Study of the Influence of NanOx Parameters

Computational approaches in the estimation of radiobiological damage for human-malignant cells irradiated with clinical proton and carbon beams

PURPOSE

The use of Monte Carlo (MC) simulations capable of reproducing radiobiological effects of ionising radiation on human cell lines is of great importance, especially for cases involving protons and heavier ion beams. In the latter, huge uncertainties can arise mainly related to the effects of the secondary particles produced in the beam-tissue interaction. This paper reports on a detailed MC study performed using Geant4-based approach on three cancer cell lines, the HTB-177, CRL-5876 and MCF-7, that were previously irradiated with therapeutic proton and carbon ion beams.

METHODS

A Geant4-based approach used jointly with analytical calculations has been developed to provide a more realistic estimation of the radiobiological damage produced by proton and carbon beams in tissues, reproducing available data obtained from in vitro cell irradiations. The MC "Hadrontherapy" Geant4 application and the Local Effect Model: LEM I, LEM II and LEM III coupled with the different numerical approaches: RapidRusso (RR) and RapidScholz (RS) were used in the study.

RESULTS

Experimental survival curves are compared with those evaluated using the highlighted Geant4 MC-based approach via chi-square statistical analysis, for the combinations of radiobiological models and numerical approaches, as outlined above.

CONCLUSION

This study has presented a comparison of the survival data from MC simulations to experimental survival data for three cancer cell lines. An overall best level of agreement was obtained for the HTB-177 cells.

Track Structure of Light Ions: The Link to Radiobiology

It is generally recognized that the biological response to irradiation by light ions is initiated by complex damages at the DNA level. In turn, the occurrence of complex DNA damages is related to spatial and temporal distribution of ionization and excitation events, i.e., the particle track structure. It is the aim of the present study to investigate the correlation between the distribution of ionizations at the nanometric scale and the probability to induce biological damage. By means of Monte Carlo track structure simulations, the mean ionization yield M1 and the cumulative probabilities F1, F2, and F3 of at least one, two and three ionizations, respectively, were calculated in spherical volumes of water-equivalent diameters equal to 1, 2, 5 and 10 nm. When plotted as a function of M1, the quantities F1, F2 and F3 are distributed along almost unique curves, largely independent of particle type and velocity. However, the shape of the curves depends on the size of the sensitive volume. When the site size is 1 nm, biological cross sections are strongly correlated to combined probabilities of F2 and F3 calculated in the spherical volume, and the proportionality factor is the saturation value of biological cross sections.

Effect of overdispersion of lethal lesions on cell survival curves

The linear-quadratic (LQ) model is the most commonly used mechanism to predict radiobiological outcomes. It has been used extensively to describe dose-responsein vitroandin vivo. There are, however, some questions about its applicability in terms of its capacity to represent some profound mechanistic behaviour. Specifically, empirical evidence suggests that the LQ model underestimates the survival of cells at low doses while overestimating cell death at higher doses. It is believed to be driven from the usual LQ model assumption that radiogenic lesions are Poisson distributed. In this context, we use a negative binomial (NB) distribution to study the effect of overdispersion on the shapes and the possibility of reducing dose-response curvature at higher doses. We develop an overdispersion model for cell survival using the non-homologous end-joining (NHEJ) pathway double-strand break (DSB) repair mechanism to investigate the effects of the overdispersion on probabilities of repair of DSBs. The error distribution is customised to ensure that the refined overdispersion parameter depends on the mean of the distribution. The predicted cell survival responses for V79, AG and HSG cells exposed to protons, helium and carbon ions are compared with the experimental data in low and high dose regions at various linear energy transfer (LET) values. The results indicate straightening of dose-response and approaching a log-linear behaviour at higher doses. The model predictions with the measured data show that the NB modelled survival curves agree with the data following medium and high doses. Model predictions are not validated at very tiny and very high doses; the approach presented provides an analysis of mechanisms at the microscopic level. This may help improve the understanding of radiobiological responses of survival curves and resolve discrepancies between experimental and theoretical predictions of cell survival models.

Monte Carlo transport of swift protons and light ions in water: The influence of excitation cross sections, relativistic effects, and Auger electron emission in w-values

PURPOSE

To develop a particle transport code to compute w-values and stopping power of swift ions in liquid water and gases of interest for reference dosimetry in hadrontherapy. To analyze the relevance of inelastic and post-collisional processes considered.

METHODS

The Monte Carlo code MDM was extended to the case of swift ion impact on liquid water (MDM-Ion). Relativistic corrections in the inelastic cross sections and the post-collisional Auger emission were considered. The effects of introducing different electronic excitation cross sections were also studied.

RESULTS

The stopping power of swift ions on liquid water, calculated with MDM-Ion, are in excellent agreement with recommended data. The w-values show a strong dependence on the electronic excitation cross sections and on the Auger electron emission. Comparisons with other Monte Carlo codes show the relevance of both the processes considered and of the cross sections employed. W and w-values for swift electron, proton, and carbon ions calculated with the MDM and MDM-Ion codes are in very close agreement with each other and with the 20.8 eV experimental value.

CONCLUSION

We found that w-values in liquid water are independent of ion charge and energy, as assumed in reference dosimetry for hadrontherapy from sparse experimental results for electron and ion impact on gases. Excitation cross sections and Auger emission included in Monte Carlo codes are critical in w-values calculations. The computation of this physical parameter should be used as a benchmark for micro-dosimetry investigations, to assess the reliability of the cross sections employed.

Impact of Hypoxia on Relative Biological Effectiveness and Oxygen Enhancement Ratio for a 62-MeV Therapeutic Proton Beam

This study uses the yields of double-strand breaks (DSBs) to determine the relative biological effectiveness (RBE) of proton beams, using cell survival as a biological endpoint. DSB induction is determined when cells locate at different depths (6 positions) along the track of 62 MeV proton beams. The DNA damage yields are estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes are estimated using Monte Carlo excision repair (MCER) simulations. The RBE for cell survival at different oxygen concentrations is calculated using the repair-misrepair-fixation (RMF) model. Using 60Co γ-rays (linear energy transfer (LET) = 2.4 keV/μm) as the reference radiation, the RBE for DSB induction and enzymatic DSB under aerobic condition (21% O2) are in the range 1.0-1.5 and 1.0-1.6 along the track depth, respectively. In accord with RBE obtained from experimental data, RMF model-derived RBE values for cell survival are in the range of 1.0-3.0. The oxygen enhancement ratio (OER) for cell survival (10%) decreases from 3.0 to 2.5 as LET increases from 1.1 to 22.6 keV/μm. The RBE values for severe hypoxia (0.1% O2) are in the range of 1.1-4.4 as LET increases, indicating greater contributions of direct effects for protons. Compared with photon therapy, the overall effect of 62 MeV proton beams results in greater cell death and is further intensified under hypoxic conditions.

Influence of gold nanoparticles embedded in water on nanodosimetry for keV photon irradiation

PURPOSE

For the past two decades, high-Z nanoparticles have been of high interest to improve the therapeutic outcomes of radiation therapy, especially for low-energy x-rays. Monte Carlo (MC) simulations have been used to evaluate the boost of dose deposition induced by Auger electrons near the nanoparticle surface, by calculating average energy deposition at the nanoscale. In this study, we propose to go beyond average quantities and quantify the stochastic nature of energy deposition at such a scale. We present results of probability density of the specific energy (restricted to ionization, excitation and electron attachment events) in cylindrical nanotargets of height and radius set at 10 nm. This quantity was evaluated for nanotargets located within 200 nm around 5-50 nm gold nanoparticles (GNPs), for 20-90 keV photon irradiation.

METHODS

This nanodosimetry study was based on the MC simulation MDM that allows tracking of electrons down to thermalization energy. We introduced a new quantity, namely the probability enhancement ratio (PER), by estimating the probability of imparting to nanotargets a restricted specific energy larger than a threshold z 0 (1, 10, and 20 kGy), normalized to the probability for pure water. The PER was calculated as a function of the distance between the nanotarget and the GNP surface. The threshold values were chosen in light of the biophysical model NanOx that predicts cell survival by calculating local lethal events based on the restricted specific energy and an effective local lethal function. z 0 then represents a threshold above which the nanotarget damages induce efficiently cell death.

RESULTS

Our calculations showed that the PER varied a lot with the GNP radius, the photon energy, z 0 and the distance of the GNP to the nanotarget. The highest PER was 95 when the nanotarget was located at 5 nm from the GNP surface, for a photon energy of 20 keV, a threshold of 20 kGy, and a GNP radius of 50 nm. This enhancement dramatically decreased with increasing GNP-nanotarget distances as it went below 1.5 for distances larger than 200 nm.

CONCLUSIONS

The PER seems better adapted than the mean dose deposition to describe the formation of biological damages. The significant increase of the PER within 200 nm around the GNP suggests that severe damages could occur for biological nanotargets located near the GNP. These calculations will be used as an input of the biophysical model NanOx to convert PER into estimation of radiation-induced cell death enhanced by GNPs.

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).

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.

Determination of the Effective Local Lethal Function for the NanOx Model

NanOx is a biophysical model recently developed in the context of hadrontherapy to predict the cell survival probability from ionizing radiation. It postulates that this may be factorized into two independent terms describing the cell response to two classes of biological events that occur in the sequence of an irradiation: the local lethal events that occur at nanometric scale and can by themselves induce cell death, and the non-local lethal events that lead to cell death by an effect of accumulation and/or interaction at a larger scale. Here we address how local lethal events are modeled in terms of the inactivation of undifferentiated nanometric targets via an "effective local lethal function F", which characterizes the response of each cell line to the spectra of "restricted specific energy". F is initially determined as a linear combination of basis functions. Then, a parametric expression is used to reproduce the function's main features, a threshold and a saturation, while at the same time reducing the number of free parameters. This strategy was applied to three cell lines in response to ions of different type and energy, which allows for benchmarking of the α(LET) curves predicted with both effective local lethal functions against the experimental data.

Comparison of biophysical models with experimental data for three cell lines in response to irradiation with monoenergetic ions

The relative biological effectiveness (RBE) in particle therapy is currently estimated using biophysical models. We compared experimental measurements to the α curves as function of linear energy transfer computed by the Local Effect Model (LEM I-IV), the Microdosimetric Kinetic Model (MKM) and the NanOx model for HSG, V79 and CHO-K1 cells in response to monoenergetic irradiations. Although the LEM IV and the MKM predictions accurately reproduced the trend observed in the data, NanOx yielded a better agreement than the other models for more irradiation configurations. Its χ 2 estimator was indeed the lowest for three over seven considered cases.