Inactivation of V79 cells by low-energy protons, deuterons and helium-3 ions

Ionization Detail Parameters for DNA Damage Evaluation in Charged Particle Radiotherapy: Simulation Study Based on Cell Survival Database

Details of excitation and ionization acts hide a description of the biological effects of charged particle traversal through living tissue. Nanodosimetry enables the introduction of novel quantities that characterize and quantify the particle track structure while also serving as a foundation for assessing biological effects based on this quantification. This presents an opportunity to enhance the planning of charged particle radiotherapy by taking into account the ionization detail. This work uses Monte Carlo simulations with Geant4-DNA code for a wide variety of charged particles and their radiation qualities to analyze the distribution of ionization cluster sizes within nanometer-scale volumes, similar to DNA diameter. By correlating these results with biological parameters extracted from the PIDE database for the V79 cell line, a novel parameter R2 based on ionization details is proposed for the evaluation of radiation quality in terms of biological consequences, i.e., radiobiological cross section for inactivation. By incorporating the probability p of sub-lethal damage caused by a single ionization, we address limitations associated with the usually proposed nanodosimetric parameter Fk for characterizing the biological effects of radiation. We show that the new parameter R2 correlates well with radiobiological data and can be used to predict biological outcomes.

An approach to assessing the contribution of the high LET effect in strategies for Auger endoradiotherapy

Purpose: The interest in exploiting Auger emitters in cancer therapy stems from their high linear energy transfer (LET)-type radiation damage to DNA. However, the design of Auger-emitter labeled vehicles that target the Auger cascade specifically to the DNA of tumour cells is challenging. Here we suggest a possible approach to evaluate tumour-targeting Auger-labeled conjugates by assessing the impact of a radioprotector known to be effective in protecting from low LET radiation, but not high LET radiation. Given some similarity between the energy spectrum of Auger electrons and that of secondary electrons from soft X-rays, we report the results of radioprotection experiments with 25 kVp X-rays. Materials and methods: Clonogenic survival curves for cultured human keratinocytes were established for three different irradiation conditions: ¹³⁷Cs γ-rays, 25 kVp X-rays and 320 kVp X-rays, and the effect of including a new radioprotector, denoted "2PH", was investigated.Results: The extent of radioprotection by 2PH was comparable for all radiation conditions, although RBE was higher (about 1.7) for soft X-rays. Conclusions: Radioprotectors like 2PH will help to evaluate Auger endoradiotherapy strategies, by determining the relative contributions of the high-LET effects (not protected), compared to other components, such as Auger electrons not effectively targeted to DNA.

Track Structure-Based Simulations on DNA Damage Induced by Diverse Isotopes

Diverse isotopes such as 2H, 3He, 10Be, 11C and 14C occur in nuclear reactions in ion beam radiotherapy, in cosmic ray shielding, or are intentionally accelerated in dating techniques. However, only a few studies have specifically addressed the biological effects of diverse isotopes and were limited to energies of several MeV/u. A database of simulations with the PARTRAC biophysical tool is presented for H, He, Li, Be, B and C isotopes at energies from 0.5 GeV/u down to stopping. The doses deposited to a cell nucleus and also the yields per unit dose of single- and double-strand breaks and their clusters induced in cellular DNA are predicted to vary among diverse isotopes of the same element at energies < 1 MeV/u, especially for isotopes of H and He. The results may affect the risk estimates for astronauts in deep space missions or the models of biological effectiveness of ion beams and indicate that radiation protection in 14C or 10Be dating techniques may be based on knowledge gathered with 12C or 9Be.

The Mayo Clinic Florida microdosimetric kinetic model of clonogenic survival: formalism and first benchmark against in vitro and in silico data

Objective. To develop a new model (Mayo Clinic Florida microdosimetric kinetic model, MCF MKM) capable of accurately describing the in vitro clonogenic survival at low and high linear energy transfer (LET) using single-event microdosimetric spectra in a single target. Methodology. The MCF MKM is based on the ‘post-processing average’ implementation of the non-Poisson microdosimetric kinetic model and includes a novel expression to compute the particle-specific quadratic-dependence of the cell survival with respect to dose (β of the linear-quadratic model). A new methodology to a priori calculate the mean radius of the MCF MKM subnuclear domains is also introduced. Lineal energy spectra were simulated with the Particle and Heavy Ion Transport code System (PHITS) for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe, and 132Xe ions and used in combination with the MCF MKM to calculate the ion-specific LET-dependence of the relative biological effectiveness (RBE) for Chinese hamster lung fibroblasts (V79 cell line) and human salivary gland tumor cells (HSG cell line). The results were compared with in vitro data from the Particle Irradiation Data Ensemble (PIDE) and in silico results of different models. The possibility of performing experiment-specific predictions to explain the scatter in the in vitro RBE data was also investigated. Finally, a sensitivity analysis on the model parameters is also included. Main results. The RBE values predicted with the MCF MKM were found to be in good agreement with the in vitro data for all tested conditions. Though all MCF MKM model parameters were determined a priori, the accuracy of the MCF MKM was found to be comparable or superior to that of other models. The model parameters determined a priori were in good agreement with the ones obtained by fitting all available in vitro data. Significance. The MCF MKM will be considered for implementation in cancer radiotherapy treatment planning with accelerated ions.

Development of modified microdosimetric kinetic model for relative biological effectiveness in proton therapy

To predict the biological effects of ionising radiation, the quantity of biological dose is introduced instead of the physical absorbed dose. In proton therapy, a constant relative biological effectiveness (RBE) of 1.1 is usually applied clinically as recommended by the International Commission of Radiation Units and Measurements. This study presents a new model, based on the modified microdosimetric kinetic model (MMKM), for calculating variable RBE values based on experimental data on the induction of DNA double-strand breaks (DSBs) within cells. The MMKM was proposed based on experimental data for the yield of DSBs in mammalian cells, which allows modification of the yield of primary lesions in the MKM. In this approach, a unique function named f(LET), which describes the relation between RBE and linear energy transfer (LET), was considered for charged particles. In the presented model (DMMKM), the MMKM approach was developed further by considering different f(LET)s for different relevant ions involved in energy deposition events in proton therapy. Although experimental data represent the dependence of the yield of primary lesions on the ion species, the DSB yield (assumed as the main primary lesion) is assumed independent of the ion species in the MMKM. In the DMMKM, by considering the yield of primary lesions as a function of the ion species, the α and β values are in better agreement with the experimental data as compared to those of the MKM and MMKM approaches. The biological dose in the DMMKM is predicted to be lower than that in the MMKM. Further, in the proposed model, the variation of the β parameter is higher than the constant value assumed in the MKM, at the distal end of the spread-out Bragg peak (SOBP). Moreover, the level of cell death estimated by the MMKM at the SOBP region is higher than that obtained based on the DMMKM. It is concluded that considering modified f(LET)s in the model developed here is more consistent with experimental results than when MMKM and MKM approaches are considered. The DMMKM examines the biological effects with full detail and will, therefore, be effective in improving proton therapy.

Taking Advantage of the Senescence-Promoting Effect of Olaparib after X-ray and Proton Irradiation Using the Senolytic Drug, ABT-263

Radiotherapy (RT) is a key component of cancer treatment. Although improvements have been made over the years, radioresistance remains a challenge. For this reason, a better understanding of cell fates in response to RT could improve therapeutic options to enhance cell death and reduce adverse effects. Here, we showed that combining RT (photons and protons) to noncytotoxic concentration of PARP inhibitor, Olaparib, induced a cell line-dependent senescence-like phenotype. The senescent cells were characterized by morphological changes, an increase in p21 mRNA expression as well as an increase in senescence-associated β-galactosidase activity. We demonstrated that these senescent cells could be specifically targeted by Navitoclax (ABT-263), a Bcl-2 family inhibitor. This senolytic drug led to significant cell death when combined with RT and Olaparib, while limited cytotoxicity was observed when used alone. These results demonstrate that a combination of RT with PARP inhibition and senolytics could be a promising therapeutic approach for cancer patients.

Biological effectiveness of He-3 and He-4 ion beams for cancer hadrontherapy: a study based on the BIANCA biophysical model

While cancer therapy with protons and C-ions is continuously spreading, in the near future patients will be also treated with He-ions which, in comparison to photons, combine the higher precision of protons with the higher relative biological effectiveness (RBE) of C-ions. Similarly to C-ions, also for He-ions the RBE variation along the beam must be known as precisely as possible, especially for active beam delivery systems. In this framework the BIANCA biophysical model, which has already been applied to calculate the RBE along proton and C-ion beams, was extended to⁴He-ions and, following interface with the FLUKA code, was benchmarked against cell survival data on CHO normal cells and Renca tumour cells irradiated at different positions along therapeutic-like⁴He-ion beams at the Heidelberg Ion-beam Therapy centre, where the first He-ion patient will be treated soon. Very good agreement between simulations and data was obtained, showing that BIANCA can now be used to predict RBE following irradiation with all ion types that are currently used, or will be used soon, for hadrontherapy. Thanks to the development of a reference simulation database describing V79 cell survival for ion and photon irradiation, these predictions can be cell-type specific because analogous databases can be produced, in principle, for any cell line. Furthermore, survival data on CHO cells irradiated by a He-3 beam were reproduced to compare the biophysical properties of He-4 and He-3 beams, which is currently an open question. This comparison showed that, at the same depth, He-4 beams tend to have a higher RBE with respect to He-3 beams, and that this difference is also modulated by the considered physical dose, as well as the cell radiosensitivity. However, at least for the considered cases, no significant difference was found for the ratio between the RBE-weighted dose in the SOBP and that in the entrance plateau.

Handling of beam spectra in training and application of proton RBE models

Published data from cell survival experiments are frequently used as training data for models of proton relative biological effectiveness (RBE). The publications rarely provide full information about the primary particle spectrum of the used beam, or its content of heavy secondary particles. The purpose of this paper is to assess to what extent heavy secondary particles may have been present in published cell survival experiments, and to investigate the impact of non-primary protons for RBE calculations in treatment planning. We used the Monte Carlo code Geant4 to calculate the occurrence of non-primary protons and heavier secondary particles for clinical protons beams in water for four incident energies in the [100, 250] MeV interval. We used the resulting spectra together with a conservative RBE parameterization and an RBE model to map both the rise of RBE at the beam entry surface due to heavy secondary particle buildup, and the difference in estimated RBE if non-primary protons are included or not in the beam quality metric. If included, non-primary protons cause a difference of 2% of the RBE in the plateau region of an spread out Bragg peak and 1% in the Bragg peak. Including non-primary protons specifically for RBE calculations will consequently have a negligible impact and can be ignored. A buildup distance in water of one millimeter was sufficient to reach an equilibrium state of RBE for the four incident energies selected. For the investigated experimental data, 83 out of the 86 data points were found to have been determined with at least that amount of buildup material. Hence, RBE model training data should be interpreted to include the contribution of heavy secondaries.

Does the uncertainty in relative biological effectiveness affect patient treatment in proton therapy?

Clinical treatment with protons uses the concept of relative biological effectiveness (RBE) to convert the absorbed dose into an RBE-weighted dose that equals the dose for radiotherapy with photons causing the same biological effect. Currently, in proton therapy a constant RBE of 1.1 is generically used. However, empirical data indicate that the RBE is not constant, but increases at the distal edge of the proton beam. This increase in RBE is of concern, as the clinical impact is still unresolved, and clinical studies demonstrating a clinical effect of an increased RBE are emerging. Within the European Particle Therapy Network (EPTN) work package 6 on radiobiology and RBE, a workshop was held in February 2020 in Manchester with one day of discussion dedicated to the impact of proton RBE in a clinical context. Current data on RBE effects, patient outcome and modelling from experimental as well as clinical studies were presented and discussed. Furthermore, representatives from European clinical proton therapy centres, who were involved in patient treatment, laid out their current clinical practice on how to consider the risk of a variable RBE in their centres. In line with the workshop, this work considers the actual impact of RBE issues on patient care in proton therapy by reviewing preclinical data on the relation between linear energy transfer (LET) and RBE, current clinical data sets on RBE effects in patients, and applied clinical strategies to manage RBE uncertainties. A better understanding of the variability in RBE would allow development of proton treatments which are safer and more effective.

A systematic review on the usage of averaged LET in radiation biology for particle therapy

Linear Energy Transfer (LET) is widely used to express the radiation quality of ion beams, when characterizing the biological effectiveness. However, averaged LET may be defined in multiple ways, and the chosen definition may impact the resulting reported value. We review averaged LET definitions found in the literature, and quantify which impact using these various definitions have for different reference setups. We recorded the averaged LET definitions used in 354 publications quantifying the relative biological effectiveness (RBE) of hadronic beams, and investigated how these various definitions impact the reported averaged LET using a Monte Carlo particle transport code. We find that the kind of averaged LET being applied is, generally, poorly defined. Some definitions of averaged LET may influence the reported averaged LET values up to an order of magnitude. For publications involving protons, most applied dose averaged LET when reporting RBE. The absence of what target medium is used and what secondary particles are included further contributes to an ill-defined averaged LET. We also found evidence of inconsistent usage of averaged LET definitions when deriving LET-based RBE models. To conclude, due to commonly ill-defined averaged LET and to the inherent problems of LET-based RBE models, averaged LET may only be used as a coarse indicator of radiation quality. We propose a more rigorous way of reporting LET values, and suggest that ideally the entire particle fluence spectra should be recorded and provided for future RBE studies, from which any type of averaged LET (or other quantities) may be inferred.

Proton therapy delivery method affects dose-averaged linear energy transfer in patients

The dosimetric advantages of proton therapy have led to its rapid proliferation in recent decades. This has been accompanied by a shift in technology from older units that deliver protons by passive scattering (PS) to newer units that increasingly use pencil-beam scanning (PBS). The biologic effectiveness of proton physical dose purportedly rises with increasing dose-weighted average linear energy transfer (LET_D). The objective of this study was to determine the extent to which proton delivery methods affect LET_D. We calculated LET_Dfrom simple, dosimetrically matched, and clinical treatment plans with TOPAS Monte-Carlo transport code. Simple treatment plans comprised single fields of PS and PBS protons in a water phantom. We performed simulations of matched and clinical treatment plans by using the treatment and anatomic data obtained from a cohort of children with craniopharyngioma who previously received PS or PBS proton therapy. We compared the distributions of LET_Dfrom PS and PBS delivery methods in clinically relevant ROIs. Wilcoxon signed-rank tests comparing single fields in water revealed that the LET_Dvalues from PBS were significantly greater than those from PS inside and outside the targeted volume (p < 0.01). Statistical tests comparing LET_D-volume histograms from matched and clinical treatment plans showed that LET_Dwas generally greater for PBS treatment plans than for PS treatment plans (p < 0.05). In conclusion, the proton delivery method affects LET_Dboth inside and outside of the target volume. These findings suggest that PBS is more biologically effective than PS. Given the rapid expansion of PBS proton therapy, future studies are needed to confirm the applicability of treatment evaluation methods developed for PS proton therapy to those for modern PBS treatments to ensure their safety and effectiveness for the growing population of patients receiving proton therapy. This study uses data from two clinical trials: NCT01419067 and NCT02792582.

Mapping the Relative Biological Effectiveness of Proton, Helium and Carbon Ions with High-Throughput Techniques

Large amounts of high quality biophysical data are needed to improve current biological effects models but such data are lacking and difficult to obtain. The present study aimed to more efficiently measure the spatial distribution of relative biological effectiveness (RBE) of charged particle beams using a novel high-accuracy and high-throughput experimental platform. Clonogenic survival was selected as the biological endpoint for two lung cancer cell lines, H460 and H1437, irradiated with protons, carbon, and helium ions. Ion-specific multi-step microplate holders were fabricated such that each column of a 96-well microplate is spatially situated at a different location along a particle beam path. Dose, dose-averaged linear energy transfer (LET_d), and dose-mean lineal energy (y_d) were calculated using an experimentally validated Geant4-based Monte Carlo system. Cells were irradiated at the Heidelberg Ion Beam Therapy Center (HIT). The experimental results showed that the clonogenic survival curves of all tested ions were y_d-dependent. Both helium and carbon ions achieved maximum RBEs within specific y_d ranges before biological efficacy declined, indicating an overkill effect. For protons, no overkill was observed, but RBE increased distal to the Bragg peak. Measured RBE profiles strongly depend on the physical characteristics such as y_d and are ion specific.

Development of a new microdosimetric biological weighting function for the RBE10 assessment in case of the V79 cell line exposed to ions from 1H to 238U

An improved biological weighting function (IBWF) is proposed to phenomenologically relate microdosimetric lineal energy probability density distributions with the relative biological effectiveness (RBE) for the in vitro clonogenic cell survival (surviving fraction = 10%) of the most commonly used mammalian cell line, i.e. the Chinese hamster lung fibroblasts (V79). The IBWF, intended as a simple and robust tool for a fast RBE assessment to compare different exposure conditions in particle therapy beams, was determined through an iterative global-fitting process aimed to minimize the average relative deviation between RBE calculations and literature in vitro data in case of exposure to various types of ions from ¹H to ²³⁸U. By using a single particle- and energy- independent function, it was possible to establish an univocal correlation between lineal energy and clonogenic cell survival for particles spanning over an unrestricted linear energy transfer range of almost five orders of magnitude (0.2 keV µm^-1 to 15 000 keV µm^-1 in liquid water). The average deviation between IBWF-derived RBE values and the published in vitro data was ∼14%. The IBWF results were also compared with corresponding calculations (in vitro RBE₁₀ for the V79 cell line) performed using the modified microdosimetric kinetic model (modified MKM). Furthermore, RBE values computed with the reference biological weighting function (BWF) for the in vivo early intestine tolerance in mice were included for comparison and to further explore potential correlations between the BWF results and the in vitro RBE as reported in previous studies. The results suggest that the modified MKM possess limitations in reproducing the experimental in vitro RBE₁₀ for the V79 cell line in case of ions heavier than ²⁰Ne. Furthermore, due to the different modelled endpoint, marked deviations were found between the RBE values assessed using the reference BWF and the IBWF for ions heavier than ²H. Finally, the IBWF was unchangingly applied to calculate RBE values by processing lineal energy density distributions experimentally measured with eight different microdosimeters in 19 ¹H and ¹²C beams at ten different facilities (eight clinical and two research ones). Despite the differences between the detectors, irradiation facilities, beam profiles (pristine or spread out Bragg peak), maximum beam energy, beam delivery (passive or active scanning), energy degradation system (water, PMMA, polyamide or low-density polyethylene), the obtained IBWF-based RBE trends were found to be in good agreement with the corresponding ones in case of computer-simulated microdosimetric spectra (average relative deviation equal to 0.8% and 5.7% for ¹H and ¹²C ions respectively).

The impact of proton LET/RBE modeling and robustness analysis on base-of-skull and pediatric craniopharyngioma proton plans relative to VMAT

Purpose: Pediatric craniopharyngioma, adult base-of-skull sarcoma and chordoma cases are all regarded as priority candidates for proton therapy. In this study, a dosimetric comparison between volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) was first performed. We then investigated the impact of physical and biological uncertainties. We assessed whether IMPT plans remained dosimetrically superior when such uncertainty estimates were considered, especially with regards to sparing organs at risk (OARs).Methodology: We studied 10 cases: four chondrosarcoma, two chordoma and four pediatric craniopharyngioma. VMAT and IMPT plans were created according to modality-specific protocols. For IMPT, we considered (i) variable RBE modeling using the McNamara model for different values of (α/β)x, and (ii) robustness analysis with ±3 mm set-up and 3.5% range uncertainties.Results: When comparing the VMAT and IMPT plans, the dosimetric advantages of IMPT were clear: IMPT led to reduced integral dose and, typically, improved CTV coverage given our OAR constraints. When physical robustness analysis was performed for IMPT, some uncertainty scenarios worsened the CTV coverage but not usually beyond that achieved by VMAT. Certain scenarios caused OAR constraints to be exceeded, particularly for the brainstem and optical chiasm. However, variable RBE modeling predicted even more substantial hotspots, especially for low values of (α/β)x. Variable RBE modeling often prompted dose constraints to be exceeded for critical structures.Conclusion: For base-of-skull and pediatric craniopharyngioma cases, both physical and biological robustness analyses should be considered for IMPT: these analyses can substantially affect the sparing of OARs and comparisons against VMAT. All proton RBE modeling is subject to high levels of uncertainty, but the clinical community should remain cognizant possible RBE effects. Careful clinical and imaging follow-up, plus further research on end-of-range RBE mitigation strategies such as LET optimization, should be prioritized for these cohorts of proton patients.

Physical characteristics at the turnover-points of relative biological effect (RBE) with linear energy transfer (LET)

This paper considers the kinematic physical characteristics of ionic beams for maximum relative bio-effectiveness (RBE). RBE studies, based on heterogenous cell survival studies at different laboratories and linear energy transfer (LET) conditions for proton, helium, carbon, neon and argon ions, have been further analysed to determine the LET_U values where RBE is maximal and the LET-RBE relationship has a turnover point. The SRIM stopping power software and other classical equations are used to determine the particle velocities, kinetic energies and their effective ionic charges at LET_U. The estimated mean LET_U values increase with atomic number (Z). Each LET_U has a unique relativistic velocity, β  =  v/c, the velocity v expressed as a fraction of the speed of light, (c), and which is non-linearly proportional to Z. For ions helium and heavier ions, these velocities indicate that the effective charge Z ^* is around 0.99 of the full Z value at each LET_U, with remarkably stable velocities of 3-4 nm · fs^-1 per nucleon, or around 6-8 nm · fs^-1 per unit Z. For Z  =  1, (protons and deuterium) some values fall outside these ranges but the result depends on the mix of proton and deuterium used in experiments. An alternative index of βA/Z ² (A is the atomic mass number), suggests an average velocity of around 15 nm · fs^-1 for each particle at LET_U. These distances, traversed in the time of the radiochemical process initiation, are all within the dimensions of the nucleosome. Curve fitting of the data set provides a predictive equation for LET_U for any ion, as LET_U  =  30.4  +  [Formula: see text] (1  -  Exp[-0.61  √  (Z  -  1)]) when normalised to protons. These data can be extended to heavier ions such as silicon and iron and give values that are consistent with experimental data. Each ion probably has a unique LET_U value. Kinematic studies show maximum bio-effectiveness occurs at particle velocities where electron stripping remains at around 99% and where the velocity per nucleon is around 3-4 nm · fs^-1. This study enhances the limited prior knowledge about the physical conditions of particle beams that provide maximum bio-effectiveness, with applications in particle radiotherapy, radiation protection and space travel.

First benchmarking of the BIANCA model for cell survival prediction in a clinical hadron therapy scenario

In the framework of RBE modelling for hadron therapy, the BIANCA biophysical model was extended to O-ions and was used to construct a radiobiological database describing the survival of V79 cells as a function of ion type (1  ⩽  Z  ⩽  8) and energy. This database allowed performing RBE predictions in very good agreement with experimental data. A method was then developed to construct analogous databases for different cell lines, starting from the V79 database as a reference. Following interface to the FLUKA Monte Carlo radiation transport code, BIANCA was then applied for the first time to predict cell survival in a typical patient treatment scenario, consisting of two opposing fields of range-equivalent protons or C-ions. The model predictions were found to be in good agreement with CHO cell survival data obtained at the Heidelberg ion-beam therapy (HIT) centre, as well as predictions performed by the local effect model (version LEM IV). This work shows that BIANCA can be used to predict cell survival and RBE not only for V79 and AG01522 cells, as shown previously, but also, in principle, for any cell line of interest. Furthermore, following interface to a transport code like FLUKA, BIANCA can provide predictions of 3D biological dose distributions for hadron therapy treatments, thus laying the foundations for future applications in clinics.

Medium-thickness-dependent proton dosimetry for radiobiological experiments

A calibration method was proposed in the present work to determine the medium-thickness-dependent proton doses absorbed in cellular components (i.e., cellular cytoplasm and nucleus) in radiobiological experiments. Consideration of the dependency on medium thickness was crucial as the linear energy transfer (LET) of protons could rise to a sharp peak (known as the Bragg peak) towards the end of their ranges. Relationships between the calibration coefficient R vs medium-layer thickness were obtained for incident proton energies of 10, 15, 20, 25, 30 and 35 MeV, and for various medium thicknesses up to 5000 μm, where R was defined as the ratio D_A/D_E, D_A was the absorbed proton dose in cellular components, and D_E was the absorbed proton dose in a separate radiation detector. In the present work, D_A and D_E were determined using the MCNPX (Monte Carlo N-Particle eXtended) code version 2.4.0. For lower incident proton energies (i.e., 10, 15 and 20 MeV), formation of Bragg-peak-like features were noticed in their R-vs-medium-layer-thickness relationships, and large R values of >7 and >6 were obtained for cytoplasm and nucleus of cells, respectively, which highlighted the importance of careful consideration of the medium thickness in radiobiological experiments.

Radiation-induced synthetic lethality: combination of poly(ADP-ribose) polymerase and RAD51 inhibitors to sensitize cells to proton irradiation

Although improvements in radiation therapy were made over the years, radioresistance is still a major challenge. Cancer cells are often deficient for DNA repair response, a feature that is currently exploited as a new anti-cancer strategy. In this context, combination of inhibitors targeting complementary pathways is of interest to sensitize cells to radiation. In this work, we used PARP (Olaparib) and RAD51 (B02) inhibitors to radiosensitize cancer cells to proton and X-ray radiation. More particularly, Olaparib and B02 were used at concentration leading to limited cytotoxic (alone or in combination) but increasing cell death when the cells were irradiated. We showed that, although at limited concentration, Olaparib and B02 were able to radiosensitize different cancer cell lines, i.e. lung and pancreatic cancer cells. Antagonistic, additive or synergistic effects were observed and correlated to cell proliferation rate. The inhibitors enhanced persistent DNA damage, delayed apoptosis, prolonged cell cycle arrest and senescence upon irradiation. These results demonstrated that radiation-induced synthetic lethality might widen the therapeutic window, hence extending the use of PARP inhibitors to patients without BRCAness.

Modelling of Cellular Survival Following Radiation-Induced DNA Double-Strand Breaks

A mechanistic model of cellular survival following radiation-induced DNA double-strand breaks (DSBs) was proposed in this study. DSBs were assumed as the initial lesions in the DNA of the cell nucleus induced by ionizing radiation. The non-homologous end-joining (NHEJ) pathway was considered as the domain pathway of DSB repair in mammalian cells. The model was proposed to predict the relationship between radiation-induced DSBs in nucleus and probability of cell survival, which was quantitatively described by two input parameters and six fitting parameters. One input parameter was the average number of primary particles which caused DSB, the other input parameter was the average number of DSBs yielded by each primary particle that caused DSB. The fitting parameters were used to describe the biological characteristics of the irradiated cells. By determining the fitting parameters of the model with experimental data, the model is able to estimate surviving fractions for the same type of cells exposed to particles with different physical parameters. The model further revealed the mechanism of cell death induced by the DSB effect. Relative biological effectiveness (RBE) of charged particles at different survival could be calculated with the model, which would provide reference for clinical treatment.

Proton Relative Biological Effectiveness - Uncertainties and Opportunities

Proton therapy treatments are prescribed using a biological effectiveness relative to photon therapy of 1.1, that is, proton beams are considered to be 10% more biologically effective. Debate is ongoing as to whether this practice needs to be revised. This short review summarizes current knowledge on relative biological effectiveness variations and uncertainties in vitro and in vivo. Clinical relevance is discussed and strategies toward biologically guided treatment planning are presented.

Target Size Variation in Microdosimetric Distributions and its Impact on the Linear-Quadratic Parameterization of Cell Survival

The linear-quadratic (LQ) parameterization of survival fraction [SF( D)] inherently assumes that all cells in a population receive the same dose ( D), albeit the distribution of specific energy z over the individual cells f( z, D) can be very wide. From these microdosimetric distributions, which are target size dependent, we estimate the size of the cellular sensitive volume by analyzing its influence on the LQ parameterization of cell survival. A Monte Carlo track structure code was used to simulate detailed tracks from a ⁶⁰Co source as well as proton and carbon ions of various energies. From these tracks, f( z, D) distributions were calculated for spherical targets with diameters ranging from 10 nm to 12 μm. A cell survival function based on f( z, D) was fitted to experimental LQ α values, revealing an intrinsic limitation that target size imposes on the usage of f( z, D) to describe the linear term of the LQ parameterization. The results indicate that such threshold volume arises naturally from the relationship between the particle's probability of no-hit and the probability of cell survival. Further analysis led to the proposal of a radiobiological property [Formula: see text], defined as the mean lineal energy corresponding to the target size that allows equivalence between the mean inactivation dose (MID) and the mean specific energy [Formula: see text]. The fact that [Formula: see text] is an increasing continuous function of target size within the range of biological targets of interest in radiobiology, ensures the uniqueness of [Formula: see text] for any radiation quality, thus, its potential usefulness in modeling. In conclusion, an accurate estimation of such threshold volumes may be useful for improving modeling of cell survival curves.

Calcitriol and Calcidiol Can Sensitize Melanoma Cells to Low⁻LET Proton Beam Irradiation

Proton beam irradiation promises therapeutic utility in the management of uveal melanoma. Calcitriol (1,25(OH)₂D₃)—the biologically active metabolite of vitamin D₃—and its precursor, calcidiol (25(OH)D₃), exert pleiotropic effects on melanoma cells. The aim of the study was to evaluate the effect of both calcitriol and calcidiol on melanoma cell proliferation and their response to proton beam irradiation. Three melanoma cell lines (human SKMEL-188 and hamster BHM Ma and BHM Ab), pre-treated with 1,25(OH)₂D₃ or 25(OH)D₃ at graded concentrations (0, 10, 100 nM), were irradiated with 0–5 Gy and then cultured in vitro. Growth curves were determined by counting the cell number every 24 h up to 120 h, which was used to calculate surviving fractions. The obtained survival curves were analysed using two standard models: linear-quadratic and multi-target single hit. Calcitriol inhibited human melanoma proliferation at 10 nM, while only calcidiol inhibited proliferation of hamster lines at 10 and 100 nM doses. Treatment with either 1,25(OH)₂D₃ or 25(OH)D₃ radio sensitized melanoma cells to low doses of proton beam radiation. The strength of the effect increased with the concentration of vitamin D₃. Our data suggest that vitamin D₃ may be an adjuvant that modifies proton beam efficiency during melanoma therapy.

BIANCA, a biophysical model of cell survival and chromosome damage by protons, C-ions and He-ions at energies and doses used in hadrontherapy

An upgraded version of the BIANCA II biophysical model, which describes more realistically interphase chromosome organization and the link between chromosome aberrations and cell death, was applied to V79 and AG01522 cells exposed to protons, C-ions and He-ions over a wide LET interval (0.6-502 keV µm^-1), as well as proton-irradiated U87 cells. The model assumes that (i) ionizing radiation induces DNA 'cluster lesions' (CLs), where by definition each CL produces two independent chromosome fragments; (ii) fragment (distance-dependent) mis-rejoining, or un-rejoining, produces chromosome aberrations; (iii) some aberrations lead to cell death. The CL yield, which mainly depends on radiation quality but is also modulated by the target cell, is an adjustable parameter. The fragment un-rejoining probability, f, is the second, and last, parameter. The value of f, which is assumed to depend on the cell type but not on radiation quality, was taken from previous studies, and only the CL yield was adjusted in the present work. Good agreement between simulations and experimental data was obtained, suggesting that BIANCA II is suitable for calculating the biological effectiveness of hadrontherapy beams. For both V79 and AG01522 cells, the mean number of CLs per micrometer was found to increase with LET in a linear-quadratic fashion before the over-killing region, where a less rapid increase, with a tendency to saturation, was observed. Although the over-killing region deserves further investigation, the possibility of fitting the CL yields is an important feature for hadrontherapy, because it allows performing predictions also at LET values where experimental data are not available. Finally, an approach was proposed to predict the ion-response of the cell line(s) of interest from the ion-response of a reference cell line and the photon response of both. A pilot study on proton-irradiated AG01522 and U87 cells, taking V79 cells as a reference, showed encouraging results.

Study of the Influence of NanOx Parameters

NanOx is a new biophysical model that aims at predicting the biological effect of ions in the context of hadron therapy. It integrates the fully-stochastic nature of ionizing radiation both at micrometric and nanometric scales and also takes into account the production and diffusion of reactive chemical species. In order to further characterize the new framework, we discuss the meaning and relevance of most of the NanOx parameters by evaluating their influence on the linear-quadratic coefficient α and on the dose deposited to achieve 10% or 1% of cell survival, D10% or D1%, as a function of LET. We perform a theoretical study in which variations in the input parameters are propagated into the model predictions for HSG, V79 and CHO-K1 cells irradiated by monoenergetic protons and carbon ions. We conclude that, in the current version of NanOx, the modeling of a specific cell line relies on five parameters, which have to be adjusted to several experimental measurements: the average cellular nuclear radius, the linear-quadratic coefficients describing photon irradiations and the α values associated with two carbon ions of intermediate and high-LET values. This may have interesting implications toward a clinical application of the new biophysical model.

Modeling in vivo relative biological effectiveness in particle therapy for clinically relevant endpoints

BACKGROUND

The relative biological effectiveness (RBE) of particle therapy compared to photon radiotherapy is known to be variable but the exact dependencies are still subject to debate. In vitro data suggested that RBE is to a large extend independent of ion type if parametrized by the beam quality Q. This study analyzed the RBE dependence of pre-clinical data on late toxicity with an emphasis on the beam quality.

MATERIAL AND METHODS

Published pre-clinical RBE dose-response data of the spinal cord following one and two fractions of photon and carbon ion irradiation were compiled. The beam quality for each treatment condition was obtained from Monte Carlo simulations. The α_p and β_p parameters of the linear-quadratic (LQ) model for particle irradiation were determined from the pre-clinical data and was provided as a function of Q. An introduced model proposed α_p to increase linearly with Q and β_p to remain constant. RBE values predicted by the model were compared to the published data.

RESULTS

The α_p parameter was highly correlated with Q (R² = 0.96) with a linear slope of 0.019 Gy^-1. No significant variation of β_p with Q was found. RBE and Q were also highly correlated (R² = 0.98) for one and two fractions. The (extrapolated) RBE at Q = 0 (theoretical photon limit) for one and two fractions was 1.22 and significantly larger than 1 (p = .004). The model reproduced the dependence of RBE on fractionation well.

CONCLUSIONS

Fraction dose and beam quality Q were sufficient to describe the RBE variability for a late toxicity model within a carbon ion treatment field. Assuming the independence of the identified RBE parameters on the ion type might suggest the translation of variable (pre-) clinical RBE data from carbon ion to proton therapy.

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.

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra

PURPOSE

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET_d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model.

METHOD

The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET_d based models for a simulated spread out Bragg peak (SOBP) scenario.

RESULTS

The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22).

CONCLUSION

The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were observed for the SOBP scenario, both non-linear LET spectrum- and linear LET_d based models should be further evaluated in clinically realistic scenarios.

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.

Calculating Variations in Biological Effectiveness for a 62 MeV Proton Beam

A biophysical model of radiation-induced cell death and chromosome aberrations [called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA)] was further developed and applied to therapeutic protons. The model assumes a pivotal role of DNA cluster damage, which can lead to clonogenic cell death following three main steps: (i) a DNA “cluster lesion” (CL) produces two independent chromosome fragments; (ii) fragment mis-rejoining within a threshold distance d gives rise to chromosome aberrations; (iii) certain aberration types (dicentrics, rings, and large deletions) lead to clonogenic inactivation. The yield of CLs and the probability, f, that a chromosome fragment remains un-rejoined even if other fragment(s) are present within d, were adjustable parameters. The model, implemented as a MC code providing simulated dose–responses directly comparable with experimental data, was applied to pristine and modulated Bragg peaks of the proton beam used to treat eye melanoma at INFN-LNS in Catania, Italy. Experimental survival curves for AG01522 cells exposed to the Catania beam were reproduced, supporting the model assumptions. Furthermore, cell death and chromosome aberrations at different depths along a spread-out Bragg peak (SOBP) dose profile were predicted. Both endpoints showed an increase along the plateau, and high levels of damage were found also beyond the distal dose fall-off, due to low-energy protons. Cell death and chromosome aberrations were also predicted for V79 cells, in the same irradiation scenario as that used for AG01522 cells. In line with other studies, this work indicated that assuming a constant relative biological effectiveness (RBE) along a proton SOBP may be sub-optimal. Furthermore, it provided qualitative and quantitative evaluations of the dependence of the beam effectiveness on the considered endpoint and dose. More generally, this work represents an example of therapeutic beam characterization avoiding the use of experimental RBE values, which can be source of uncertainties.

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.

Analytical linear energy transfer model including secondary particles: calculations along the central axis of the proton pencil beam

In proton therapy, the relative biological effectiveness (RBE) depends on various types of parameters such as linear energy transfer (LET). An analytical model for LET calculation exists (Wilkens' model), but secondary particles are not included in this model. In the present study, we propose a correction factor, L sec, for Wilkens' model in order to take into account the LET contributions of certain secondary particles. This study includes secondary protons and deuterons, since the effects of these two types of particles can be described by the same RBE-LET relationship. L sec was evaluated by Monte Carlo (MC) simulations using the GATE/GEANT4 platform and was defined by the ratio of the LET d distributions of all protons and deuterons and only primary protons. This method was applied to the innovative Pencil Beam Scanning (PBS) delivery systems and L sec was evaluated along the beam axis. This correction factor indicates the high contribution of secondary particles in the entrance region, with L sec values higher than 1.6 for a 220 MeV clinical pencil beam. MC simulations showed the impact of pencil beam parameters, such as mean initial energy, spot size, and depth in water, on L sec. The variation of L sec with these different parameters was integrated in a polynomial function of the L sec factor in order to obtain a model universally applicable to all PBS delivery systems. The validity of this correction factor applied to Wilkens' model was verified along the beam axis of various pencil beams in comparison with MC simulations. A good agreement was obtained between the corrected analytical model and the MC calculations, with mean-LET deviations along the beam axis less than 0.05 keV μm(-1). These results demonstrate the efficacy of our new correction of the existing LET model in order to take into account secondary protons and deuterons along the pencil beam axis.

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.

Modeling radiation-induced cell death: role of different levels of DNA damage clustering

Some open questions on the mechanisms underlying radiation-induced cell death were addressed by a biophysical model, focusing on DNA damage clustering and its consequences. DNA "cluster lesions" (CLs) were assumed to produce independent chromosome fragments that, if created within a micrometer-scale threshold distance (d), can lead to chromosome aberrations following mis-rejoining; in turn, certain aberrations (dicentrics, rings and large deletions) were assumed to lead to clonogenic cell death. The CL yield and d were the only adjustable parameters. The model, implemented as a Monte Carlo code called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA), provided simulated survival curves that were directly compared with experimental data on human and hamster cells exposed to photons, protons, α-particles and heavier ions including carbon and iron. d = 5 μm, independent of radiation quality, and CL yields in the range ~2-20 CLs Gy(-1) cell(-1), depending on particle type and energy, led to good agreement between simulations and data. This supports the hypothesis of a pivotal role of DNA cluster damage at sub-micrometric scale, modulated by chromosome fragment mis-rejoining at micrometric scale. To investigate the features of such critical damage, the CL yields were compared with experimental or theoretical yields of DNA fragments of different sizes, focusing on the base-pair scale (related to the so-called local clustering), the kbp scale ("regional clustering") and the Mbp scale, corresponding to chromatin loops. Interestingly, the CL yields showed better agreement with kbp fragments rather than bp fragments or Mbp fragments; this suggests that also regional clustering, in addition to other clustering levels, may play an important role, possibly due to its relationship with nucleosome organization in the chromatin fiber.

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.

DSB repair model for mammalian cells in early S and G1 phases of the cell cycle: application to damage induced by ionizing radiation of different quality

The purpose of this work is to test the hypothesis that kinetics of double strand breaks (DSB) repair is governed by complexity of DSB. To test the hypothesis we used our recent published mechanistic mathematical model of DSB repair for DSB induced by selected protons, deuterons, and helium ions of different energies representing radiations of different qualities. In light of recent advances in experimental and computational techniques, the most appropriate method to study cellular responses in radiation therapy, and exposures to low doses of ionizing radiations is using mechanistic approaches. To this end, we proposed a 'bottom-up' approach to study cellular response that starts with the DNA damage. Monte Carlo track structure method was employed to simulate initial damage induced in the genomic DNA by direct and indirect effects. Among the different types of DNA damage, DSB are known to be induced in simple and complex forms. The DSB repair model in G1 and early S phases of the cell cycle was employed to calculate the repair kinetics. The model considers the repair of simple and complex DSB, and the DSB produced in the heterochromatin. The inverse sampling method was used to calculate the repair kinetics for each individual DSB. The overall repair kinetics for 500 DSB induced by single tracks of the radiation under test were compared with experimental results. The results show that the model is capable of predicting the repair kinetics for the DSB induced by radiations of different qualities within an accepted range of uncertainty.

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.

Influence of the nucleus area distribution on the survival fraction after charged particles broad beam irradiation

It is well known that broad beam irradiation with heavy ions leads to variation in the number of hit(s) received by each cell as the distribution of particles follows the Poisson statistics. Although the nucleus area will determine the number of hit(s) received for a given dose, variation amongst its irradiated cell population is generally not considered. In this work, we investigate the effect of the nucleus area's distribution on the survival fraction. More specifically, this work aims to explain the deviation, or tail, which might be observed in the survival fraction at high irradiation doses. For this purpose, the nucleus area distribution was added to the beam Poisson statistics and the Linear-Quadratic model in order to fit the experimental data. As shown in this study, nucleus size variation, and the associated Poisson statistics, can lead to an upward survival trend after broad beam irradiation. The influence of the distribution parameters (mean area and standard deviation) was studied using a normal distribution, along with the Linear-Quadratic model parameters (α and β). Finally, the model proposed here was successfully tested to the survival fraction of LN18 cells irradiated with a 85 keV µm(- 1) carbon ion broad beam for which the distribution in the area of the nucleus had been determined.

"Broadbeam" irradiation of mammalian cells using a vertical microbeam facility

A "broadbeam" facility is demonstrated for the vertical microbeam at Surrey's Ion Beam Centre, validating the new technique used by Barazzuol et al. (Radiat Res 177:651-662, 2012). Here, droplets with a diameter of about 4 mm of 15,000 mammalian cells in suspension were pipetted onto defined locations on a 42-mm-diameter cell dish with each droplet individually irradiated in "broadbeam" mode with 2 MeV protons and 4 MeV alpha particles and assayed for clonogenicity. This method enables multiple experimental data points to be rapidly collected from the same cell dish. Initially, the Surrey vertical beamline was designed for the targeted irradiation of single cells with single counted ions. Here, the benefits of both targeted single-cell and broadbeam irradiations being available at the same facility are discussed: in particular, high-throughput cell irradiation experiments can be conducted on the same system as time-intensive focused-beam experiments with the added benefits of fluorescent microscopy, cell recognition and time-lapse capabilities. The limitations of the system based on a 2 MV tandem accelerator are also discussed, including the uncertainties associated with particle Poisson counting statistics, spread of linear energy transfer in the nucleus and a timed dose delivery. These uncertainties are calculated with Monte Carlo methods. An analysis of how this uncertainty affects relative biological effect measurements is made and discussed.

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.

Microdosimetric calculation of relative biological effectiveness for design of therapeutic proton beams

The authors attempt to establish the relative biological effectiveness (RBE) calculation for designing therapeutic proton beams on the basis of microdosimetry. The tissue-equivalent proportional counter (TEPC) was used to measure microdosimetric lineal energy spectra for proton beams at various depths in a water phantom. An RBE-weighted absorbed dose is defined as an absorbed dose multiplied by an RBE for cell death of human salivary gland (HSG) tumor cells in this study. The RBE values were calculated by a modified microdosimetric kinetic model using the biological parameters for HSG tumor cells. The calculated RBE distributions showed a gradual increase to about 1cm short of a beam range and a steep increase around the beam range for both the mono-energetic and spread-out Bragg peak (SOBP) proton beams. The calculated RBE values were partially compared with a biological experiment in which the HSG tumor cells were irradiated by the SOBP beam except around the distal end. The RBE-weighted absorbed dose distribution for the SOBP beam was derived from the measured spectra for the mono-energetic beam by a mixing calculation, and it was confirmed that it agreed well with that directly derived from the microdosimetric spectra measured in the SOBP beam. The absorbed dose distributions to planarize the RBE-weighted absorbed dose were calculated in consideration of the RBE dependence on the prescribed absorbed dose and cellular radio-sensitivity. The results show that the microdosimetric measurement for the mono-energetic proton beam is also useful for designing RBE-weighted absorbed dose distributions for range-modulated proton beams.