Track Structure Simulations Research Articles

Double differential cross sections for proton induced electron emission from molecular analogues of DNA constituents for energies in the Bragg peak region.

For track structure simulations in the Bragg peak region, measured electron emission cross sections of DNA constituents are required as input for developing parameterized model functions representing the scattering probabilities. In the present work, double differential cross sections were measured for the electron emission from vapor-phase pyrimidine, tetrahydrofuran, and trimethyl phosphate that are structural analogues to the base, the sugar, and the phosphate residue of the DNA, respectively. The range of proton energies was from 75 keV to 135 keV, the angles ranged from 15° to 135°, and the electron energies were measured from 10 eV to 200 eV. Single differential and total electron emission cross sections are derived by integration over angle and electron energy and compared to the semi-empirical Hansen-Kocbach-Stolterfoht (HKS) model and a quantum mechanical calculation employing the first Born approximation with corrected boundary conditions (CB1). The CB1 provides the best prediction of double and single differential cross section, while total cross sections can be fitted with semi-empirical models. The cross sections of the three samples are proportional to their total number of valence electrons.

A New Simulation of Track Structure of Low-Energy Electrons in Liquid Water: Considering the Condensed-Phase Effect on Electron Elastic Scattering

A new Monte Carlo simulation of the track structure of low-energy electrons (<10 keV) in liquid water is presented. The feature of the simulation is taken into consideration of the condensed-phase effect of liquid water on electron elastic scattering with the use of the Champion model, while the dielectric response formalism incorporating the optical-data model developed by Emfietzoglou et al. is applied for calculating the electron inelastic scattering. The spatial distributions of energy deposition and inelastic scattering events of low-energy electrons with different primary energies in liquid water are calculated and compared with other theoretical evaluations. The present work shows that the condensed-phase effect of liquid water on electron elastic scattering may be of the influence on the fraction of absorbed energy and distribution of inelastic scattering events at lower primary energies, which also indicate potential effects on the DNA damage induced by low-energy electrons.

Perspectives in radiation biophysics: From radiation track structure simulation to mechanistic models of DNA damage and repair

In radiation targeted therapy and genetic risk estimation of low dose radiation protection there is a crucial need for full description of DNA damage response and repair (DDR) leading to cell death and cell mutation. We propose such a description can be arrived through realistic track-structure simulations together with mechanistic mathematical formulation of DDR and the availability of experimental data for testing the proof of principle. In this paper we review briefly first the state of the art in DNA damage and repair, and then the recent advances in the physics of track structure which represents an essential tool in radiation biophysics.

WE‐DE‐202‐02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation‐type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue.Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub‐cellular level to dose‐response effects on larger scales.In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub‐cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose‐response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scalesJ. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC‐IOF‐623630)

SU‐F‐T‐127: Charged Particle Transport in Condensed Media

Purpose:Provide quality interaction cross sections for charged particle Monte Carlo (MC) track structure codes and evaluate low energy electron transport in condensed media.Methods:MC methods and codes are often used to model or simulate charged particle radiation transport in matter. Detailed (or event‐by‐event) track structure simulations are of special interest for the modeling of the physical and chemical stages of radiation action with matter and the initial radiation damage to biological systems. They require reliable interaction cross sections of all radiation qualities considered (e.g., electrons, protons, alpha particles, light and heavy ions) with the target material under consideration, mainly in the condensed phase, including liquids and solids. Interaction cross sections are calculated using the dielectric formalism, a mixture of first principles, theoretical modeling and experimental information for bulk and surface transport and implemented into MC track structure codes. Secondary electron emission yields from amorphous solid water (ASW) and thin metal foils (copper and gold) after fast proton impact are simulated and measured experimentally.Results:After considering different transport models for bulk and surface transport and a careful modeling of the experimental geometry, simulated secondary electron emission yields follow the trends of experimental data well. Furthermore, yields for electron emissions below 50 eV are sensitive to differential elastic scattering cross sections.Conclusion:Low‐energy electron transport in condensed media is still a challenge for detailed track structure simulation codes. Interaction cross‐sections, transport models, and target geometry need to be considered adequately.The research was funded in part by NSF Major Research Instrumentation Program 2009, Award Number: 0923270 and by NIH/NCI R01 CA93351.

WE‐DE‐202‐01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation‐type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue.Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub‐cellular level to dose‐response effects on larger scales.In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub‐cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose‐response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scalesJ. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC‐IOF‐623630)

WE‐DE‐202‐03: Modeling of Biological Processes ‐ What Happens After Early Molecular Damage?

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation‐type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue.Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub‐cellular level to dose‐response effects on larger scales.In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub‐cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose‐response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scalesJ. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC‐IOF‐623630)

WE‐H‐BRA‐04: Biological Geometries for the Monte Carlo Simulation Toolkit TOPASNBio

Purpose:New advances in radiation therapy are most likely to come from the complex interface of physics, chemistry and biology. Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can thus help bridge the gap between physics and biology. The aim of TOPAS‐nBio is to provide a comprehensive tool to generate advanced radiobiology simulations.Methods:TOPAS wraps and extends the Geant4 Monte Carlo (MC) simulation toolkit. TOPAS‐nBio is an extension to TOPAS which utilizes the physics processes in Geant4‐DNA to model biological damage from very low energy secondary electrons. Specialized cell, organelle and molecular geometries were designed for the toolkit.Results:TOPAS‐nBio gives the user the capability of simulating biological geometries, ranging from the micron‐scale (e.g. cells and organelles) to complex nano‐scale geometries (e.g. DNA and proteins). The user interacts with TOPAS‐nBio through easy‐to‐use input parameter files. For example, in a simple cell simulation the user can specify the cell type and size as well as the type, number and size of included organelles. For more detailed nuclear simulations, the user can specify chromosome territories containing chromatin fiber loops, the later comprised of nucleosomes on a double helix. The chromatin fibers can be arranged in simple rigid geometries or within factual globules, mimicking realistic chromosome territories. TOPAS‐nBio also provides users with the capability of reading protein data bank 3D structural files to simulate radiation damage to proteins or nucleic acids e.g. histones or RNA. TOPAS‐nBio has been validated by comparing results to other track structure simulation software and published experimental measurements.Conclusion:TOPAS‐nBio provides users with a comprehensive MC simulation tool for radiobiological simulations, giving users without advanced programming skills the ability to design and run complex simulations.

WE‐DE‐202‐00: Connecting Radiation Physics with Computational Biology

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation‐type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue.Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub‐cellular level to dose‐response effects on larger scales.In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub‐cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose‐response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scalesJ. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC‐IOF‐623630)

The impact of new Geant4-DNA cross section models on electron track structure simulations in liquid water

The most recent release of the open source and general purpose Geant4 Monte Carlo simulation toolkit (Geant4 10.2 release) contains a new set of physics models in the Geant4-DNA extension for improving the modelling of low-energy electron transport in liquid water (&amp;lt;10 keV). This includes updated electron cross sections for excitation, ionization, and elastic scattering. In the present work, the impact of these developments to track-structure calculations is examined for providing the first comprehensive comparison against the default physics models of Geant4-DNA. Significant differences with the default models are found for the average path length and penetration distance, as well as for dose-point-kernels for electron energies below a few hundred eV. On the other hand, self-irradiation absorbed fractions for tissue-like volumes and low-energy electron sources (including some Auger emitters) reveal rather small differences (up to 15%) between these new and default Geant4-DNA models. The above findings indicate that the impact of the new developments will mainly affect those applications where the spatial pattern of interactions and energy deposition of very-low energy electrons play an important role such as, for example, the modelling of the chemical and biophysical stage of radiation damage to cells.

Influence of the geometrical detail in the description of DNA and the scoring method of ionization clustering on nanodosimetric parameters of track structure: a Monte Carlo study using Geant4-DNA

The aim of this study was to evaluate the influence of the geometrical detail of the DNA on nanodosimetric parameters of track structure induced by protons and alpha particles of different energies (LET values ranging from 1 to ) as calculated by Geant4-DNA Monte Carlo simulations.The first geometry considered consisted of a well-structured placement of a realistic description of the DNA double helix wrapped around cylindrical histones (GeomHist) forming a 18 kbp-long chromatin fiber. In the second geometry considered, the DNA was modeled as a total of 1800 ten bp-long homogeneous cylinders (2.3 nm diameter and 3.4 nm height) placed in random positions and orientations (GeomCyl). As for GeomHist, GeomCyl contained a DNA material equivalent to 18 kbp. Geant4-DNA track structure simulations were performed and ionizations were counted in the scoring volumes. For GeomCyl, clusters were defined as the number of ionizations (ν) scored in each 10 bp-long cylinder. For GeomHist, clusters of ionizations scored in the sugar-phosphate groups of the double-helix were revealed by the DBSCAN clustering algorithm according to a proximity criteria among ionizations separated by less than 10 bp. The topology of the ionization clusters formed using GeomHist and GeomCyl geometries were compared in terms of biologically relevant nanodosimetric quantities.The discontinuous modeling of the DNA for GeomCyl led to smaller cluster sizes than for GeomHist. The continuous modeling of the DNA molecule for GeomHist allowed the merging of ionization points by the DBSCAN algorithm giving rise to larger clusters, which were not detectable within the GeomCyl geometry. Mean cluster size (m1) was found to be of the order of 10% higher for GeomHist compared to GeomCyl for LET . For higher LETs, the difference increased with LET similarly for protons and alpha particles. Both geometries showed the same relationship between m1 and the cumulative relative frequency of clusters with (f3) within statistical variations, independently of particle type.In order to obtain ionization cluster size distributions relevant for biological DNA lesions, the complex DNA geometry and a scoring method without fixed boundaries should be preferred to the simple cylindrical geometry with a fixed scoring volume.

Monte Carlo simulations of the relative biological effectiveness for DNA double strand breaks from 300 MeV u−1 carbon-ion beams

Monte Carlo simulations are used to calculate the relative biological effectiveness (RBE) of 300 MeV u−1 carbon-ion beams at different depths in a cylindrical water phantom of 10 cm radius and 30 cm long. RBE values for the induction of DNA double strand breaks (DSB), a biological endpoint closely related to cell inactivation, are estimated for monoenergetic and energy-modulated carbon ion beams. Individual contributions to the RBE from primary ions and secondary nuclear fragments are simulated separately. These simulations are based on a multi-scale modelling approach by first applying the FLUKA (version 2011.2.17) transport code to estimate the absorbed doses and fluence energy spectra, then using the MCDS (version 3.10A) damage code for DSB yields. The approach is efficient since it separates the non-stochastic dosimetry problem from the stochastic DNA damage problem. The MCDS code predicts the major trends of the DSB yields from detailed track structure simulations. It is found that, as depth is increasing, RBE values increase slowly from the entrance depth to the plateau region and change substantially in the Bragg peak region. RBE values reach their maxima at the distal edge of the Bragg peak. Beyond this edge, contributions to RBE are entirely from nuclear fragments. Maximum RBE values at the distal edges of the Bragg peak and the spread-out Bragg peak are, respectively, 3.0 and 2.8. The present approach has the flexibility to weight RBE contributions from different DSB classes, i.e. DSB0, DSB+ and DSB++.

Double differential ionization cross section of tetrahydrofuran for proton impact

SynopsisDouble differential (in angle and energy) ionization cross sections were experimentally determined for the collisions of protons with a tetrahydrofuran gas target at impact energies between 100 keV and 1910 keV in the angular range between 15° and 165° relative to the beam direction. The derived absolute double differential cross sections will be included in the BioQuaRT [1] multi-scale track structure simulation program.

Cross-section scaling for track structure simulations of low-energy ions in liquid water.

Radiation damage by low-energy ions significantly contributes to the high biological efficiency of ion beams in distal Bragg peak regions as well as to the energy-dependent efficiency of neutron irradiation. To enable assessing biological effects of ions at energies <1 MeV u(-1) with track-structure based models, a Barkas-like scaling procedure is developed that provides ion cross sections in liquid water based on those for hydrogen ions. The resulting stopping power and range for carbon ions agree with the ICRU 73 database and other low-energy stopping power data. The method represents the basis for extending PARTRAC simulations of light ion track structures and biological effects down to the keV u(-1) range.

Microdosimetry of the full slowing down of protons using Monte Carlo track structure simulations.

The article investigates two approaches in microdosimetric calculations based on Monte Carlo track structure (MCTS) simulations of a 160-MeV proton beam. In the first approach, microdosimetric parameters of the proton beam were obtained using the weighted sum of proton energy distributions and microdosimetric parameters of proton track segments (TSMs). In the second approach, phase spaces of energy depositions obtained using MCTS simulations in the full slowing down (FSD) mode were used for the microdosimetric calculations. Targets of interest were water cylinders of 2.3-100 nm in diameters and heights. Frequency-averaged lineal energies ([Formula: see text]) obtained using both approaches agreed within the statistical uncertainties. Discrepancies beyond this level were observed for dose-averaged lineal energies ([Formula: see text]) towards the Bragg peak region due to the small number of proton energies used in the TSM approach and different energy deposition patterns in the TSM and FSD of protons.

Simulations of Radioactive Decays: an Application of Low-Energy Electromagnetic Packages for the Nuclear Medicine

Problems of the radiobiology and the nuclear medicine require clarifying the specifics of radionuclides interactions with unhealthy cells. In this work we aimed to simulate emitting particles tracks of radionuclides and their radioactive decays at DNA level inside the cell nucleus. Accordingly, using the Monte Carlo-based track structure simulation technique, we estimated the radial distribution of deposited energy and kinetic energy spectra of electrons produced by primary particles resulting from radioactive decays of different radionuclides within cell nucleus. To address the possibility of DNA damage, we performed the cluster analysis of track structures of emitted particles inside the volumes corresponding to the size of the native double-stranded DNA. For this purpose, G4-RadioactiveDecay and low-energy electromagnetic packages form Geant4 Monte-Carlo toolkit were combined together. Besides, a comparative analysis was performed for various low-energy electromagnetic packages as G4-DNA and G4-Livermore.

Future development of biologically relevant dosimetry.

Proton and ion beams are radiotherapy modalities of increasing importance and interest. Because of the different biological dose response of these radiations as compared with high-energy photon beams, the current approach of treatment prescription is based on the product of the absorbed dose to water and a biological weighting factor, but this is found to be insufficient for providing a generic method to quantify the biological outcome of radiation. It is therefore suggested to define new dosimetric quantities that allow a transparent separation of the physical processes from the biological ones. Given the complexity of the initiation and occurrence of biological processes on various time and length scales, and given that neither microdosimetry nor nanodosimetry on their own can fully describe the biological effects as a function of the distribution of energy deposition or ionization, a multiscale approach is needed to lay the foundation for the aforementioned new physical quantities relating track structure to relative biological effectiveness in proton and ion beam therapy. This article reviews the state-of-the-art microdosimetry, nanodosimetry, track structure simulations, quantification of reactive species, reference radiobiological data, cross-section data and multiscale models of biological response in the context of realizing the new quantities. It also introduces the European metrology project, Biologically Weighted Quantities in Radiotherapy, which aims to investigate the feasibility of establishing a multiscale model as the basis of the new quantities. A tentative generic expression of how the weighting of physical quantities at different length scales could be carried out is presented.

Developments and trends in bioequivalent dosimetry.

Significant progress in radiobiology has refined the understanding of radiation-induced biological response at the cellular level and challenged the conventional application of a macroscopic description of radiation action to dosimetry in favour of a microscopic approach. Pioneering experiments, which investigated the stochastics of energy deposition from ionising radiations in volumes of cellular dimensions, contributed to the recognition of microdosimetry as a new scientific discipline. The first quantitative applications of Monte Carlo track structure simulations in radiobiology, however, supported evidence for target sizes of particular biological importance being in the nanometre regime. Bioequivalent dosimetry attempts to link particular features of the response of physical detectors with biological endpoints, exploiting clusters of multiple ionisations within nanometre scales in solid-state, gas- and water-filled devices. This approach supports the continued development of new concepts and quantities in radiation protection to permit evaluation of the biological effectiveness of radiations of different quality independently of dose and dose rate.

Nanodosimetric characterization of ion beams

The characterization of particle track structure is essential for an estimation of radiobiological effects, particularly in the case of densely ionizing radiation. The particle track structure can be characterized by nanodosimetric quantities which are measurable by means of a nanodosimeter. Results obtained from experiments with the nanodosimeter can be used to validate track structure simulations, which are essential for estimating track structure parameters in biological material. For this purpose, the dedicated Monte Carlo code PTra has been developed to simulate the nanodosimeter setup as well as nanometric targets consisting of water. Recently, electron-impact cross section data of DNA constituents measured at PTB were implemented into PTra. A calculation of nanodosimetric quantities in DNA-analog media shows considerable differences to results obtained in water medium, particularly for electron energies lower than 200 eV. These discrepancies become more considerable when nanodosimetric quantities are used to estimate biological effects. This paper aims to provide an overview of the present status of nanodosimetry, focusing on the experimental and simulation work at PTB. Furthermore, the suitability of simple models directly linking nanodosimetric track structure characteristics and radiobiological effectiveness is discussed.

SU‐E‐T‐334: Track Structure Simulations of Charged Particles at Low and Intermediate Energies: Cross Sections Needs for Light and Heavy Ions

Purpose/Methods:Monte Carlo (MC) track structure simulations follow the primary as well as all produced secondary particles in an event‐by‐event manner, from starting or ejection energy down to total stopping. They provide useful information on physics and chemistry of the biological response to radiation. They depend on reliable interaction cross sections and transport models of the considered radiation quality with biologically relevant materials. Most transport models focus on sufficiently fast and bare (i.e., fully ionized) ions and cross sections calculated within the (relativistic) first Born or Bethe approximations. These theories consider the projectile as a point particle and rely on proton cross sections and simple charge‐scaling methods; they neglect the atomic nature of the ion and break down at low and intermediate ion energies. Heavier ions are used in particle therapy and slow to intermediate and low energies in the biologically interesting Bragg peak. Lighter and slower fragment ions, including alpha particles, protons, and neutrons are also produced in nuclear and break up reactions of charged particles. Secondary neutrons also produce recoil protons and ions, mainly in the intermediate energy range.Results/Conclusion:This work reviews existing models for track structure simulations and cross section calculations for light and heavy ions focusing on the low and intermediate energy range. It also presents new and updated aspects on cross section calculations and simulation techniques for ions and discusses the need for new models, calculations, and experimental data.