The second scores LET along the entire path described by each proton within the voxel. The third followed the same approach of the first method, but the LET was evaluated at each step from stopping power tables according to the proton kinetic energy value. We carried out microdosimetry calculations with the aim of deriving reference dose average LET values from microdosimetric quantities. Significant differences between the methods were reported either with pristine or spread-out Bragg peaks (SOBPs). The first method reported values systematically higher than the other two at depths proximal to SOBP by about 15% for a 5.9 cm wide SOBP and about 30% for a 11.0 cm one. At distal SOBP, the second method gave values about 15% lower than the others. Overall, we found that the third method gave the most consistent performance since it returned stable dose average LET values against simulation parameter changes and gave the best agreement with dose average LET estimations from microdosimetry calculations.

The effect of radiation quality on the risks of second malignancies

Abstract Purpose: Numerous studies have implicated elevated second cancer risks as a result of radiation therapy. Our aim in this paper was to contribute to an understanding of the effects of radiation quality on second cancer risks. In particular, we developed a biologically motivated model to study the effects of linear energy transfer (LET) of charged particles (including protons, alpha particles and heavy ions Carbon and Neon) on the risk of second cancer.

MATERIALS AND METHODS

A widely used approach to estimate the risk uses the so-called initiation-inactivation-repopulation model. Based on the available experimental data for the LET dependence of radiobiological parameters and mutation rate, we generalized this formulation to include the effects of radiation quality. We evaluated the secondary cancer risks for protons in the clinical range of LET, i.e., around 4-10 (KeV/μm), which lies in the plateau region of the Bragg peak.

RESULTS

For protons, at a fixed radiation dose, we showed that the increase in second cancer risks correlated directly with increasing values of LET to a certain point, and then decreased. Interestingly, we obtained a higher risk for proton LET of 10 KeV/μm compared to the lower LET of 4 KeV/μm in the low dose region. In the case of heavy ions, the risk was higher for Carbon ions than Neon ions (even though they have almost the same LET). We also compared protons and alpha particles with the same LET, and it was interesting to note that the second cancer risks were higher for protons compared to alpha particles in the low-dose region.

CONCLUSION

Overall, this study demonstrated the importance of including LET dependence in the estimation of second cancer risk. Our theoretical risk predictions were noticeably high; however, the biological end points should be tested experimentally for multiple treatment fields and to improve theoretical predictions.

Radiobiological intercomparison of the 160 MeV and 230 MeV proton therapy beams at the Harvard Cyclotron Laboratory and at Massachusetts General Hospital

The purpose of this study was to determine the relative biological effectiveness (RBE) along the axis of two range-modulated proton beams (160 and 230 MeV). Both the depth and the dose dependence of RBE were investigated. Chinese hamster V79-WNRE cells, suspended in medium containing gelatin and cooled to 2 °C, were used to obtain complete survival curves at multiple positions throughout the entrance and 10 cm spread-out Bragg peak (SOBP). Simultaneous measurements of the survival response to (60)Co gamma rays served as the reference data for the proton RBE determinations. For both beams the RBE increased significantly with depth in the 10 cm SOBP, particularly in the distal half of the SOBP, then rose even more sharply at the distal edge, the most distal position measured. At a 4 Gy dose of gamma radiation (S = 0.34) the average RBE values for the entrance, proximal half, distal half and distal edge were 1.07 ± 0.01, 1.10 ± 0.01, 1.17 ± 0.01 and 1.21 ± 0.01, respectively, and essentially the same for both beams. At a 2 Gy dose of gamma radiation (S = 0.71) the average RBE values rose to 1.13 ± 0.03, 1.15 ± 0.02, 1.26 ± 0.02 and 1.30 ± 0.02, respectively, for the same four regions of the SOBP. The difference between the 4 Gy and 2 Gy RBE values reflects the dose dependence of RBE as measured in these V79-WNRE cells, which have a low α/β value, as do other widely used cell lines that also show dose-dependent RBE values. Late-responding tissues are also characterized by low α/β values, so it is possible that these cell lines may be predictive for the response of such tissues (e.g., spinal cord, optic nerve, kidney, liver, lung). However, in the very small number of studies of late-responding tissues performed to date there appears to be no evidence of an increased RBE for protons at low doses. Similarly, RBE measurements using early responding in vivo systems (mostly mouse jejunum, an early-responding tissue which has a large α/β ∼ 10 Gy) have generally shown little or no detectable dose dependence. It is useful to compare the RBE values reported here to the commonly used generic clinical RBE of 1.1, which assumes no dependence on depth or on dose. Our proximal RBEs obviously avoid the depth-related increase in RBE and for doses of 4 Gy or more, the low-dose increase in RBE is also minimized, as shown in this article. Thus the proximal RBE at a 4 Gy dose of 1.10 ± 0.01, quoted above, represents an interesting point of congruence with the clinical RBE for conditions where it could reasonably be expected in the measurements reported here. The depth dependence of RBE reported here is consistent with the majority of measurements, both in vitro and in vivo, by other investigators. The dose dependence of RBE, on the other hand, is tissue specific but has not yet been demonstrated for protons by RBE values in late-responding normal tissue systems. This indicates a need for additional RBE determination as function of dose, especially in late-responding tissues.

Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer

Proton therapy treatments are based on a proton RBE (relative biological effectiveness) relative to high-energy photons of 1.1. The use of this generic, spatially invariant RBE within tumors and normal tissues disregards the evidence that proton RBE varies with linear energy transfer (LET), physiological and biological factors, and clinical endpoint. Based on the available experimental data from published literature, this review analyzes relationships of RBE with dose, biological endpoint and physical properties of proton beams. The review distinguishes between endpoints relevant for tumor control probability and those potentially relevant for normal tissue complication. Numerous endpoints and experiments on sub-cellular damage and repair effects are discussed. Despite the large amount of data, considerable uncertainties in proton RBE values remain. As an average RBE for cell survival in the center of a typical spread-out Bragg peak (SOBP), the data support a value of ~1.15 at 2 Gy/fraction. The proton RBE increases with increasing LETd and thus with depth in an SOBP from ~1.1 in the entrance region, to ~1.15 in the center, ~1.35 at the distal edge and ~1.7 in the distal fall-off (when averaged over all cell lines, which may not be clinically representative). For small modulation widths the values could be increased. Furthermore, there is a trend of an increase in RBE as (α/β)x decreases. In most cases the RBE also increases with decreasing dose, specifically for systems with low (α/β)x. Data on RBE for endpoints other than clonogenic cell survival are too diverse to allow general statements other than that the RBE is, on average, in line with a value of ~1.1. This review can serve as a source for defining input parameters for applying or refining biophysical models and to identify endpoints where additional radiobiological data are needed in order to reduce the uncertainties to clinically acceptable levels.

Future development of biologically relevant dosimetry

Proton and ion beams are radiotherapy modalities of increasing importance and interest. Because of the different biological dose response of these radiations as compared with high-energy photon beams, the current approach of treatment prescription is based on the product of the absorbed dose to water and a biological weighting factor, but this is found to be insufficient for providing a generic method to quantify the biological outcome of radiation. It is therefore suggested to define new dosimetric quantities that allow a transparent separation of the physical processes from the biological ones. Given the complexity of the initiation and occurrence of biological processes on various time and length scales, and given that neither microdosimetry nor nanodosimetry on their own can fully describe the biological effects as a function of the distribution of energy deposition or ionization, a multiscale approach is needed to lay the foundation for the aforementioned new physical quantities relating track structure to relative biological effectiveness in proton and ion beam therapy. This article reviews the state-of-the-art microdosimetry, nanodosimetry, track structure simulations, quantification of reactive species, reference radiobiological data, cross-section data and multiscale models of biological response in the context of realizing the new quantities. It also introduces the European metrology project, Biologically Weighted Quantities in Radiotherapy, which aims to investigate the feasibility of establishing a multiscale model as the basis of the new quantities. A tentative generic expression of how the weighting of physical quantities at different length scales could be carried out is presented.

Systematic analysis of RBE and related quantities using a database of cell survival experiments with ion beam irradiation

For tumor therapy with light ions and for experimental aspects in particle radiobiology the relative biological effectiveness (RBE) is an important quantity to describe the increased effectiveness of particle radiation. By establishing and analysing a database of ion and photon cell survival data, some remarkable properties of RBE-related quantities were observed. The database consists of 855 in vitro cell survival experiments after ion and photon irradiation. The experiments comprise curves obtained in different labs, using different ion species, different irradiation modalities, the whole range of accessible energies and linear energy transfers (LETs) and various cell types. Each survival curve has been parameterized using the linear-quadratic (LQ) model. The photon parameters, α and β, appear to be slightly anti-correlated, which might point toward an underlying biological mechanism. The RBE values derived from the survival curves support the known dependence of RBE on LET, on particle species and dose. A positive correlation of RBE with the ratio α/β of the photon LQ parameters is found at low doses, which unexpectedly changes to a negative correlation at high doses. Furthermore, we investigated the course of the β coefficient of the LQ model with increasing LET, finding typically a slight initial increase and a final falloff to zero. The observed fluctuations in RBE values of comparable experiments resemble overall RBE uncertainties, which is of relevance for treatment planning. The database can also be used for extensive testing of RBE models. We thus compare simulations with the local effect model to achieve this goal.

DNA and cellular effects of charged particles

Development of new radiotherapy strategies based on the use of hadrons, as well as reduction of uncertainties associated with radiation health risk during long-term space flights, requires increasing knowledge of the mechanisms underlying the biological effects of charged particles. It is well known that charged particles are more effective in damaging biological systems than photons. This capability has been related to the production of spatially correlated and/or clustered DNA damage, in particular two or more double-strand breaks (DSB) in close proximity or DSB associated with other lesions within a localized DNA region. These kinds of complex damages are rarely induced by photons. They are difficult to repair accurately and are therefore expected to produce severe consequences at the cellular level. This paper provides a review of radiation-induced cellular effects and will discuss the dependence of cell death and mutation induction on the linear energy transfer of various light and heavy ions. This paper will show the inadequacy of a single physical parameter for describing radiation quality, underlining the importance of the characteristics of the track structure at the submicrometer level to determine the biological effects. This paper will give a description of the physical properties of the track structure that can explain the differences in the spatial distributions of DNA damage, in particular DSB, induced by radiation of different qualities. In addition, this paper will show how a combined experimental and theoretical approach based on Monte Carlo simulations can be useful for providing information on the damage distribution at the nanoscale level. It will also emphasize the importance, especially for DNA damage evaluation at low doses, of the more recent functional approaches based on the use of fluorescent antibodies against proteins involved in the cellular processing of DNA damage. Advantages and limitations of the different experimental techniques will be discussed with particular emphasis on the still unsolved problem of the clustered DNA damage resolution. Development of biophysical models aimed to describe the kinetics of the DNA repair process is underway, and it is expected to support the experimental investigation of the mechanisms underlying the cellular radiation response.

Eighth Warren K. Sinclair keynote address: Heavy ions in therapy and space: benefits and risks

Heavy charged particles produce biological damage that is different from that normally produced by sparsely ionizing radiation, such as x- or gamma-rays, which are a large component of the natural radiation background. In fact, as a result of the different spatial distribution of the energy deposited along the core and penumbra of the track, DNA lesions are exquisitely complex and difficult to repair. Relative biological effectiveness (RBE) factors are normally used to scale from x-rays to heavy ion damage, but it should be kept in mind that RBE depends on several factors (dose, dose rate, endpoint, particle energy, and charge, etc.), and sometimes heavy ions produce special damages that just cannot be scaled by x-ray damage alone. These special characteristics of heavy ions can be used to treat tumors efficiently, as it is currently done in Japan and Germany, but they represent a threat for human space exploration.

Assessing the risk of second malignancies after modern radiotherapy

Recent advances in radiotherapy have enabled the use of different types of particles, such as protons and heavy ions, as well as refinements to the treatment of tumours with standard sources (photons). However, the risk of second cancers arising in long-term survivors continues to be a problem. The long-term risks from treatments such as particle therapy have not yet been determined and are unlikely to become apparent for many years. Therefore, there is a need to develop risk assessments based on our current knowledge of radiation-induced carcinogenesis.

Repair kinetic considerations in particle beam radiotherapy

OBJECTIVES

A second-order repair kinetics model is developed to predict damage repair rates following low or high linear energy transfer (LET) irradiations and to assess the amount of unrepairable damage produced by such radiations. The model is a further development of an earlier version designed to test if low-LET radiation repair processes could be quantified in terms of second-order kinetics. The newer version allows calculation of both the repair rate of the proportion of DNA damages that repair according to second-order kinetics and the proportion of DNA damages that do not repair.

METHODS

The original and present models are intercompared in terms of their goodness-of-fit to a number of data sets obtained from different ion beams. The analysis demonstrates that the present model provides a better fit to the data in all cases studied.

RESULTS

The proportions of unrepairable damage created by radiations of different LET predicted by the new model correspond well with previous studies on the increased effectiveness of high-LET radiations in inducing reproductive cell death. The results show that the original model may underestimate the proportion of unrepaired damage at any given time after its creation as well as failing to predict very slow or unrepairable damage components, which may result from high-LET irradiation.

CONCLUSION

It is suggested that the second-order model presented here offers a more realistic view of the patterns of repair in cell lines or tissues exposed to high-LET radiation.

A nanodosimetric model of radiation-induced clustered DNA damage yields

We present a nanodosimetric model for predicting the yield of double strand breaks (DSBs) and non-DSB clustered damages induced in irradiated DNA. The model uses experimental ionization cluster size distributions measured in a gas model by an ion counting nanodosimeter or, alternatively, distributions simulated by a Monte Carlo track structure code developed to simulate the nanodosimeter. The model is based on a straightforward combinatorial approach translating ionizations, as measured or simulated in a sensitive gas volume, to lesions in a DNA segment of one-two helical turns considered equivalent to the sensitive volume of the nanodosimeter. The two model parameters, corresponding to the probability that a single ion detected by the nanodosimeter corresponds to a single strand break or a single lesion (strand break or base damage) in the equivalent DNA segment, were tuned by fitting the model-predicted yields to previously measured double-strand break and double-strand lesion yields in plasmid DNA irradiated with protons and helium nuclei. Model predictions were also compared to both yield data simulated by the PARTRAC code for protons of a wide range of different energies and experimental DSB and non-DSB clustered DNA damage yield data from the literature. The applicability and limitations of this model in predicting the LET dependence of clustered DNA damage yields are discussed.

Direct Comparison of Biological Effectiveness of Protons and Alpha-particles of the Same LET. II. Mutation Induction at the HPRT Locus in V79 Cells

Mutation induction at the hprt locus has been studied in V79-4 Chinese hamster cells irradiated with mono-energetic protons and alpha-particles with LET of 20.3 and 23 keV microns-1. The mutation frequency increased linearly with the dose for all the four radiation qualities investigated, so that effectiveness for mutation induction could be expressed by the slope of the relevant curve. This effectiveness did not significantly change with the small change in LET of each kind of particle, while sizeable differences were found between particles. Protons were more effective in mutation induction than alpha-particles with the same LET by a factor of about 2. This finding is similar to, although slightly larger than, the factors 1.5-1.8 found for inactivation of the same cells in the same series of experiments.

Direct Comparison of Biological Effectiveness of Protons and Alpha-particles of the Same LET. III. Initial Yield of DNA Double-strand Breaks in V79 Cells

The results reported form part of a series of experiments to substantiate and extend the findings by Belli et al. (1989) that protons are more biologically effective at cell killing than alpha-particles of the same LET. The irradiations were carried out using the Variable Energy Cyclotron (VEC) at the Harwell Laboratories. V79-4 Chinese hamster cells were exposed to alpha-particles and protons with LETs of 20 and 23 keV microns-1 in the dose range 40-150 Gy. X-rays were also used for comparison. Two methods were used for measurement of initial DNA double-strand breaks: sedimentation and DNA precipitation assays. The dose-response relationships were found to be well fitted by straight lines in all cases. With the sedimentation assay a slightly lower yield of dsb was found from protons than from alpha-particles of the same LET. The yield from X-rays was not significantly different from either. The precipitation assay showed similar yields of DNA damage from both particle types but significantly higher yields from X-rays. This may reflect a difference in the type of lesions scored by the two methods. Since the initial amount of dsb does not account for the observed differences in cellular response to radiations of different qualities, it is likely that these are related to the nature of the dsb (affecting reparability) or to the occurrence of other types of molecular damage.

Detailed probabilistic modelling of cell inactivation by ionizing radiations of different qualities: the model and its applications

The probabilistic two-stage model of cell killing by ionizing radiation enables to represent both damage induction by radiation and its repair by the cell. The model properties and applications as well as possible interpretation of the underlying damage classification are discussed. Analyses of published survival data for V79 hamster cells irradiated by protons and He, C, O, and Ne ions are reported, quantifying the variations in radiation quality with increasing charge and linear energy transfer of the ions.

A model for the induction of DNA damages by fast neutrons and their evolution into cell clonogenic inactivation

It has been long stated that cellular inactivation through neutron irradiation is mainly caused by energy deposition in DNA molecules from recoiled secondary charged particles. Complexities associated with neutrons, such as the generally broad energy spectrum and the inherently wide energy spectrum of the induced charged particles, not to mention that the dependence of cellular inactivation by charged particles on radiation quality is yet to be fully understood, make it difficult to check this statement. Recently a molecular model has been proposed that improves the quantitative explanation of the dependence of cellular inactivation by charged particles on radiation quality. An attempt was made to apply this model for analysis of neutron cellular inactivation. As a preliminary result it is suggested that neutron cellular inactivation is caused not only by secondary charged particles but also by an "atomic deletion" effect, generated by a stripped atom recoiling from a DNA molecule. This effect seems to be of significant importance, the inactivation cross section of this effect for fission neutrons is as much as 15% (aerobic conditions) or 55% (hypoxic) of the total, and the severity of one occurrence of atomic deletion by a single neutron is estimated as much as 3.1 +/- 1.1 times (aerobic) or 6.8 +/- 1.2 times (hypoxic) higher than the severity of one event by a single track of a charged particle interacting with DNA.

Initial yields of DNA double-strand breaks and DNA Fragmentation patterns depend on linear energy transfer in tobacco BY-2 protoplasts irradiated with helium, carbon and neon ions

The ability of ion beams to kill or mutate plant cells is known to depend on the linear energy transfer (LET) of the ions, although the mechanism of damage is poorly understood. In this study, DNA double-strand breaks (DSBs) were quantified by a DNA fragment-size analysis in tobacco protoplasts irradiated with high-LET ions. Tobacco BY-2 protoplasts, as a model of single plant cells, were irradiated with helium, carbon and neon ions having different LETs and with gamma rays. After irradiation, DNA fragments were separated into sizes between 1600 and 6.6 kbp by pulsed-field gel electrophoresis. Information on DNA fragmentation was obtained by staining the gels with SYBR Green I. Initial DSB yields were found to depend on LET, and the highest relative biological effectiveness (about 1.6) was obtained at 124 and 241 keV/microm carbon ions. High-LET carbon and neon ions induced short DNA fragments more efficiently than gamma rays. These results partially explain the large biological effects caused by high-LET ions in plants.