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

Formation of spread-out Bragg peak for helium-ion beam using microdosimetric kinetic model

PURPOSE

To evaluate the applicability of microdosimetric kinetic model (MKM) to helium-ion therapy by forming a spread-out Bragg peak (SOBP) of a helium-ion beam using the MKM developed for carbon-ion radiotherapy and confirming the predictions in biological experiments.

METHODS

Using a ridge filter, a 90-mm wide SOBP for a 210 MeV/u helium-ion beam was created in a broad beam delivery system. The ridge filter was designed such that a uniform biological response was achieved with a cell survival rate of 7% over the SOBP region. Biological experiments were then performed using the SOBP beam in a human salivary gland (HSG) cell line to measure the cell survival rates.

RESULTS

The biological responses were uniform in the SOBP region, as expected by the MKM; however, the mean of the measured cell survival rates was (11.2 ± 0.6) % in the SOBP region, which was 60% higher than the designed rate. When investigating the biological parameters of the HSG cell line used in the experiments, we found that they were altered slightly from the MKM parameters used for carbon-ion radiotherapy. The new β parameter reproduced the measured survival rates within 6.5% in the SOBP region.

CONCLUSION

We produced biologically uniform SOBP using MKM for carbon-ion radiotherapy. The measured survival rates in the SOBP region were higher than expected, and the survival rates were reproduced by modifying the MKM parameter. This study was limited to one SOBP, and further investigations are required to prove that MKM is generally applicable to helium-ion radiotherapy.

Computational modeling and a Geant4-DNA study of the rejoining of direct and indirect DNA damage induced by low energy electrons and carbon ions

PURPOSE

DNA double-strand breaks (DSBs) created by ionizing radiations are considered as the most detrimental lesion, which could result in the cell death or sterilization. As the empirical evidence gathered from the cellular and molecular radiation biology has demonstrated significant correlations between the initial and lasting levels of DSBs, gaining knowledge into the DSB repair mechanisms proves vital. Much effort has been invested into understanding the mechanisms triggering the repair and processes engaged after irradiation of cells. Given a mechanistic model, we performed - to our knowledge - the first Monte Carlo study of the expected repair kinetics of carbon ions and electrons using on the one hand Geant4-DNA simulations of electrons for benchmarking purposes and on the other hand quantifying the influence of direct and indirect damage. Our objective was to calculate the DSB repair rates using a repair mechanism for G1 and early S phases of the cell cycle in conjunction with simulations of the DNA damage.

MATERIALS AND METHODS

Based on Geant4-DNA simulations of DSB damage caused by electrons and carbon ions - using a B-DNA model and a water sphere of 3 μm radius resembling the mean size of human cells - we derived the kinetics of various biochemical repair processes.

RESULTS

The overall repair times of carbon ions increased with the DSB complexity. Comparison of the DSB complexity (DSBc) and repair times as a function of carbon-ion energy suggested that the repair time of no specific fraction of DSBs could solely be explained as a function of DSB complexity.

CONCLUSION

Analysis of the carbon-ion repair kinetics indicated that, given a fraction of DSBs, decreasing the energy would result in an increase of the repair time. The disagreements of the calculated and experimental repair kinetics for electrons could, among others, be due to larger damage complexity predicted by simulations or created actually by electrons of comparable energies to x-rays. They are also due to the employed repair mechanisms, which introduce no inherent dependence on the radiation type but make direct use of the simulated DSBs.

A Mission to Mars: Prediction of GCR Doses and Comparison with Astronaut Dose Limits

Long-term human space missions such as a future journey to Mars could be characterized by several hazards, among which radiation is one the highest-priority problems for astronaut health. In this work, exploiting a pre-existing interface between the BIANCA biophysical model and the FLUKA Monte Carlo transport code, a study was performed to calculate astronaut absorbed doses and equivalent doses following GCR exposure under different shielding conditions. More specifically, the interface with BIANCA allowed us to calculate both the RBE for cell survival, which is related to non-cancer effects, and that for chromosome aberrations, related to the induction of stochastic effects, including cancer. The results were then compared with cancer and non-cancer astronaut dose limits. Concerning the stochastic effects, the equivalent doses calculated by multiplying the absorbed dose by the RBE for chromosome aberrations ("high-dose method") were similar to those calculated using the Q-values recommended by ICRP. For a 650-day mission at solar minimum (representative of a possible Mars mission scenario), the obtained values are always lower than the career limit recommended by ICRP (1 Sv), but higher than the limit of 600 mSv recently adopted by NASA. The comparison with the JAXA limits is more complex, since they are age and sex dependent. Concerning the deterministic limits, even for a 650-day mission at solar minimum, the values obtained by multiplying the absorbed dose by the RBE for cell survival are largely below the limits established by the various space agencies. Following this work, BIANCA, interfaced with an MC transport code such as FLUKA, can now predict RBE values for cell death and chromosome aberrations following GCR exposure. More generally, both at solar minimum and at solar maximum, shielding of 10 g/cm² Al seems to be a better choice than 20 g/cm² for astronaut protection against GCR.

Biophysical Modeling of the Ionizing Radiation Influence on Cells Using the Stochastic (Monte Carlo) and Deterministic (Analytical) Approaches

This review article describes our simplified biophysical model for the response of a group of cells to ionizing radiation. The model, which is a product of 10 years of studies, acts as (a) a comprehensive stochastic approach based on the Monte Carlo simulation with a probability tree and (b) the thereof derived detailed deterministic models describing the selected biophysical and radiobiological phenomena in an analytical manner. Specifically, the presented model describes effects such as the risk of neoplastic transformation of cells relative to the absorbed radiation dose, the dynamics of tumor development, the priming dose effect (also called the Raper–Yonezawa effect) based on the introduced adaptive response approach, and the bystander effect. The model is also modifiable depending on users’ potential needs.

Impact of DNA Geometry and Scoring on Monte Carlo Track-Structure Simulations of Initial Radiation-Induced Damage

Track structure Monte Carlo simulations are a useful tool to investigate the damage induced to DNA by ionizing radiation. These simulations usually rely on simplified geometrical representations of the DNA subcomponents. DNA damage is determined by the physical and physicochemical processes occurring within these volumes. In particular, damage to the DNA backbone is generally assumed to result in strand breaks. DNA damage can be categorized as direct (ionization of an atom part of the DNA molecule) or indirect (damage from reactive chemical species following water radiolysis). We also consider quasi-direct effects, i.e., damage originated by charge transfers after ionization of the hydration shell surrounding the DNA. DNA geometries are needed to account for the damage induced by ionizing radiation, and different geometry models can be used for speed or accuracy reasons. In this work, we use the Monte Carlo track structure tool TOPAS-nBio, built on top of Geant4-DNA, for simulation at the nanometer scale to evaluate differences among three DNA geometrical models in an entire cell nucleus, including a sphere/spheroid model specifically designed for this work. In addition to strand breaks, we explicitly consider the direct, quasi-direct, and indirect damage induced to DNA base moieties. We use results from the literature to determine the best values for the relevant parameters. For example, the proportion of hydroxyl radical reactions between base moieties was 80%, and between backbone, moieties was 20%, the proportion of radical attacks leading to a strand break was 11%, and the expected ratio of base damages and strand breaks was 2.5-3. Our results show that failure to update parameters for new geometric models can lead to significant differences in predicted damage yields.

4He dose- and track-averaged linear energy transfer: Monte Carlo algorithms and experimental verification

Objective. In the present hadrontherapy scenario, there is a growing interest in exploring the capabilities of different ion species other than protons and carbons. The possibility of using different ions paves the way for new radiotherapy approaches, such as the multi-ions treatment, where radiation could vary according to target volume, shape, depth and histologic characteristics of the tumor. For these reasons, in this paper, the study and understanding of biological-relevant quantities was extended for the case of 4He ion. Approach. Geant4 Monte Carlo based algorithms for dose- and track-averaged LET (Linear Energy Transfer) calculations, were validated for 4He ions and for the case of a mixed field characterised by the presence of secondary ions from both target and projectile fragmentation. The simulated dose and track averaged LETs were compared with the corresponding dose and frequency mean values of the lineal energy, y D ¯ and y ¯ F , derived from experimental microdosimetric spectra. Two microdosimetric experimental campaigns were carried out at the Italian eye proton therapy facility of the Laboratori Nazionali del Sud of Istituto Nazionale di Fisica Nucleare (INFN-LNS, Catania, I) using two different microdosimeters: the MicroPlus probe and the nano-TEPC (Tissue Equivalent Proportional Counter). Main results. A good agreement of L ¯ d Total and L ¯ t Total with y ¯ D and y ¯ T experimentally measured with both microdosimetric detectors MicroPlus and nano-TEPC in two configurations: full energy and modulated 4He ion beam, was found. Significance. The results of this study certify the use of a very effective tool for the precise calculation of LET, given by a Monte Carlo approach which has the advantage of allowing detailed simulation and tracking of nuclear interactions, even in complex clinical scenarios.

First application of the BIANCA biophysical model to carbon-ion patient cases

Objective. The main objective of this work consists of applying, for the first time, the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model to the RBE calculation for C-ion cancer patients, and comparing the outcomes with those obtained by the LEM I model, which is applied in clinics. Indeed, the continuous development of heavy-ion cancer therapy requires modelling of biological effects of ion beams on tumours and normal tissues. The relative biological effectiveness (RBE) of heavy ions is higher than that of protons, with a significant variation along the beam path. Therefore, it requires a precise modelling, especially for the pencil-beam scanning technique. Currently, two radiobiological models, LEM I and MKM, are in use for heavy ions in scanned pencil-beam facilities. Approach. Utilizing an interface with the FLUKA Particle Therapy Tool, BIANCA was applied to re-calculate the RBE-weighted dose distribution for carbon-ion treatment of three patients (chordoma, head-and-neck and prostate) previously irradiated at CNAO, where radiobiological optimization was based on LEM I. The predictions obtained by BIANCA were based either on chordoma cell survival (RBE surv ), or on dicentric aberrations in peripheral blood lymphocytes (RBE ab ), which are indicators of late normal tissue damage, including secondary tumours. The simulation outcomes were then compared with those provided by LEM I. Main results. While in the target and in the entrance channel BIANCA predictions were lower than those obtained by LEM I, the two models provided very similar results in the considered OAR. The observed differences between RBE surv and RBE ab (which were also dependent on fractional dose and LET) suggest that in normal tissues the information on cell survival should be integrated by information more closely related to the induction of late damage, such as chromosome aberrations. Significance. This work showed that BIANCA is suitable for treatment plan optimization in ion-beam therapy, especially considering that it can predict both cell survival and chromosome aberrations and has previously shown good agreement with carbon-ion experimental data.

On the calculation of the relative biological effectiveness of ion radiation therapy using a biological weighting function, the microdosimetric kinetic model (MKM) and subsequent corrections (non-Poisson MKM and modified MKM)

Objective. To investigate similarities and differences in the formalism, processing, and the results of relative biological effectiveness (RBE) calculations with a biological weighting function (BWF), the microdosimetric kinetic model (MKM) and subsequent modifications (non-Poisson MKM, modified MKM). This includes: (a) the extension of the V79-RBE10% BWF to model the RBE for other clonogenic survival levels; (b) a novel implementation of MKMs as weighting functions; (c) a benchmark against Chinese Hamster lung fibroblast (V79) in vitro data; (d) a study on the effect of pre- or post- processing the average biophysical quantities used for the RBE calculations; (e) a possible modification of the modified MKM parameters to improve the model accuracy at high linear energy transfer (LET). Methodology. Lineal energy spectra were simulated for two spherical targets (diameter = 0.464 or 1.0 μm) using PHITS for 1H, 4He, 12C, 20Ne, 40Ar, 56Fe and 132Xe ions. The results of the in silico calculations were compared with published in vitro data. Main results. All models appear to underestimate the RBE α of hydrogen ions. All MKMs generally overestimate the RBE50%, RBE10% and RBE1% for ions with an LET greater than ∼200 keV μm−1. This overestimation is greater for small surviving fractions and is likely due to the assumption of a radiation-independent quadratic term of clonogenic survival (ß). The overall RBE trends seem to be best described by the novel ‘post-processing average’ implementation of the non-Poisson MKM. In case of calculations with the non-Poisson MKM, pre- or post- processing the average biophysical quantities affects the computed RBE values significantly. Significance. This study presents a systematic analysis of the formalism and results of widely used microdosimetric models of clonogenic survival for ions relevant for cancer particle therapy and space radiation protection. Points for improvements were highlighted and will contribute to the development of upgraded biophysical models.

Radiobiological damage by space radiation: extension of the BIANCA model to heavy ions up to iron, and pilot application to cosmic ray exposure

Space research seems to be object of a renewed interest, also considering that human missions to the Moon, and possibly Mars, are being planned. Among the risks affecting such missions, astronauts' exposure to space radiation is a major concern. In this work, the question of the evaluation of biological damage by Galactic Cosmic Rays (GCR) was addressed by a biophysical model called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA), which simulates the induction of cell death and chromosome aberrations by different ions. While previously BIANCA has been validated for calculating cell death along hadrontherapy beams up to oxygen, herein the approach was extended up to Fe ions. Specifically, experimental survival curves available in literature for V79 cells irradiated by Si-, Ne-, Ar- and Fe-ions were reproduced, and a reference radiobiological database describing V79 cell survival as a function of ion type (1 ⩽Z⩽ 26), energy and dose was constructed. Analogous databases were generated for Chinese hamster ovary hamster cells and human skin fibroblasts, finding good agreement between simulations and data. Concerning chromosome aberrations, which are regarded as radiation risk biomarkers, dicentric data in human lymphocytes irradiated by heavy ions up to iron were reproduced, and a radiobiological database allowing calculation of lymphocyte dicentric yields as a function of dose, ion type (1 ⩽Z⩽ 26) and energy was constructed. Following interface between BIANCA and the FLUKA Monte Carlo transport code, a feasibility study was performed to calculate the relative biological effectiveness (RBE) of different GCR spectrum components, for both dicentrics and cell death. Fe-ions, although representing only 10% of the total absorbed dose, were found to be responsible for about 35%-40% of the RBE-weighted dose. Interestingly, the RBE for dicentrics was higher than that for cell survival. More generally, this work shows that BIANCA can calculate RBE values for cell death and lymphocyte dicentrics not only for ion therapy, but also for space radiation.

Extension of the BIANCA biophysical model up to Fe-ions and applications for space radiation research

BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) is a biophysical model, implemented as a Monte Carlo code, which simulates the induction of chromosome aberrations and cell death by different monochromatic ion beams (i.e., different ion types and energy values), as well as photons. In previous works, the model predictions for cell survival and lymphocyte dicentrics along therapeutic-like ion beams have been successfully benchmarked against experimental data. With the aim of evaluating the biological damage induced by Galactic Cosmic Rays (GCR), in this study BIANCA was extended up to Fe-ions. A radiobiological database describing human skin fibroblast cell survival and lymphocyte dicentrics as a function of ion type (1≤Z≤26) and energy, as well as dose, was constructed. Afterwards, interfacing BIANCA with the FLUKA Monte Carlo transport code, a feasibility study was performed to calculate the Relative Biological Effectiveness (RBE) of Galactic Cosmic Rays, both for dicentrics and for cell survival; the results were discussed with respect to available space radiation protection limits. Following this work, BIANCA can now provide RBE predictions of cell killing, which can be related to deterministic effects, and lymphocyte dicentrics, more related to stochastic effects, for space radiation exposure.

Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble

PURPOSE

The increased relative biological effectiveness (RBE) of ions is one of the key benefits of ion radiotherapy compared to conventional radiotherapy with photons. To account for the increased RBE of ions during the process of ion radiotherapy treatment planning, a robust model for RBE predictions is indispensable. Currently, at several ion therapy centers the local effect model I (LEM I) is applied to predict the RBE, which varies with biological and physical impacting factors. After the introduction of LEM I, several model improvements were implemented, leading to the current version, LEM IV, which is systematically tested in this study.

METHODS

As a comprehensive RBE model should give consistent results for a large variety of ion species and energies, the particle irradiation data ensemble (PIDE) is used to systematically validate the LEM IV. The database covers over 1100 photon and ion survival experiments in form of their linear-quadratic parameters for a wide range of ion types and energies. This makes the database an optimal tool to challenge the systematic dependencies of the RBE model. After appropriate filtering of the database, 571 experiments were identified and used as test data.

RESULTS

The study confirms that the LEM IV reflects the RBE systematics observed in measurements well. It is able to reproduce the dependence of RBE on the linear energy transfer (LET) as well as on the α_γ /β_γ ratio for several ion species in a wide energy range. Additionally, the systematic quantitative analysis revealed precision capabilities and limits of the model. At lower LET values, the LEM IV tends to underestimate the RBE with an increasing underestimation with increasing atomic number of the ion. At higher LET values, the LEM IV overestimates the RBE for protons or helium ions, whereas the predictions for heavier ions match experimental data well.

CONCLUSIONS

The LEM IV is able to predict general RBE characteristics for several ion species in a broad energy range. The accuracy of the predictions is reasonable considering the small number of input parameters needed by the model. The detailed quantification of possible systematic deviations, however, enables to identify not only strengths but also limitations of the model. The gained knowledge can be used to develop model adjustments to further improve the model accuracy, which is on the way.

Investigation into the foundations of the track-event theory of cell survival and the radiation action model based on nanodosimetry

This work aims at elaborating the basic assumptions behind the "track-event theory" (TET) and its derivate "radiation action model based on nanodosimetry" (RAMN) by clearly distinguishing between effects of tracks at the cellular level and the induction of lesions in subcellular targets. It is demonstrated that the model assumptions of Poisson distribution and statistical independence of the frequency of single and clustered DNA lesions are dispensable for multi-event distributions because they follow from the Poisson distribution of the number of tracks affecting the considered target volume. It is also shown that making these assumptions for the single-event distributions of the number of lethal and sublethal lesions within a cell would lead to an essentially exponential dose dependence of survival for practically relevant values of the absorbed dose. Furthermore, it is elucidated that the model equation used for consideration of repair within the TET is based on the assumption that DNA lesions induced by different tracks are repaired independently. Consequently, the model equation is presumably inconsistent with the model assumptions and requires an additional model parameter. Furthermore, the methodology for deriving model parameters from nanodosimetric properties of particle track structure is critically assessed. Based on data from proton track simulations it is shown that the assumption of statistically independent targets leads to the prediction of negligible frequency of clustered DNA damage. An approach is outlined how track structure could be considered in determining the model parameters, and the implications for TET and RAMN are discussed.

Comparison between the results of a recently-developed biological weighting function (V79-RBE10BWF) and thein vitroclonogenic survival RBE10of other repair-competent asynchronized normoxic mammalian cell lines and ions not used for the development of the model

728 simulated microdosimetric lineal energy spectra (26 different ions between 1H and 238U, 28 energy points from 1 to 1000 MeV/n) were used in combination with a recently-developed biological weighting function (Parisi et al., 2020) and 571 published in vitro clonogenic survival curves in order to: 1) assess prediction intervals for the in silico results by deriving an empirical indication of the experimental uncertainty from the dispersion in the in vitro hamster lung fibroblast (V79) data used for the development of the biophysical model; 2) explore the possibility of modeling the relative biological effectiveness (RBE) of the 10% clonogenic survival of asynchronized normoxic repair-competent mammalian cell lines other than the one used for the development of the model (V79); 3) investigate the predictive power of the model through a comparison between in silico results and in vitro data for 10 ions not used for the development of the model. At first, different strategies for the assessment of the in silico prediction intervals were compared. The possible sources of uncertainty responsible for the dispersion in the in vitro data were also shortly reviewed. Secondly, also because of the relevant scatter in the in vitro data, no statistically-relevant differences were found between the RBE10 of the investigated different asynchronized normoxic repair-competent mammalian cell lines. The only exception (Chinese Hamster peritoneal fibroblasts, B14FAF28), is likely due to the limited dataset (all in vitro ion data were extracted from a single publication), systematic differences in the linear energy transfer (LET) calculations for the employed very-heavy ions, and the use of reference photon survival curves extracted from a different publication. Finally, the in silico predictions for the 10 ions not used for the model development were in good agreement with the corresponding in vitro data.

Healthy Tissue Damage Following Cancer Ion Therapy: A Radiobiological Database Predicting Lymphocyte Chromosome Aberrations Based on the BIANCA Biophysical Model

Chromosome aberrations are widely considered among the best biomarkers of radiation health risk due to their relationship with late cancer incidence. In particular, aberrations in peripheral blood lymphocytes (PBL) can be regarded as indicators of hematologic toxicity, which is a major limiting factor of radiotherapy total dose. In this framework, a radiobiological database describing the induction of PBL dicentrics as a function of ion type and energy was developed by means of the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model, which has been previously applied to predict the effectiveness of therapeutic-like ion beams at killing tumour cells. This database was then read by the FLUKA Monte Carlo transport code, thus allowing us to calculate the Relative Biological Effectiveness (RBE) for dicentric induction along therapeutic C-ion beams. A comparison with previous results showed that, while in the higher-dose regions (e.g., the Spread-Out Bragg Peak, SOBP), the RBE for dicentrics was lower than that for cell survival. In the lower-dose regions (e.g., the fragmentation tail), the opposite trend was observed. This work suggests that, at least for some irradiation scenarios, calculating the biological effectiveness of a hadrontherapy beam solely based on the RBE for cell survival may lead to an underestimation of the risk of (late) damage to healthy tissues. More generally, following this work, BIANCA has gained the capability of providing RBE predictions not only for cell killing, but also for healthy tissue damage.

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.

A Mathematical Radiobiological Model (MRM) to Predict Complex DNA Damage and Cell Survival for Ionizing Particle Radiations of Varying Quality

Predicting radiobiological effects is important in different areas of basic or clinical applications using ionizing radiation (IR); for example, towards optimizing radiation protection or radiation therapy protocols. In this case, we utilized as a basis the ‘MultiScale Approach (MSA)’ model and developed an integrated mathematical radiobiological model (MRM) with several modifications and improvements. Based on this new adaptation of the MSA model, we have predicted cell-specific levels of initial complex DNA damage and cell survival for irradiation with ¹¹Β, ¹²C, ¹⁴Ν, ¹⁶Ο, ²⁰Νe, ⁴⁰Αr, ²⁸Si and ⁵⁶Fe ions by using only three input parameters (particle’s LET and two cell-specific parameters: the cross sectional area of each cell nucleus and its genome size). The model-predicted survival curves are in good agreement with the experimental ones. The particle Relative Biological Effectiveness (RBE) and Oxygen Enhancement Ratio (OER) are also calculated in a very satisfactory way. The proposed integrated MRM model (within current limitations) can be a useful tool for the assessment of radiation biological damage for ions used in hadron-beam radiation therapy or radiation protection purposes.

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).

In Vivo Validation of the BIANCA Biophysical Model: Benchmarking against Rat Spinal Cord RBE Data

(1) Background: Cancer ion therapy is constantly growing thanks to its increased precision and, for heavy ions, its increased biological effectiveness (RBE) with respect to conventional photon therapy. The complex dependence of RBE on many factors demands biophysical modeling. Up to now, only the Local Effect Model (LEM), the Microdosimetric Kinetic Model (MKM), and the "mixed-beam" model are used in clinics. (2) Methods: In this work, the BIANCA biophysical model, after extensive benchmarking in vitro, was applied to develop a database predicting cell survival for different ions, energies, and doses. Following interface with the FLUKA Monte Carlo transport code, for the first time, BIANCA was benchmarked against in vivo data obtained by C-ion or proton irradiation of the rat spinal cord. The latter is a well-established model for CNS (central nervous system) late effects, which, in turn, are the main dose-limiting factors for head-and-neck tumors. Furthermore, these data have been considered to validate the LEM version applied in clinics. (3) Results: Although further benchmarking is desirable, the agreement between simulations and data suggests that BIANCA can predict RBE for C-ion or proton treatment of head-and-neck tumors. In particular, the agreement with proton data may be relevant if the current assumption of a constant proton RBE of 1.1 is revised. (4) Conclusions: This work provides the basis for future benchmarking against patient data, as well as the development of other databases for specific tumor types and/or normal tissues.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

Radiation Track Structure: How the Spatial Distribution of Energy Deposition Drives Biological Response

Ionising radiation is incredibly effective at causing biological effects. This is due to the unique way energy is deposited along highly structured tracks of ionisation and excitation events, which results in correlation with sites of DNA damage from the nanometre to the micrometre scale. Correlation of these events along the track on the nanometre scale results in clustered damage, which not only results in the formation of DNA double-strand breaks (DSB), but also more difficult to repair complex DSB, which include additional damage within a few base pairs. The track structure varies significantly with radiation quality and the increase in relative biological effectiveness observed with increasing linear energy transfer in part corresponds to an increase in the probability and complexity of clustered DNA damage produced. Likewise, correlation over larger scales, associated with packing of DNA and associated chromosomes within the cell nucleus, can also have a major impact on the biological response. The proximity of the correlated damage along the track increases the probability of miss-repair through pairwise interactions resulting in an increase in probability and complexity of DNA fragments/deletions, mutations and chromosomal rearrangements. Understanding the mechanisms underlying the biological effectiveness of ionising radiation can provide an important insight into ways of increasing the efficacy of radiotherapy, as well as the risks associated with exposure. This requires a multi-scale approach for modelling, not only considering the physics of the track structure from the millimetre scale down to the nanometre scale, but also the structural packing of the DNA within the nucleus, the resulting chemistry in the context of the highly reactive environment of the nucleus, together with the subsequent biological response.

Stochastic multicellular modeling of x-ray irradiation, DNA damage induction, DNA free-end misrejoining and cell death

The repair or misrepair of DNA double-strand breaks (DSBs) largely determines whether a cell will survive radiation insult or die. A new computational model of multicellular, track structure-based and pO₂-dependent radiation-induced cell death was developed and used to investigate the contribution to cell killing by the mechanism of DNA free-end misrejoining for low-LET radiation. A simulated tumor of 1224 squamous cells was irradiated with 6 MV x-rays using the Monte Carlo toolkit Geant4 with low-energy Geant4-DNA physics and chemistry modules up to a uniform dose of 1 Gy. DNA damage including DSBs were simulated from ionizations, excitations and hydroxyl radical interactions along track segments through cell nuclei, with a higher cellular pO₂ enhancing the conversion of DNA radicals to strand breaks. DNA free-ends produced by complex DSBs (cDSBs) were able to misrejoin and produce exchange-type chromosome aberrations, some of which were asymmetric and lethal. A sensitivity analysis was performed and conditions of full oxia and anoxia were simulated. The linear component of cell killing from misrejoining was consistently small compared to values in the literature for the linear component of cell killing for head and neck squamous cell carcinoma (HNSCC). This indicated that misrejoinings involving DSBs from the same x-ray (including all associated secondary electrons) were rare and that other mechanisms (e.g. unrejoined ends) may be important. Ignoring the contribution by the indirect effect toward DNA damage caused the DSB yield to drop to a third of its original value and the cDSB yield to drop to a tenth of its original value. Track structure-based cell killing was simulated in all 135306 viable cells of a 1 mm³ hypoxic HNSCC tumor for a uniform dose of 1 Gy.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.

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.

Monoenergetic 290 MeV/n carbon-ion beam biological lethal dose distribution surrounding the Bragg peak

The sharp high dose Bragg peak of a carbon-ion beam helps it to deliver the highest dosage to the malignant cells while leaving the normal cells relatively unharmed. However, the precise range in which it distributes dosages that significantly induce cell death or genotoxicity surrounding its Bragg peak remains unclear. To evaluate biological effects of carbon-ion radiation through entrance to post Bragg peak in a single biological system, CHO and xrs5 cells were cultured in T-175 cell culture flasks and irradiated with 290 MeV/n monoenergetic carbon-ions with initial dosages upon entrance to the flask of 1, 2, or 3 Gy for cell survival assays or 1 Gy for cytokinesis block micronuclei assays. Under all initial dosages, the biological Bragg peak and the highest micronuclei formation was observed at the depth of 14.5 cm. Moreover, as the initial dosage increased the range displaying a significant decrease in survival fraction increased as well (P < 0.0001). Intriguingly from 1 Gy to 3 Gy, we observed a significant increase in reappearance of colony formation depth (P < 0.05), possibly indicating the nuclear fragmentation lethality potential of the carbon-ion. By means of our single system approach, we can achieve a more comprehensive understanding of biological effects surrounding of carbon-ions Bragg peak.

A New Standard DNA Damage (SDD) Data Format

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

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.