Simulation of DNA damage using Geant4-DNA: an overview of the "molecularDNA" example application

GANDALF: Generative ANsatz for DNA damage evALuation and Forecast. A neural network-based regression for estimating early DNA damage across micro-nano scales

PURPOSE

This study aims to develop a comprehensive simulation framework to connect radiation effects from the microscopic to the nanoscopic scale.

METHOD

The process begins with a Geant4-DNA simulation based on the example "molecularDNA", producing a dataset of twelve different types of early DNA damages within an Escherichia coli (E. coli) bacterium, generated by proton irradiation at different kinetic energies, giving a nano-scale view of the particle-matter interaction. Then we pass to the micro-scale with a Geant4 simulation, based on the example "radiobiology", providing a microscopic view of proton interactions with matter through the Linear Energy Transfer (LET). Then GANDALF (Generative ANsatz for DNA damage evALuation and Forecast) Machine Learning (ML) toolkit, a Neural Network (NN)-based regression system, is employed to correlate the micro-scale LET data with the nano-scale occurrences of DNA damages in the E. coli bacterium.

RESULTS

The trained ML algorithm provides a practical tool to convert LET curves versus depth in a water phantom into DNA damage curves for twelve distinct types of DNA damage. To assess the performance, we evaluated the choice and optimization of the regression system based on its interpolation and extrapolation capabilities, ensuring the model could reliably predict DNA damage under various conditions.

CONCLUSIONS

Through the synergistic integration of Geant4, Geant4-DNA and ML, the study provides a tool to easily convert the results at the micro-scale of Geant4 to those at the nano-scale of Geant4-DNA without having to deal with the high CPU time requirements of the latter.

Position in proton Bragg curve influences DNA damage complexity and survival in head and neck cancer cells

Background and purpose

Understanding the cellular and molecular effect of proton radiation, particularly the increased DNA damage complexity at the distal end of the Bragg curve, is current topic of investigation. This work aims to study in vitro clonogenic survival and DNA damage foci kinetics of a head and neck squamous cell carcinoma cell line at various positions along a double passively scattered Bragg curve. Complementary in silico studies are conducted to gain insights into the link between cell survival variations, experimentally yielded foci and the number and complexity of double strand breaks (DSBs).

Materials and methods

Proton irradiations are performed at the HollandPTC R&D proton beamline, using a double passively scattered setup. A custom water phantom setup is employed to accurately position the samples within the Bragg curve. FaDu cells are irradiated at the proximal 36 % point of the Bragg peak, (P36), proximal 80 % point of the Bragg peak (P80) and distal 20 % point of the Bragg peak (D20), with dose-averaged mean lineal energies (y D ¯ ) of 1.10 keV/μm, 1.80 keV/μm and 7.25 keV/μm, respectively.

Results

Clonogenic survival correlates strongly withy D ¯ , showing similar survival for P36 (D37%=3.0 Gy) and P80 (D37%=2.9 Gy), but decreased survival for D20 (D37% = 1.6 Gy). D20 irradiated samples exhibit increased 53BP1 foci shortly after irradiation, slower resolution of the foci, and larger residual 53BP1 foci after 24 h, indicating unrepaired complex breaks. These experimental observations are supported by the in silico study which demonstrates that irradiation at D20 leads to a 1.7-fold increase in complex DSBs with respect to the total number of strand breaks compared to P36 and P80.

Conclusions

This combined approach provides valuable insights into the cellular and molecular effect of proton radiation, emphasizing the increased DNA damage complexity at the distal end of the Bragg curve, and has the potential to enhance the efficacy of proton therapy.

Evaluating the biological impact of shelters on astronaut health during different solar particle events: a Geant4-DNA simulation study

Mechanistic Monte Carlo simulations have proven invaluable in tackling complex challenges in radiobiology, for example for protecting astronauts from solar particle events (SPEs) during deep space missions which remains an underexplored area. In this study, the Geant4-DNA Monte Carlo code was used to assess the DNA damage caused by SPEs and evaluate the protective effectiveness of a multilayer shelter. By examining the February 1956 and October 1989 SPEs-two extreme cases-the results showed that the proposed shelter reduced DNA damage by up to 57.9% for the October 1989 SPE and 36.7% for the February 1956 SPE. Cell repair and survival modeling further revealed enhanced cell survival with the shelter, reducing lethal DNA damage by up to 64.3% and 88.2% for February 1956 and October 1989 SPEs, respectively. The results presented here highlight the crucial importance of developing effective radiation shielding to protect astronauts during solar storms and emphasizes the need to improve predictions of solar particle events to optimize shelter design.

Modelling and validation of a 6 MV compact linear accelerator via Monte Carlo simulation using Geant4 Application for Tomographic Emission (GATE)

Objective. To accurately model and validate the 6 MV Elekta Compact linear accelerator using the Geant4 Application for Tomographic Emission (GATE). In particular, this study focuses on the precise calibration and validation of critical parameters, including jaw collimator positioning, electron source nominal energy, flattening filter geometry, and electron source spot size, which are often not provided in technical documentation.Methods. Simulation of the Elekta CompactTM6 MV linear accelerator was performed using the Geant4 Application for Tomographic Emission (GATE) v.9.1. A 50 cm × 50 cm × 50 cm water phantom was irradiated with a source-to-surface distance of 100 cm. Percentage Depth Dose Profile (PDD) and Lateral Dose Profile (Crossplane and Inplane) were assessed as reference dose measurements. The half-length field difference (FHLD) method was introduced to optimize the jaw collimator setup. Gamma index analysis was used to quantitatively assess the accuracy of the simulated dosimetry data in relation to the actual dose measurements.Results. Crucial parameters of the Linac Head have been successfully optimized. The validation achieved Gamma-Index acceptance rates of 97.93% for the Depth Dose profile, 100% for the Crossplane (X) Dose Profile, and 93.98% for the Inplane (Y) Dose Profile, all meeting the 1%/1 mm Gamma-Index criteria.Conclusion. The simulation and calibration of the Elekta Compact Linac have achieved a reliable model with high fidelity in dosimetry calculations which could pave the way for the future development and application of new techniques using Elekta CompactTMLinear Accelerator.

Targeted alpha therapies using 211At: A Geant4 simulation of dose and DNA damage

INTRODUCTION

Targeted alpha therapies show great potential for cancer treatment due to their high linear energy transfer (LET) and low range. 211At is currently employed in clinical trials. Targeted alpha therapies (TAT) are effective as an adjuvant treatment for cancer or to treat micrometastases and diffuse cancers. A deeper understanding of the induced initial damage is crucial to enhance treatment planning.

METHODS

This study shows Geant4(-DNA)-based simulations to calculate absorbed dose profiles and DNA damaging potential in intravenously administered TAT with 211At. It assumes radionuclide decay on the blood vessel wall, and calculates the DNA damage in the surrounding tissue.

RESULTS

The calculated dosimetric quantities show that the effect of such treatment is mainly due to the emitted alpha particles, and is localised in a region of up to 80μm from the blood vessel. The RBE of the treatment is in the range 2.5-4, and is calculated as a function of the number of double-strand breaks.

CONCLUSIONS

Targeted therapies with 211At are effective within the range of the emitted alpha particles. With its capacity to induce complex DNA damage in such a short range, it is very promising for localised treatment of small tumour cells or micrometastases.

Comparison of in vitro cell survival predictions using Monte Carlo methods for proton irradiation

PURPOSE

It is possible to combine theoretical models with Monte Carlo simulations to investigate the relationship between radiation-induced initial DNA damage and cell survival. Several combinations of models have been proposed in recent years, sparking interest in comparing their predictions in view of future clinical applications.

METHODS

Two in silico methods for calculating cell survival fractions were optimized for proton irradiation of the Chinese hamster V79 cell line, for LET values ranging from 3.40 and 100 keV/μm. These methods, based on different Monte Carlo codes and theoretical models, were benchmarked against published V79 cell survival data to identify the sources of discrepancies.

RESULTS

The predictive capacities of the methods were evaluated for several proton LET values using an external dataset. After recalibrating model parameters, multiple methods were assessed. This approach helped identify sources of variation, the main one being the simulated number of DSBs, which differed by a factor up to 3 between the two Monte Carlo codes. In this process a new method was defined, that, in all but one case, allows for a reduction in prediction error of up to 56%. Additionally, a freely available GUI for computing cell survival was refined, to facilitate further comparison of diverse theoretical models.

CONCLUSION

The systematic comparison of two predictive chains, characterized by distinct applicability ranges and features, was conducted. Optimization and analysis of various combinations were undertaken to elucidate differences. Addressing and minimizing such discrepancies will be crucial for further enhancing the reliability of predictive models of cell survival, aiming for biologically informed treatment planning.

Assessing the biological effects of boron neutron capture therapy through cellular DNA damage repair model

BACKGROUND

Boron neutron capture therapy (BNCT) is a targeted radiotherapy that relies on the 10B (n, α) 7Li reaction, which produces secondary particles with high linear energy transfer (LET), leading to a high relative biological effectiveness (RBE) in tumors. The biological effectiveness of BNCT is influenced by factors such as boron distribution and concentration, necessitating improved methods for assessing its radiobiological effects and clarifying the sensitivity of the differences in different factors to the biological effects.

PURPOSE

This paper introduces a method to evaluate the biological effects of BNCT using the cellular repair model. This method aims to overcome some of the limitations of current evaluation approaches. The primary goal is to provide guidance for clinical treatments and the development of boron drugs, as well as to investigate the impact of the synergistic effects of mixed radiation fields in BNCT on treatment outcomes.

METHODS

The approach involves three key steps: first, extending the radial energy deposition distribution of BNCT secondary particles using Geant4-DNA. This allows for the calculation of initial DNA double-strand breaks (DSBs) distributions for a given absorbed dose. Next, the obtained initial DSB distributions are used for DNA damage repair simulations to generate cell survival curves, then thereby quantifying RBE and compound biological effectiveness (CBE). The study also explores the synergistic effects of the mixed radiation fields in BNCT on assessing biological effects were also explored in depth.

RESULTS

The results showed that the RBE of boronophenylalanine (BPA) and sodium borocaptate (BSH) drugs at cell survival fraction 0.01 was 2.50 and 2.15, respectively. The CBE of the boron dose component was 3.60 and 0.73, respectively, and the RBE of the proton component was 3.21, demonstrating that BPA has a significantly higher biological impact than BSH due to superior cellular permeability. The proton dose significance in BNCT treatment is also underscored, necessitating consideration in both experimental and clinical contexts. The study demonstrates that synergistic effects between disparate radiation fields lead to increased misrepairs and enhanced biological impact. Additionally, the biological effect diminishes with rising boron concentration, emphasizing the need to account for intercellular DNA damage heterogeneity.

CONCLUSIONS

This methodology offers valuable insights for the development of new boron compounds and precise assessment of bio-weighted doses in clinical settings and can be adapted to other therapeutic modalities.

Development of a novel computational technique to create DNA and cell geometrical models for Geant4-DNA

BACKGROUND

This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve.

METHODS

A Python-based tool named "complexDNA" was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the "molecularDNA" Geant4-DNA example.

RESULTS

Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results.

CONCLUSIONS

This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The "complexDNA" tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model's accuracy.

Monte Carlo investigation of the nucleus size effect and cell's oxygen content on the damage efficiency of protons

Living tissues could suffer different types of DNA damage as a result of being exposed to ionizing radiations. Monte Carlo simulations of the underlying interactions have been instrumental in predicting the damage types and the processes involved. In this work, we employed Geant4-DNA and MCDS for extracting the initial DNA damage and investigating the dependence of damage efficiency on the cell's oxygen content. The frequency-mean lineal (y¯F) and specific (z¯F) energies were derived for a spherical volume of water of various diameters between 2 and 11.1 μm. This sphere would serve as the nucleus of a cell of 100 μm diameter, engulfed by a homogeneous beam of protons. These microdosimetric quantities were calculated assuming spherical samples of 1 μm diameter in MCDS. The simulation results showed that for 230 MeV protons, an increase in the oxygen content from 0 by 10% raised the frequency of single- and double-strand breaks and lowered the base damage frequency. The resulting damage frequencies appeared to be independent of nucleus diameter. For proton energies between 2 and 230 MeV,y¯Fshowed no dependence on the cell diameter and an increase of the cell size resulted in a decrease inz¯F.An increase in the proton energy slowed down the decreasing rate ofz¯Fas a function of nucleus diameter. However, the ratio ofy¯Fvalues corresponding to two proton energies of choice showed no dependence on the nucleus size and were equal to the ratio of the correspondingz¯Fvalues. Furthermore, the oxygen content of the cell did not affect these microdosimetric quantities. Contrary to damage frequencies, these quantities appeared to depend only on direct interactions due to deposited energies. Our calculations showed the near independence of DNA damages on the nucleus size of the human cells. The probabilities of different types of single and double-strand breaks increase with the oxygen content.

A mechanistic simulation of induced DNA damage in a bacterial cell by X- and gamma rays: a parameter study

Mechanistic Monte Carlo simulations calculating DNA damage caused by ionizing radiation are highly dependent on the simulation parameters. In the present study, using the Geant4-DNA toolkit, the impact of different parameters on DNA damage induced in a bacterial cell by X- and gamma-ray irradiation was investigated. Three geometry configurations, including the simple (without DNA details), the random (a random multiplication of identical DNA segments), and the fractal (a regular replication of DNA segments using fractal Hilbert curves), were simulated. Also, three physics constructors implemented in Geant4-DNA, i.e., G4EmDNAPhysics_option2, G4EmDNAPhysics_option4, and G4EmDNAPhysics_option6, with two energy thresholds of 17.5 eV and 5-37.5 eV were compared for direct DNA damage calculations. Finally, a previously developed mathematical model of cell repair called MEDRAS (Mechanistic DNA Repair and Survival) was employed to compare the impact of physics constructors on the cell survival curve. The simple geometry leads to undesirable results compared to the random and fractal ones, highlighting the importance of simulating complex DNA structures in mechanistic simulation studies. Under the same conditions, the DNA damage calculated in the fractal geometry was more consistent with the experimental data. All physics constructors can be used alternatively with the fractal geometry, provided that an energy threshold of 17.5 eV is considered for recording direct DNA damage. All physics constructors represent a similar behavior in generating cell survival curves, although the slopes of the curves are different. Since the inverse of the slope of a bacterial cell survival curve (i.e., the D10-value) is highly sensitive to the simulation parameters, it is not logical to determine an optimal set of parameters for calculating the D10-value by Monte Carlo simulation.

Quantitative analysis of dose dependent DNA fragmentation in dry pBR322 plasmid using long read sequencing and Monte Carlo simulations

Exposure to ionizing radiation can induce genetic aberrations via unrepaired DNA strand breaks. To investigate quantitatively the dose-effect relationship at the molecular level, we irradiated dry pBR322 plasmid DNA with 3 MeV protons and assessed fragmentation yields at different radiation doses using long-read sequencing from Oxford Nanopore Technologies. This technology applied to a reference DNA model revealed dose-dependent fragmentation, as evidenced by read length distributions, showing no discernible radiation sensitivity in specific genetic sequences. In addition, we propose a method for directly measuring the single-strand break (SSB) yield. Furthermore, through a comparative study with a collection of previous works on dry DNA irradiation, we show that the irradiation protocol leads to biases in the definition of ionizing sources. We support this scenario by discussing the size distributions of nanopore sequencing reads in the light of Geant4 and Geant4-DNA simulation toolkit predictions. We show that integrating long-read sequencing technologies with advanced Monte Carlo simulations paves a promising path toward advancing our comprehension and prediction of radiation-induced DNA fragmentation.

Clustered DNA Damage and its Complexity: Tracking the History

The concept of radiation-induced clustered damage in DNA has grown over the past several decades to become a topic of considerable interest across the scientific disciplines involved in studies of the biological effects of ionizing radiation. This paper, prepared for the 70th anniversary issue of Radiation Research, traces historical development of the three main threads of physics, chemistry, and biochemical/cellular responses that led to the hypothesis and demonstration that a key component of the biological effectiveness of ionizing radiation is its characteristic of producing clustered DNA damage of varying complexities. The physics thread has roots that started as early as the 1920s, grew to identify critical nanometre-scale clusterings of ionizations relevant to biological effectiveness, and then, by the turn of the century, had produced an extensive array of quantitative predictions on the complexity of clustered DNA damage from different radiations. Monte Carlo track structure simulation techniques played a key role through these developments, and they are now incorporated into many recent and ongoing studies modelling the effects of radiation. The chemistry thread was seeded by water-radiolysis descriptions of events in water as radical-containing "spurs," demonstration of the important role of the hydroxyl radical in radiation-inactivation of cells and the difficulty of protection by radical scavengers. This led to the concept and description of locally multiply damaged sites (LMDS) for DNA double-strand breaks and other combinations of DNA base damage and strand breakage that could arise from a spur overlapping, or created in very close proximity to, the DNA. In these ways, both the physics and the chemistry threads, largely in parallel, put out the challenge to the experimental research community to verify these predictions of clustered DNA damage from ionizing radiations and to investigate their relevance to DNA repair and subsequent cellular effects. The third thread, biochemical and cell-based research, responded strongly to the challenge by demonstrating the existence and biological importance of clustered DNA damage. Investigations have included repair of a wide variety of defined constructs of clustered damage, evaluation of mutagenic consequences, identification of clustered base-damage within irradiated cells, and identification of co-localization of repair complexes indicative of complex clustered damage after high-LET irradiation, as well as extensive studies of the repair pathways involved in repair of simple double-strand breaks. There remains, however, a great deal more to be learned because of the diversity of clustered DNA damage and of the biological responses.

"dsbandrepair" - An updated Geant4-DNA simulation tool for evaluating the radiation-induced DNA damage and its repair

PURPOSE

Interdisciplinary scientific communities have shown large interest to achieve a mechanistic description of radiation-induced biological damage, aiming to predict biological results produced by different radiation quality exposures. Monte Carlo track-structure simulations are suitable and reliable for the study of early DNA damage induction used as input for assessing DNA damage. This study presents the most recent improvements of a Geant4-DNA simulation tool named "dsbandrepair".

METHODS

"dsbandrepair" is a Monte Carlo simulation tool based on a previous code (FullSim) that estimates the induction of early DNA single-strand breaks (SSBs) and double-strand breaks (DSBs). It uses DNA geometries generated by the DNAFabric computational tool for simulating the induction of early single-strand breaks (SSBs) and double-strand breaks (DSBs). Moreover, the new tool includes some published radiobiological models for survival fraction and un-rejoined DSB. Its application for a human fibroblast cell and human umbilical vein endothelial cell containing both heterochromatin and euchromatin was conducted. In addition, this new version offers the possibility of using the new IRT-syn method for computing the chemical stage.

RESULTS

The direct and indirect strand breaks, SSBs, DSBs, and damage complexity obtained in this work are equivalent to those obtained with the previously published simulation tool when using the same configuration in the physical and chemical stages. Simulation results on survival fraction and un-rejoined DSB are in reasonable agreement with experimental data.

CONCLUSIONS

"dsbandrepair" is a tool for simulating DNA damage and repair, benchmarked against experimental data. It has been released as an advanced example in Geant4.11.2.

Modelling Cellular Response to Ionizing Radiation: Mechanistic, Semi-Mechanistic, and Phenomenological Approaches - A Historical Perspective

Radiation research is a multidisciplinary field, and among its many branches, mathematical and computational modelers have played a significant role in advancing boundaries of knowledge. A fundamental contribution is modelling cellular response to ionizing radiation as that is the key to not only understanding how radiation can kill cancer cells, but also cause cancer and other health issues. The invention of microdosimetry in the 1950s by Harold Rossi paved the way for brilliant scientists to study the mechanism of radiation at cellular and sub-cellular scales. This paper reviews some snippets of ingenious mathematical and computational models published in microdosimetry symposium proceedings and publications of the radiation research community. Among these are simulations of radiation tracks at atomic and molecular levels using Monte Carlo methods, models of cell survival, quantification of the amount of energy required to create a single strand break, and models of DNA-damage-repair. These models can broadly be categorized into mechanistic, semi-mechanistic, and phenomenological approaches, and this review seeks to provide historical context of their development. We salute pioneers of the field and great teachers who supported and educated the younger members of the community and showed them how to build upon their work.

Manipulating Radiation-Sensitive Z-DNA Conformation for Enhanced Radiotherapy

DNA double-strand breaks (DSBs) yield highly determines radiotherapy efficacy. However, improving the inherent radiosensitivity of tumor DNA to promote radiation-induced DSBs remains a challenge. Using theoretical and experimental models, the underexplored impact of Z-DNA conformations on radiosensitivity, yielding higher DSBs than other DNA conformations, is discovered. Thereout, a radiosensitization strategy focused on inducing Z-DNA conformation, utilizing CBL@HfO2 nanocapsules loaded with a Z-DNA inducer CBL0137, is proposed. A hollow mesoporous HfO2 (HM-HfO2) acts as a delivery and an energy depositor to promote Z-DNA breakage. The nanocapsule permits the smart DSBs accelerator that triggers its radiosensitization with irradiation stimulation. Impressively, the CBL@HfO2 facilitates the B-Z DNA conformational transition, augmenting DSBs about threefold stronger than irradiation alone, generating significant tumor suppression with a 30% cure rate. The approach enables DSBs augmentation by improving the inherent radiosensitivity of DNA. As such, it opens up an era of Z-DNA conformation manipulation in radiotherapy.

Simulation of Radiation-Induced DNA Damage and Protection by Histones Using the Code RITRACKS

(1) Background: DNA damage is of great importance in the understanding of the effects of ionizing radiation. Various types of DNA damage can result from exposure to ionizing radiation, with clustered types considered the most important for radiobiological effects. (2) Methods: The code RITRACKS (Relativistic Ion Tracks), a program that simulates stochastic radiation track structures, was used to simulate DNA damage by photons and ions spanning a broad range of linear energy transfer (LET) values. To perform these simulations, the transport code was modified to include cross sections for the interactions of ions or electrons with DNA and amino acids for ionizations, dissociative electron attachment, and elastic collisions. The radiochemistry simulations were performed using a step-by-step algorithm that follows the evolution of all particles in time, including reactions between radicals and DNA structures and amino acids. Furthermore, detailed DNA damage events, such as base pair positions, DNA fragment lengths, and fragment yields, were recorded. (3) Results: We report simulation results using photons and the ions 1H+, 4He2+, 12C6+, 16O8+, and 56Fe26+ at various energies, covering LET values from 0.3 to 164 keV/µm, and performed a comparison with other codes and experimental results. The results show evidence of DNA protection from damage at its points of contacts with histone proteins. (4) Conclusions: RITRACKS can provide a framework for studying DNA damage from a variety of ionizing radiation sources with detailed representations of DNA at the atomic scale, DNA-associated proteins, and resulting DNA damage events and statistics, enabling a broader range of future comparisons with experiments such as those based on DNA sequencing.

A spatial measure-valued model for radiation-induced DNA damage kinetics and repair under protracted irradiation condition

In the present work, we develop a general spatial stochastic model to describe the formation and repair of radiation-induced DNA damage. The model is described mathematically as a measure-valued particle-based stochastic system and extends in several directions the model developed in Cordoni et al. (Phys Rev E 103:012412, 2021; Int J Radiat Biol 1-16, 2022a; Radiat Res 197:218-232, 2022b). In this new spatial formulation, radiation-induced DNA damage in the cell nucleus can undergo different pathways to either repair or lead to cell inactivation. The main novelty of the work is to rigorously define a spatial model that considers the pairwise interaction of lesions and continuous protracted irradiation. The former is relevant from a biological point of view as clustered lesions are less likely to be repaired, leading to cell inactivation. The latter instead describes the effects of a continuous radiation field on biological tissue. We prove the existence and uniqueness of a solution to the above stochastic systems, characterizing its probabilistic properties. We further couple the model describing the biological system to a set of reaction-diffusion equations with random discontinuity that model the chemical environment. At last, we study the large system limit of the process. The developed model can be applied to different contexts, with radiotherapy and space radioprotection being the most relevant. Further, the biochemical system derived can play a crucial role in understanding an extremely promising novel radiotherapy treatment modality, named in the community FLASH radiotherapy, whose mechanism is today largely unknown.

An inter-comparison between radiobiological characteristics of a commercial low-energy IORT system by Geant4-DNA and MCDS Monte Carlo codes

INTRODUCTION

The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code.

MATERIALS AND METHODS

RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical's chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions.

RESULTS

Acquired results by two considered MC codes showed that the same trend is found for RBEDSB and RBESSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBESSB and RBEDSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBESSB and RBEDSB values by two codes, respectively.

CONCLUSION

Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBEDSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBEDSB where lethal damages are regarded.

Geant4-DNA simulation of human cancer cells irradiation with helium ion beams

PURPOSE

This study aimed to develop a computational environment for the accurate simulation of human cancer cell irradiation using Geant4-DNA. New cell geometrical models were developed and irradiated by alpha particle beams to induce DNA damage. The proposed approach may help further investigation of the benefits of external alpha irradiation therapy.

METHODS

The Geant4-DNA Monte Carlo (MC) toolkit allows the simulation of cancer cell geometries that can be combined with accurate modelling of physical, physicochemical and chemical stages of liquid water irradiation, including radiolytic processes. Geant4-DNA is used to calculate direct and non-direct DNA damage yields, such as single and double strand breaks, produced by the deposition of energy or by the interaction of DNA with free radicals.

RESULTS

In this study, the "molecularDNA" example application of Geant4-DNA was used to quantify early DNA damage in human cancer cells upon irradiation with alpha particle beams, as a function of linear energy transfer (LET). The MC simulation results are compared to experimental data, as well as previously published simulation data. The simulation results agree well with the experimental data on DSB yields in the lower LET range, while the experimental data on DSB yields are lower than the results obtained with the "molecularDNA" example in the higher LET range.

CONCLUSION

This study explored and demonstrated the possibilities of the Geant4-DNA toolkit together with the "molecularDNA" example to simulate the helium beam irradiation of cancer cell lines, to quantify the early DNA damage, or even the following DNA damage response.