The origin of neutron biological effectiveness as a function of energy

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

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

A Monte Carlo model of the Dingo thermal neutron imaging beamline

In this study, we present a validated Geant4 Monte Carlo simulation model of the Dingo thermal neutron imaging beamline at the Australian Centre for Neutron Scattering. The model, constructed using CAD drawings of the entire beam transport path and shielding structures, is designed to precisely predict the in-beam neutron field at the position at the sample irradiation stage. The model's performance was assessed by comparing simulation results to various experimental measurements, including planar thermal neutron distribution obtained in-beam using gold foil activation and [Formula: see text]B[Formula: see text]C-coated microdosimeters and the out-of-beam neutron spectra measured with Bonner spheres. The simulation results demonstrated that the predicted neutron fluence at the field's centre is within 8.1% and 2.1% of the gold foil and [Formula: see text]B[Formula: see text]C-coated microdosimeter measurements, respectively. The logarithms of the ratios of average simulated to experimental fluences in the thermal (E[Formula: see text] 0.414 eV), epithermal (0.414 eV < E[Formula: see text] 11.7 keV) and fast (E[Formula: see text] 11.7 keV) spectral regions were approximately - 0.03 to + 0.1, - 0.2 to + 0.15, and - 0.4 to + 0.2, respectively. Furthermore, the predicted thermal, epithermal and fast neutron components in-beam at the sample stage position constituted approximately 18%, 64% and 18% of the total neutron fluence.

A Monte Carlo study on the impact of indirect action on neutron relative biological effectiveness

Recent Monte Carlo studies have linked the energy-dependent risk of neutron-induced stochastic effects to the relative biological effectiveness (RBE) of neutrons in inflicting difficult-to-repair clusters of lesions in nuclear deoxyribonucleic acid (DNA). However, an investigation on the damaging effects of indirect radiation action is missing from such studies. In this work, we extended our group's existing simulation pipeline by incorporating and validating a model for indirect action. Our updated simulation pipeline was used to study the impact of indirect action and estimate neutron RBE for inflicting clustered lesions in DNA. In our results, although indirect action significantly increased the average yield of DNA damage clusters, our neutron RBE values are lower in magnitude than previous estimates due to model limitations and the greater relative impact of indirect action in lower-linear energy transfer (LET) radiation than in higher-LET radiation.

Radiation environment in high-altitude Antarctic plateau: Recent measurements and model studies

Polar regions are the most exposed to secondary particles and radiation produced by primary cosmic rays in the atmosphere, because naturally they are with marginal geomagnetic shielding. In addition, the secondary particle flux contributing to the complex radiation field is enhanced at high-mountain altitudes compared to sea level because of the reduced atmospheric attenuation. At present, there are very few systematic experimental measurements of environmental dose at high southern latitudes, specifically at high-altitude region. Here, we report a campaign of measurements with different devices, that is passive and Liulin-type dosimeters, of the radiation background at high-mountain Antarctic station Vostok (3488 m above sea level, 78° 27' S; 106° 50' E). We compare the measurements with a Monte Carlo-based model for the propagation of the cosmic rays through the atmosphere and assessment of the radiation field in the atmosphere. We employed the model to estimate the radiation dose at Vostok station during the ground-level enhancement at 28 October 2021. As in previous studies by other teams, we show that the annual dose equivalent at high-altitude Antarctic facilities can significantly exceed the limit of 1 mSv established for the general population by the ICRP.

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.

MINAS TIRITH: a new tool for simulating radiation-induced DNA damage at the cell population level

Objective. The mechanisms of radiation-induced DNA damage can be understood via the fundamental acquisition of knowledge through a combination of experiments and modeling. Currently, most biological experiments are performed by irradiating an entire cell population, whereas modeling of radiation-induced effects is usually performed via Monte Carlo simulations with track structure codes coupled to realistic DNA geometries of a single-cell nucleus. However, the difference in scale between the two methods hinders a direct comparison because the dose distribution in the cell population is not necessarily uniform owing to the stochastic nature of the energy deposition. Thus, this study proposed the MINAS TIRITH tool to model the distribution of radiation-induced DNA damage in a cell population.Approach. The proposed method is based on precomputed databases of microdosimetric parameters and DNA damage distributions generated using the Geant4-DNA Monte Carlo Toolkit. First, a specific energyzwas assigned to each cell of an irradiated population for a particular absorbed doseDabs,following microdosimetric formalism. Then, each cell was assigned a realistic number of DNA damage events according to the specific energyz,respecting the stochastic character of its occurrence.Main results. This study validated the MINAS TIRITH tool by comparing its results with those obtained using the Geant4-DNA track structure code and a Geant4-DNA based simulation chain for DNA damage calculation. The different elements of comparison indicated consistency between MINAS TIRITH and the Monte Carlo simulation in case of the dose distribution in the population and the calculation of the amount of DNA damage.Significance. MINAS TIRITH is a new approach for the calculation of radiation-induced DNA damage at the cell population level that facilitates reasonable simulation times compared to those obtained with track structure codes. Moreover, this tool enables a more direct comparison between modeling and biological experimentation.

Neutron shielding assessment of a16O hadron therapy room by means of Monte Carlo simulations with the PHITS code

Hadron radiation therapy is of great interest worldwide. Heavy-ion beams provide ideal therapeutic conditions for deep-seated local tumours. At the Heidelberg Ion Beam Therapy Center (HIT, Germany), protons and carbon ions are already integrated into the clinical routine, while16O ions are still used for research only. To ensure the protection of the technical staff and members of the public, it is required to estimate the neutron dose distribution for optimal working conditions and at different locations. The Particle and Heavy Ion Transport Code System (PHITS) is used in this work to evaluate the dose rate distribution of secondary neutrons in a treatment room at HIT where16O ions are used: an equivalent target in soft tissue is considered in the shielding assessment to simulate the interaction of the beam with patients. The angular dependence of neutron fluences and energy spectra around the considered phantom were calculated. Alongside the spatial distribution of the neutron and photon fluence, a map of the effective dose rate was estimated using the ICRP fluence-to-effective dose conversion coefficients, exploiting the PHITS code's built-in capabilities. The capability of the actual shielding design of the studied HIT treatment room was approved.

A matter of space: how the spatial heterogeneity in energy deposition determines the biological outcome of radiation exposure

The outcome of the exposure of living organisms to ionizing radiation is determined by the distribution of the associated energy deposition at different spatial scales. Radiation proceeds through ionizations and excitations of hit molecules with an ~ nm spacing. Approaches such as nanodosimetry/microdosimetry and Monte Carlo track-structure simulations have been successfully adopted to investigate radiation quality effects: they allow to explore correlations between the spatial clustering of such energy depositions at the scales of DNA or chromosome domains and their biological consequences at the cellular level. Physical features alone, however, are not enough to assess the entity and complexity of radiation-induced DNA damage: this latter is the result of an interplay between radiation track structure and the spatial architecture of chromatin, and further depends on the chromatin dynamic response, affecting the activation and efficiency of the repair machinery. The heterogeneity of radiation energy depositions at the single-cell level affects the trade-off between cell inactivation and induction of viable mutations and hence influences radiation-induced carcinogenesis. In radiation therapy, where the goal is cancer cell inactivation, the delivery of a homogenous dose to the tumour has been the traditional approach in clinical practice. However, evidence is accumulating that introducing heterogeneity with spatially fractionated beams (mini- and microbeam therapy) can lead to significant advantages, particularly in sparing normal tissues. Such findings cannot be explained in merely physical terms, and their interpretation requires considering the scales at play in the underlying biological mechanisms, suggesting a systemic response to radiation.

Comparison of the Medical Uses and Cellular Effects of High and Low Linear Energy Transfer Radiation

Exposure to ionizing radiation can occur during medical treatments, from naturally occurring sources in the environment, or as the result of a nuclear accident or thermonuclear war. The severity of cellular damage from ionizing radiation exposure is dependent upon a number of factors including the absorbed radiation dose of the exposure (energy absorbed per unit mass of the exposure), dose rate, area and volume of tissue exposed, type of radiation (e.g., X-rays, high-energy gamma rays, protons, or neutrons) and linear energy transfer. While the dose, the dose rate, and dose distribution in tissue are aspects of a radiation exposure that can be varied experimentally or in medical treatments, the LET and eV are inherent characteristics of the type of radiation. High-LET radiation deposits a higher concentration of energy in a shorter distance when traversing tissue compared with low-LET radiation. The different biological effects of high and low LET with similar energies have been documented in vivo in animal models and in cultured cells. High-LET results in intense macromolecular damage and more cell death. Findings indicate that while both low- and high-LET radiation activate non-homologous end-joining DNA repair activity, efficient repair of high-LET radiation requires the homologous recombination repair pathway. Low- and high-LET radiation activate p53 transcription factor activity in most cells, but high LET activates NF-kB transcription factor at lower radiation doses than low-LET radiation. Here we review the development, uses, and current understanding of the cellular effects of low- and high-LET radiation exposure.

Fast and Furious: Fast Neutron Therapy in Cancer Treatment

Fast neutron therapy has been used for decades. In conjunction with recent advances in photonic techniques, fast neutrons are no longer of much oncologic interest, which is not unequivocally positive, given their undoubted therapeutic value. This mini-review recalls the history of medical research on fast neutrons, considers their physical and radiobiological properties alongside their benefits for cancer treatment, and discusses their place in modern radiation oncology.

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.

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.

Key biological mechanisms involved in high-LET radiation therapies with a focus on DNA damage and repair

DNA damage and repair studies are at the core of the radiation biology field and represent also the fundamental principles informing radiation therapy (RT). DNA damage levels are a function of radiation dose, whereas the type of damage and biological effects such as DNA damage complexity, depend on radiation quality that is linear energy transfer (LET). Both levels and types of DNA damage determine cell fate, which can include necrosis, apoptosis, senescence or autophagy. Herein, we present an overview of current RT modalities in the light of DNA damage and repair with emphasis on medium to high-LET radiation. Proton radiation is discussed along with its new adaptation of FLASH RT. RT based on α-particles includes brachytherapy and nuclear-RT, that is proton-boron capture therapy (PBCT) and boron-neutron capture therapy (BNCT). We also discuss carbon ion therapy along with combinatorial immune-based therapies and high-LET RT. For each RT modality, we summarise relevant DNA damage studies. Finally, we provide an update of the role of DNA repair in high-LET RT and we explore the biological responses triggered by differential LET and dose.

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body

OBJECTIVE

As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical CT scans.

APPROACH

A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT (WBCT) scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code.

MAIN RESULTS

The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively.

SIGNIFICANCE

The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.

Investigation of the effects of biomaterials on proton Bragg peak and secondary neutron production by the Monte Carlo method in the slab head phantom

Interest in proton therapy has increased in the last decade, as protons are effective to treat deeply located tumors, cause less damage to healthy tissue and allow controlling the energy to be transferred in a target-oriented manner (or energy transfer within target limits). It is known that secondary particles such as neutrons are produced by a result of nuclear interactions of protons with the target. Secondary neutrons can cause an uncontrolled dose increase in healthy tissue near the target site, and because they have a high radiobiological effectiveness, they raise the risk of secondary cancer. There are not enough studies examining the effect of biomaterials on secondary neutron production (SNP) in proton therapy. This study aims to investigate the effect of biomaterials used as implants instead of cranium in the skull on proton depth dose distribution and SNP with Monte Carlo-based PHITS code. Therefore, Bragg peaks and SNPs for 40-140 MeV energy protons were calculated and compared with the literature in a slab head phantom containing stainless steel, CoCrMo (CCM) alloy, alumina, polytetrafluoroethylene, Ti alloy, and NiTi alloy biomaterials used in cranioplasty. It was observed that the most compatible biomaterial compared to cranium for all energies is polytetrafluoroethylene. When polytetrafluoroethylene biomaterial was placed instead of the cranium in the skull, the Bragg peak position of the 100 MeV protons was decreased by 5.04% compared to that in the cranium. In this case, the energy absorbed in the polytetrafluoroethylene biomaterial increased by approximately 28% compared to the cranium, while it decreased by approx. 4% in the brain tissue. It was also observed that while SNP was 0.0501 in the cranium, it increased by almost 18% in PTFE.

DNA damage response of haematopoietic stem and progenitor cells to high-LET neutron irradiation

The radiosensitivity of haematopoietic stem and progenitor cells (HSPCs) to neutron radiation remains largely underexplored, notwithstanding their potential role as target cells for radiation-induced leukemogenesis. New insights are required for radiation protection purposes, particularly for aviation, space missions, nuclear accidents and even particle therapy. In this study, HSPCs (CD34⁺CD38⁺ cells) were isolated from umbilical cord blood and irradiated with ⁶⁰Co γ-rays (photons) and high energy p(66)/Be(40) neutrons. At 2 h post-irradiation, a significantly higher number of 1.28 ± 0.12 γ-H2AX foci/cell was observed after 0.5 Gy neutrons compared to 0.84 ± 0.14 foci/cell for photons, but this decreased to similar levels for both radiation qualities after 18 h. However, a significant difference in late apoptosis was observed with Annexin-V⁺/PI⁺ assay between photon and neutron irradiation at 18 h, 43.17 ± 6.10% versus 55.55 ± 4.87%, respectively. A significant increase in MN frequency was observed after both 0.5 and 1 Gy neutron irradiation compared to photons illustrating higher levels of neutron-induced cytogenetic damage, while there was no difference in the nuclear division index between both radiation qualities. The results point towards a higher induction of DNA damage after neutron irradiation in HSPCs followed by error-prone DNA repair, which contributes to genomic instability and a higher risk of leukemogenesis.

Towards the characterization of neutron carcinogenesis through direct action simulations of clustered DNA damage

Neutron exposure poses a unique radiation protection concern because neutrons have a large, energy-dependent relative biological effectiveness (RBE) for stochastic effects. Recent computational studies on the microdosimetric properties of neutron dose deposition have implicated clustered DNA damage as a likely contributor to this marked energy dependence. So far, publications have focused solely on neutron RBE for inducing clusters of DNA damage containing two or more DNA double strand breaks (DSBs). In this study, we have conducted a novel assessment of neutron RBE for inducing all types of clustered DNA damage that contain two or more lesions, stratified by whether the clusters contain DSBs (complex DSB clusters) or not (non-DSB clusters). This assessment was conducted for eighteen initial neutron energies between 1 eV and 10 MeV as well as a reference radiation of 250 keV x-rays. We also examined the energy dependence of cluster length and cluster complexity because these factors are believed to impact the DNA repair process. To carry out our investigation, we developed a user-friendly TOPAS-nBio application that includes a custom nuclear DNA model and a novel algorithm for recording clustered DNA damage. We found that neutron RBE for inducing complex DSB clusters exhibited similar energy dependence to the canonical neutron RBE for stochastic radiobiological effects, at multiple depths in human tissue. Qualitatively similar results were obtained for non-DSB clusters, although the quantitative agreement was lower. Additionally we identified a significant neutron energy dependence in the average length and complexity of clustered lesions. These results support the idea that many types of clustered DNA damage contribute to the energy dependence of neutron RBE for stochastic radiobiological effects and imply that the size and constituent lesions of individual clusters should be taken into account when modeling DNA repair. Our results were qualitatively consistent for (i) multiple radiation doses (including a low-dose 0.1 Gy irradiation), (ii) variations in the maximal lesion separation distance used to define a cluster, and (iii) two distinct collections of physics models used to govern particle transport. Our complete TOPAS-nBio application has been released under an open-source license to enable others to independently validate our work and to expand upon it.

Calculation and benchmark of fluence-to-local skin equivalent dose coefficients for neutrons with FLUKA, MCNP, and GEANT4 Monte-Carlo codes

Dose equivalent limits for single organs are recommended by the ICRP (International Commission for the Radiological Protection publication 103). These limits do not lend themselves to be measured. They are assessed by convoluting conversion factors with particle fluences. The Fluence-to-Dose conversion factors are tabulated in the ICRP literature. They allow assessing the organ dose of interest using numerical simulations. In particular, the literature lacks the knowledge of local skin equivalent dose (LSD) coefficients for neutrons. In this article, we compute such values for neutron energies ranging from 1 meV to 15 MeV. We use FLUKA, MCNP and GEANT4 Radiation transport Monte-Carlo simulation codes to perform the calculations. A comparison between these three codes is performed. These calculated values are important for radiation protection studies and radiotherapy applications.

The relation between microdosimetry and induction of direct damage to DNA by alpha particles

In radiopharmaceutical treatmentsα-particles are employed to treat tumor cells. However, the mechanism that drives the biological effect induced is not well known. Being ionizing radiation,α-particles can affect biological organisms by producing damage to the DNA, either directly or indirectly. Following the principle that microdosimetry theory accounts for the stochastic way in which radiation deposits energy in sub-cellular sized volumes via physical collisions, we postulate that microdosimetry represents a reasonable framework to characterize the statistical nature of direct damage induction byα-particles to DNA. We used the TOPAS-nBio Monte Carlo package to simulate direct damage produced by monoenergetic alpha particles to different DNA structures. In separate simulations, we obtained the frequency-mean lineal energy (yF) and dose-mean lineal energy (yD) of microdosimetric distributions sampled with spherical sites of different sizes. The total number of DNA strand breaks, double strand breaks (DSBs) and complex strand breaks per track were quantified and presented as a function of eitheryForyD.The probability of interaction between a track and the DNA depends on how the base pairs are compacted. To characterize this variability on compactness, spherical sites of different size were used to match these probabilities of interaction, correlating the size-dependent specific energy (z) with the damage induced. The total number of DNA strand breaks per track was found to linearly correlate withyFandzFwhen using what we defined an effective volume as microdosimetric site, while the yield of DSB per unit dose linearly correlated withyDorzD,being larger for compacted than for unfolded DNA structures. The yield of complex breaks per unit dose exhibited a quadratic behavior with respect toyDand a greater difference among DNA compactness levels. Microdosimetric quantities correlate with the direct damage imparted on DNA.

Medical application of particle and heavy ion transport code system PHITS

The Particle and Heavy Ion Transport code System (PHITS) is a general-purpose Monte Carlo simulation code that has been applied in various areas of medical physics. These include application in different types of radiotherapy, shielding calculations, application to radiation biology, and research and development of medical tools. In this article, the useful features of PHITS are explained by referring to actual examples of various medical applications.

Molecular Mechanisms of Specific Cellular DNA Damage Response and Repair Induced by the Mixed Radiation Field During Boron Neutron Capture Therapy

The impact of a mixed neutron-gamma beam on the activation of DNA damage response (DDR) proteins and non-coding RNAs (ncRNAs) is poorly understood. Ionizing radiation is characterized by its biological effectiveness and is related to linear energy transfer (LET). Neutron-gamma mixed beam used in boron neutron capture therapy (BNCT) can induce another type of DNA damage such as clustered DNA or multiple damaged sites, as indicated for high LET particles, such as alpha particles, carbon ions, and protons. We speculate that after exposure to a mixed radiation field, the repair capacity might reduce, leading to unrepaired complex DNA damage for a long period and may promote genome instability and cell death. This review will focus on the poorly studied impact of neutron-gamma mixed beams with an emphasis on DNA damage and molecular mechanisms of repair. In case of BNCT, it is not clear which repair pathway is involved, and recent experimental work will be presented. Further understanding of BNCT-induced DDR mechanisms may lead to improved therapeutic efficiency against different tumors.

Fast neutron energy based modelling of biological effectiveness with implications for proton and ion beams

A practical neutron energy dependent RBE model has been developed, based on the relationship between a mono-energetic neutron energy and its likely recoil proton energy. Essentially, the linear energy transfer (LET) values of the most appropriate recoil proton energies are then used to modify the linear quadratic model radiosensitivities (α and β) from their reference LET radiation values to provide the RBE estimates. Experimental neutron studies published by Hall (including some mono-energetic beams ranging from 0.2 to 15 MeV), Broerse, Berry, and data from the Clatterbridge and Detroit clinical neutron beams, which all contain some data from a spectrum of neutron energies, are used to derive single effective neutron energies (NE_eff) for each spectral beam. These energies yield a recoil proton spectrum, but with an effective mean proton energy (being around 50% of NE_eff). The fractional increase in LET is given by the recoil proton LET divided by the proton (LET_U) value which provides the highest RBE. This ratio is then used to determine the change in the linear-quadratic model α and β parameters, from those of the reference radiation, to estimate the RBE. The predicted proton recoil RBE is then reasonably close to the experimental neutron RBE values found when taking into account the variation inherent in biological experiments. The work has some important consequences. The data of Hall et al (1975 Radiat. Res. 64 245-55) shows that the highest RBE values are found with neutron energies around 0.3-0.4 MeV, but this energy cannot possibly generate recoil proton energies which are higher, as necessary for a 0.68 MeV proton with a 30.5 keV μm^-1 LET_U (the LET value which provides the maximum obtainable RBE for a specified ion). For 0.4 MeV neutrons with proton recoil energies of around 0.2 MeV, the latter have a LET of around 62.88 keV μm^-1. This could have an impact on proton beam RBE modelling. However, this is compensated by finding that the maximum radiosensitivity for mono-energetic neutrons was around 1.7 times larger than previously suggested from experimental ion beam studies, probably due to the necessary spreading out of Bragg peaks for ion beam experimental purposes, sampling errors and particle range considerations. This semi-empirical model can be used with minimal computer support and could have applications in ionic beams and in radioprotection.

Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D

Understanding and designing clinical radiation therapy is one of the most important areas of state-of-the-art oncological treatment regimens. Decades of research have gone into developing sophisticated treatment devices and optimization protocols for schedules and dosages. In this paper, we presented a comprehensive computational platform that facilitates building of the sophisticated multi-cell-based model of how radiation affects the biology of living tissue. We designed and implemented a coupled simulation method, including a radiation transport model, and a cell biology model, to simulate the tumor response after irradiation. The radiation transport simulation was implemented through Geant4 which is an open-source Monte Carlo simulation platform that provides many flexibilities for users, as well as low energy DNA damage simulation physics, Geant4-DNA. The cell biology simulation was implemented using CompuCell3D (CC3D) which is a cell biology simulation platform. In order to couple Geant4 solver with CC3D, we developed a 'bridging' module, RADCELL, that extracts tumor cellular geometry of the CC3D simulation (including specification of the individual cells) and ported it to the Geant4 for radiation transport simulation. The cell dose and cell DNA damage distribution in multicellular system were obtained using Geant4. The tumor response was simulated using cell-based tissue models based on CC3D, and the cell dose and cell DNA damage information were fed back through RADCELL to CC3D for updating the cell properties. By merging two powerful and widely used modeling platforms, CC3D and Geant4, we delivered a novel tool that can give us the ability to simulate the dynamics of biological tissue in the presence of ionizing radiation, which provides a framework for quantifying the biological consequences of radiation therapy. In this introductory methods paper, we described our modeling platform in detail and showed how it can be applied to study the application of radiotherapy to a vascularized tumor.

Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies

Track structure based simulations valuably complement experimental research on biological effects of ionizing radiation. They provide information at the highest level of detail on initial DNA damage induced by diverse types of radiation. Simulations with the biophysical Monte Carlo code PARTRAC have been used for testing working hypotheses on radiation action mechanisms, for benchmarking other damage codes and as input for modelling subsequent biological processes. To facilitate such applications and in particular to enable extending the simulations to mixed radiation field conditions, we present analytical formulas that capture PARTRAC simulation results on DNA single- and double-strand breaks and their clusters induced in cells irradiated by ions ranging from hydrogen to neon at energies from 0.5 GeV/u down to their stopping. These functions offer a means by which radiation transport codes at the macroscopic scale could easily be extended to predict biological effects, exploiting a large database of results from micro-/nanoscale simulations, without having to deal with the coupling of spatial scales and running full track-structure calculations.

A microdosimetric analysis of the interactions of mono-energetic neutrons with human tissue

Nuclear reactions induced during high-energy radiotherapy produce secondary neutrons that, due to their carcinogenic potential, constitute an important risk for the development of iatrogenic cancer. Experimental and epidemiological findings indicate a marked energy dependence of neutron relative biological effectiveness (RBE) for carcinogenesis, but little is reported on its physical basis. While the exact mechanism of radiation carcinogenesis is yet to be fully elucidated, numerical microdosimetry can be used to predict the biological consequences of a given irradiation based on its microscopic pattern of energy depositions. Building on recent studies, this work investigated the physics underlying neutron RBE by using the microdosimetric quantity dose-mean lineal energy (y‾_D) as a proxy. A simulation pipeline was constructed to explicitly calculate the y‾_D of radiation fields that consisted of (i) the open source Monte Carlo toolkit Geant4, (ii) its radiobiological extension Geant4-DNA, and (iii) a weighted track-sampling algorithm. This approach was used to study mono-energetic neutrons with initial kinetic energies between 1 eV and 10 MeV at multiple depths in a tissue-equivalent phantom. Spherical sampling volumes with diameters between 2 nm and 1 μm were considered. To obtain a measure of RBE, the neutron y‾_D values were divided by those of 250 keV X-rays that were calculated in the same way. Qualitative agreement was found with published radiation protection factors and simulation data, allowing for the dependencies of neutron RBE on depth and energy to be discussed in the context of the neutron interaction cross sections and secondary particle distributions in human tissue.

Neutron dose and its measurement in proton therapy-current State of Knowledge

Proton therapy has shown dosimetric advantages over conventional radiation therapy using photons. Although the integral dose for patients treated with proton therapy is low, concerns were raised about late effects like secondary cancer caused by dose depositions far away from the treated area. This is especially true for neutrons and therefore the stray dose contribution from neutrons in proton therapy is still being investigated. The higher biological effectiveness of neutrons compared to photons is the main cause of these concerns. The gold-standard in neutron dosimetry is measurements, but performing neutron measurements is challenging. Different approaches have been taken to overcome these difficulties, for instance with newly developed neutron detectors. Monte Carlo simulations is another common technique to assess the dose from secondary neutrons. Measurements and simulations are used to develop analytical models for fast neutron dose estimations. This article tries to summarize the developments in the different aspects of neutron dose in proton therapy since 2017. In general, low neutron doses have been reported, especially in active proton therapy. Although the published biological effectiveness of neutrons relative to photons regarding cancer induction is higher, it is unlikely that the neutron dose has a large impact on the second cancer risk of proton therapy patients.

Computational approach to determine the relative biological effectiveness of fast neutrons using the Geant4-DNA toolkit and a DNA atomic model from the Protein Data Bank

This study proposes an innovative approach to estimate relative biological effectiveness (RBE) of fast neutrons using the Geant4 toolkit. The Geant4-DNA version cannot track heavy ions below 0.5 MeV/nucleon. In order to explore the impact of this issue, secondary particles are simulated instead of the primary low-energy neutrons. The Evaluated Nuclear Data File library is used to determine the cross sections for the elastic and inelastic interactions of neutrons with water and to find the contribution of each secondary particle spectrum. Two strategies are investigated in order to find the best possible approach and results. The first one takes into account only light particles, protons produced from elastic scattering, and α particles from inelastic scattering. Geantino particles are shot instead of heavy ions; hence all heavy ions are considered in the simulations, though their physical effects on DNA not. The second strategy takes into account all the heavy and light ions, although heavy ions cannot be tracked down to very low energies (E<0.5 MeV/nucleon). Our model is based on the combination of an atomic resolution DNA geometrical model and a Monte Carlo simulation toolkit for tracking particles. The atomic coordinates of the DNA double helix are extracted from the Protein Data Bank. Since secondary particle spectra are used instead of simulating the interaction of neutrons explicitly, this method reduces the computation times dramatically. Double-strand break induction is used as the end point for the estimation of the RBE of fast neutrons. ^{60}Co γ rays are used as the reference radiation quality. Both strategies succeed in reproducing the behavior of the RBE_{max} as a function of the incident neutron energy ranging from 0.1 to 14 MeV, including the position of its peak. A comparison of the behavior of the two strategies shows that for neutrons with energies less than 0.7 MeV, the effect of heavy ions would not be very significant, but above 0.7 MeV, heavy ions have an important role in neutron RBE.

The Impact of Dose Rate on DNA Double-Strand Break Formation and Repair in Human Lymphocytes Exposed to Fast Neutron Irradiation

The lack of information on how biological systems respond to low-dose and low dose-rate exposures makes it difficult to accurately assess the carcinogenic risks. This is of critical importance to space radiation, which remains a serious concern for long-term manned space exploration. In this study, the γ-H2AX foci assay was used to follow DNA double-strand break (DSB) induction and repair following exposure to neutron irradiation, which is produced as secondary radiation in the space environment. Human lymphocytes were exposed to high dose-rate (HDR: 0.400 Gy/min) and low dose-rate (LDR: 0.015 Gy/min) p(66)/Be(40) neutrons. DNA DSB induction was investigated 30 min post exposure to neutron doses ranging from 0.125 to 2 Gy. Repair kinetics was studied at different time points after a 1 Gy neutron dose. Our results indicated that γ-H2AX foci formation was 40% higher at HDR exposure compared to LDR exposure. The maximum γ-H2AX foci levels decreased gradually to 1.65 ± 0.64 foci/cell (LDR) and 1.29 ± 0.45 (HDR) at 24 h postirradiation, remaining significantly higher than background levels. This illustrates a significant effect of dose rate on neutron-induced DNA damage. While no significant difference was observed in residual DNA damage after 24 h, the DSB repair half-life of LDR exposure was slower than that of HDR exposure. The results give a first indication that the dose rate should be taken into account for cancer risk estimations related to neutrons.

DNA Condensation with a Boron-Containing Cationic Peptide for Modeling Boron Neutron Capture Therapy

The amino acid derivative 4-borono-L-phenylalanine (BPA) has been used in the radiation medicine technique boron neutron capture therapy (BNCT). Here we have characterized its interaction with DNA when incorporated into a positively charged hexa-L-arginine peptide. This ligand binds strongly to DNA and induces its condensation, an effect which is attenuated at higher ionic strengths. The use of an additional tetra-L-arginine ligand enables the preparation of a DNA condensate in the presence of a negligible concentration of unbound boron. Under these conditions, Monte Carlo simulation indicates that >85% of energy deposition events resulting from thermal neutron irradiation derive from boron fission. The combination of experimental model systems and simulations that we describe here provides a valuable tool for accurate track structure modeling of the DNA damage produced by the high LET particles involved in BNCT.

Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures

The consideration of how a given technique affects results of experimental measurements is a must to achieve correct data interpretation. This might be challenging when it comes to measurements on biological systems, where it is unrealistic to have full control (e.g. through a software replica) of all steps in the measurement chain. In this work we address how the effectiveness of different radiation qualities in inducing biological damage can be assessed measuring DNA damage foci yields, only provided that artefacts related to the scoring technique are adequately considered. To this aim, we developed a unified stochastic modelling approach that, starting from radiation tracks, predicts both the induction, spatial distribution and complexity of DNA damage, and the experimental readout of foci when immunocytochemistry coupled to 2D fluorescence microscopy is used. The approach is used to interpret γ-H2AX data for photon and neutron exposures. When foci are reconstructed in the whole cell nucleus, we obtain information on damage characteristics "behind" experimental observations, as the average damage content of a focus. We reproduce how the detection technique affects experimental findings, e.g. contributing to the saturation of foci yields scored at 30 minutes after exposure with increasing dose and to the lack of dose dependence for yields at 24 hours.

WHAT ROLES FOR TRACK-STRUCTURE AND MICRODOSIMETRY IN THE ERA OF -omics AND SYSTEMS BIOLOGY?

Ionizing radiation is a peculiar perturbation when it comes to damage to biological systems: it proceeds through discrete energy depositions, over a short temporal scale and a spatial scale critical for subcellular targets as DNA, whose damage complexity determines the outcome of the exposure. This lies at the basis of the success of track structure (and nanodosimetry) and microdosimetry in radiation biology. However, such reductionist approaches cannot account for the complex network of interactions regulating the overall response of the system to radiation, particularly when effects are manifest at the supracellular level and involve long times. Systems radiation biology is increasingly gaining ground, but the gap between reductionist and holistic approaches is becoming larger. This paper presents considerations on what roles track structure and microdosimetry can have in the attempt to fill this gap, and on how they can be further exploited to interpret radiobiological data and inform systemic approaches.

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.

A novel vertebrate system for the examination and direct comparison of the relative biological effectiveness for different radiation qualities and sources

PURPOSE

The recent rapid increase of hadron therapy applications requires the development of high performance, reliable in vivo models for preclinical research on the biological effects of high linear energy transfer (LET) particle radiation.

AIM

The aim of this paper was to test the relative biological effectiveness (RBE) of the zebrafish embryo system at two neutron facilities.

MATERIAL AND METHODS

Series of viable zebrafish embryos at 24-hour post-fertilization (hpf) were exposed to single fraction, whole-body, photon and neutron (reactor fission neutrons (<En = 1 MeV>) and (p (18 MeV)+Be, <En> = 3.5 MeV) fast neutron) irradiation. The survival and morphologic abnormalities of each embryo were assessed at 24-hour intervals from the point of fertilization up to 192 hpf and then compared to conventional 6 MV photon beam irradiation results.

RESULTS

The higher energy of the fast neutron beams represents lower RBE (ref. source LINAC 6 MV photon). The lethality rate in the zebrafish embryo model was 10 times higher for 1 MeV fission neutrons and 2.5 times greater for p (18 MeV)+Be cyclotron generated fast neutron beam when compared to photon irradiation results. Dose-dependent organ perturbations (shortening of the body length, spine curvature, microcephaly, micro-ophthalmia, pericardial edema and inhibition of yolk sac resorption) and microscopic (marked cellular changes in eyes, brain, liver, muscle and the gastrointestinal system) changes scale together with the dose response.

CONCLUSION

The zebrafish embryo system is a powerful and versatile model for assessing the effect of ionizing radiation with different LET values on viability, organ and tissue development.

AT THE PHYSICS-BIOLOGY INTERFACE: THE NEUTRON AFFAIR

We present predictions of neutron relative biological effectiveness (RBE) for cell irradiations with neutron beams at PTB-Braunschweig. A neutron RBE model is adopted to evaluate initial DNA damage induction given the neutron-induced charged particle field. RBE values are predicted for cell exposures to quasi-monoenergetic beams (0.56 MeV, 1.2 MeV) and to a broad energy distribution neutron field with dose-averaged energy of 5.75 MeV. Results are compared to what obtained with our RBE predictions for neutrons at similar energies, when a 30-cm sphere is irradiated in an isotropic neutron field. RBE values for experimental conditions are higher for the lowest neutron energies, because, as expected, target geometry determines the weight of the low-effectiveness photon component of the neutron dose. These results highlight the importance of characterizing neutron fields in terms of physical interactions, to fully understand neutron-induced biological effects, contributing to risk estimation and to the improvement of radiation protection standards.

Track to the future: historical perspective on the importance of radiation track structure and DNA as a radiobiological target

PURPOSE

Understanding the mechanisms behind induced biological response following exposure to ionizing radiation is not only important in assessing the risk associated with human exposure, but potentially can help identify ways of improving the efficacy of radiotherapy. Over the decades, there has been much discussion on what is the key biological target for radiation action and its associated size. It was already known in the 1930s that microscopic features of radiation significantly influenced biological outcomes. This resulted in the development of classic target theory, leading to field of microdosimetry and subsequently nanodosimetry, studying the inhomogeneity and stochastics of interactions, along with the identification of DNA as a key target.

CONCLUSIONS

Ultimately, the biological response has been found to be dependent on the radiation track structure (spatial and temporal distribution of ionization and excitation events). Clustering of energy deposition on the nanometer scale has been shown to play a critical role in determining biological response, producing not just simple isolated DNA lesions but also complex clustered lesions that are more difficult to repair. The frequency and complexity of these clustered damage sites are typically found to increase with increasing LET. However in order to fully understand the consequences, it is important to look at the relative distribution of these lesions over larger dimensions along the radiation track, up to the micrometer scale. Correlation of energy deposition events and resulting sites of DNA damage can ultimately result in complex gene mutations and complex chromosome rearrangements following repair, with the frequency and spectrum of the resulting rearrangements critically dependent on the spatial and temporal distribution of these sites and therefore the radiation track. Due to limitations in the techniques used to identify these rearrangements it is likely that the full complexity of the genetic rearrangements that occur has yet to be revealed. This paper discusses these issues from a historical perspective, with many of these historical studies still having relevance today. These can not only cast light on current studies but guide future studies, especially with the increasing range of biological techniques available. So, let us build on past knowledge to effectively explore the future.

In Silico Non-Homologous End Joining Following Ion Induced DNA Double Strand Breaks Predicts That Repair Fidelity Depends on Break Density

This work uses Monte Carlo simulations to investigate the dependence of residual and misrepaired double strand breaks (DSBs) at 24 hours on the initial damage pattern created during ion therapy. We present results from a nanometric DNA damage simulation coupled to a mechanistic model of Non-Homologous End Joining, capable of predicting the position, complexity, and repair of DSBs. The initial damage pattern is scored by calculating the average number of DSBs within 70 nm from every DSB. We show that this local DSB density, referred to as the cluster density, can linearly predict misrepair regardless of ion species. The models predict that the fraction of residual DSBs is constant, with 7.3% of DSBs left unrepaired following 24 hours of repair. Through simulation over a range of doses and linear energy transfer (LET) we derive simple correlations capable of predicting residual and misrepaired DSBs. These equations are applicable to ion therapy treatment planning where both dose and LET are scored. This is demonstrated by applying the correlations to an example of a clinical proton spread out Bragg peak. Here we see a considerable biological effect past the distal edge, dominated by residual DSBs.

Monte Carlo studies on neutron interactions in radiobiological experiments

Monte Carlo method was used to study the characteristics of neutron interactions with cells underneath a water medium layer with varying thickness. The following results were obtained. (1) The fractions of neutron interaction with ¹H, ¹²C, ¹⁴N and ¹⁶O nuclei in the cell layer were studied. The fraction with ¹H increased with increasing medium thickness, while decreased for ¹²C, ¹⁴N and ¹⁶O nuclei. The bulges in the interaction fractions with ¹²C, ¹⁴N and ¹⁶O nuclei were explained by the resonance spikes in the interaction cross-section data. The interaction fraction decreased in the order: ¹H > ¹⁶O > ¹²C > ¹⁴N. (2) In general, as the medium thickness increased, the number of “interacting neutrons” which exited the medium and then further interacted with the cell layer increased. (3) The area under the angular distributions for “interacting neutrons” decreased with increasing incident neutron energy. Such results would be useful for deciphering the reasons behind discrepancies among existing results in the literature.

Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping

Track structures and resulting DNA damage in human cells have been simulated for hydrogen, helium, carbon, nitrogen, oxygen and neon ions with 0.25–256 MeV/u energy. The needed ion interaction cross sections have been scaled from those of hydrogen; Barkas scaling formula has been refined, extending its applicability down to about 10 keV/u, and validated against established stopping power data. Linear energy transfer (LET) has been scored from energy deposits in a cell nucleus; for very low-energy ions, it has been defined locally within thin slabs. The simulations show that protons and helium ions induce more DNA damage than heavier ions do at the same LET. With increasing LET, less DNA strand breaks are formed per unit dose, but due to their clustering the yields of double-strand breaks (DSB) increase, up to saturation around 300 keV/μm. Also individual DSB tend to cluster; DSB clusters peak around 500 keV/μm, while DSB multiplicities per cluster steadily increase with LET. Remarkably similar to patterns known from cell survival studies, LET-dependencies with pronounced maxima around 100–200 keV/μm occur on nanometre scale for sites that contain one or more DSB, and on micrometre scale for megabasepair-sized DNA fragments.