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BackgroundGeant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing.AimsTo respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.Materials and methodsG4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes.ResultsThis paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.DiscussionOur results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics.ConclusionThe results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

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.

A chemistry module has been implemented in Geant4-DNA since Geant4 version 10.1 to simulate the radiolysis of water after irradiation. It has been used in a number of applications, including the calculation of G-values and early DNA damage, allowing the comparison with experimental data. Since the first version, numerous modifications have been made to the module to improve the computational efficiency and extend the simulation to homogeneous kinetics in bulk solution. With these new developments, new applications have been proposed and released as Geant4 examples, showing how to use chemical processes and models. This work reviews the models implemented and application developments for modeling water radiolysis in Geant4-DNA as reported in the ESA BioRad III Project., (© 2024 American Association of Physicists in Medicine.)

Purpose: This study aimed to develop a computational environment for the accurate simulation of human cancer cell irradiation using Geant4-DNA. New cell geometrical models were developed and irradiated by alpha particle beams to induce DNA damage. The proposed approach may help further investigation of the benefits of external alpha irradiation therapy., Methods: The Geant4-DNA Monte Carlo (MC) toolkit allows the simulation of cancer cell geometries that can be combined with accurate modelling of physical, physicochemical and chemical stages of liquid water irradiation, including radiolytic processes. Geant4-DNA is used to calculate direct and non-direct DNA damage yields, such as single and double strand breaks, produced by the deposition of energy or by the interaction of DNA with free radicals., Results: In this study, the "molecularDNA" example application of Geant4-DNA was used to quantify early DNA damage in human cancer cells upon irradiation with alpha particle beams, as a function of linear energy transfer (LET). The MC simulation results are compared to experimental data, as well as previously published simulation data. The simulation results agree well with the experimental data on DSB yields in the lower LET range, while the experimental data on DSB yields are lower than the results obtained with the "molecularDNA" example in the higher LET range., Conclusion: This study explored and demonstrated the possibilities of the Geant4-DNA toolkit together with the "molecularDNA" example to simulate the helium beam irradiation of cancer cell lines, to quantify the early DNA damage, or even the following DNA damage response., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

A Geant4 based simulation platform of the Holland Proton Therapy Centre (HollandPTC, Netherlands) R&D beamline (G4HPTC-R&D) was developed to enable the planning, optimisation and advanced dosimetry for radiobiological studies. It implemented a six parameter non-symmetrical Gaussian pencil beam surrogate model to simulate the R&D beamline in both a pencil beam and passively scattered field configuration. Three different experimental proton datasets (70 MeV, 150 MeV, and 240 MeV) of the pencil beam envelope evolution in free air and depth-dose profiles in water were used to develop a set of individual parameter surrogate functions to enable the modelling of the non-symmetrical Gaussian pencil beam properties with only the ProBeam isochronous cyclotron mean extraction proton energy as input. This refined beam model was then benchmarked with respect to three independent experimental datasets of the R&D beamline operating in both a pencil beam configuration at 120 and 200 MeV, and passively scattered field configuration at 150 MeV. It was shown that the G4HPTC-R&D simulation platform can reproduce the pencil beam envelope evolution in free air and depth-dose profiles to within an accuracy on the order of ±5% for all tested energies, and that it was able to reproduce the 150 MeV passively scattered field to the specifications need for clinical and radiobiological applications., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This work was partially funded by Varian Medical Systems (a Siemens Healthineers Company)., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Glioblastoma is among the most lethal cancers, with no known cure. A multitude of therapeutics are being developed or in clinical trials, but currently there are no ways to predict which patient may benefit the most from which drug. Assays that allow prediction of the tumor's response to anti-cancer drugs may improve clinical decision-making. Here, we present a high-density 3D primary cell culture model for short-term testing from resected glioblastoma tissue that is set up on the day of surgery, established within 7 days and viable for at least 3 weeks. High-density 3D cultures contain tumor and host cells, including microglia, and retain key histopathological characteristics of their parent tumors, including proliferative activity, expression of the marker GFAP, and presence of giant cells. This provides a proof-of-concept that 3D primary cultures may be useful to model tumor heterogeneity. Importantly, we show that high-density 3D cultures can be used to test chemotherapy response within a 2-3-week timeframe and are predictive of patient response to Temozolomide therapy. Thus, primary high-density 3D cultures could be a useful tool for brain cancer research and prediction of therapeutic resistance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Track structure Monte Carlo (MC) codes have achieved successful outcomes in the quantitative investigation of radiation-induced initial DNA damage. The aim of the present study is to extend a Geant4-DNA radiobiological application by incorporating a feature allowing for the prediction of DNA rejoining kinetics and corresponding cell surviving fraction along time after irradiation, for a Chinese hamster V79 cell line, which is one of the most popular and widely investigated cell lines in radiobiology., Methods: We implemented the Two-Lesion Kinetics (TLK) model, originally proposed by Stewart, which allows for simulations to calculate residual DNA damage and surviving fraction along time via the number of initial DNA damage and its complexity as inputs., Results: By optimizing the model parameters of the TLK model in accordance to the experimental data on V79, we were able to predict both DNA rejoining kinetics at low linear energy transfers (LET) and cell surviving fraction., Conclusion: This is the first study to demonstrate the implementation of both the cell surviving fraction and the DNA rejoining kinetics with the estimated initial DNA damage, in a realistic cell geometrical model simulated by full track structure MC simulations at DNA level and for various LET. These simulation and model make the link between mechanistic physical/chemical damage processes and these two specific biological endpoints., (Copyright © 2022 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Background: Treatment of early-stage breast cancer currently includes surgical removal of the tumor and (partial) breast irradiation of the tumor site performed at fractionated dose. Although highly effective, this treatment is exhaustive for both patient and clinic. In this study, the theoretical potential of an alternative treatment combining thermal ablation with low dose rate (LDR) brachytherapy using radioactive magnetic nanoparticles (RMNPs) containing 103-palladium was researched., Methods: The radiation dose characteristics and emission spectra of a single RMNP were calculated, and dose distributions of a commercial brachytherapy seed and an RMNP brachytherapy seed were simulated using Geant4 Monte Carlo toolkit., Results: It was found that the RMNP seeds deliver a therapeutic dose similar to currently used commercial seed, while the dose distribution shows a spherical fall off compared to the more inhomogeneous dose distribution of the commercial seed. Changes in shell thickness only changed the dose profile between 2 × 10 -4 mm and 3 × 10 -4 mm radial distance to the RMNP, not effecting long-range dose., Conclusion: The dose distribution of the RMNP seed is comparable with current commercial brachytherapy seeds, while anisotropy of the dose distribution is reduced. Because this reduces the dependency of the dose distribution on the orientation of the seed, their surgical placement is easier. This supports the feasibility of the clinical application of the proposed novel treatment modality.

In X-ray imaging, photons are transmitted through and absorbed by the target object, but are also scattered in significant quantities. Previous attempts to use scattered X-ray photons for imaging applications used pencil or fan beam illumination. Here we present 3D X-ray Scatter Tomography using full-field illumination for small-animal imaging. Synchrotron imaging experiments were performed on a phantom and the chest of a juvenile rat. Transmitted and scattered photons were simultaneously imaged with separate cameras; a scientific camera directly downstream of the sample stage, and a pixelated detector with a pinhole imaging system placed at 45 ° to the beam axis. We obtained scatter tomogram feature fidelity sufficient for segmentation of the lungs and major airways in the rat. The image contrast in the scatter tomogram slices approached that of transmission imaging, indicating robustness to the amount of multiple scattering present in our case. This opens the possibility of augmenting full-field 2D imaging systems with additional scatter detectors to obtain complementary modes or to improve the fidelity of existing images without additional dose, potentially leading to single-shot or reduced-angle tomography or overall dose reduction for live animal studies.

Over the last decade one of the most significant technological advances made in the field of radiation detectors for nuclear medicine was the development of Silicon Photomultipler (SiPM) sensors. At present only a small number of SiPM based radiation detectors for Single Photon Emission Computed Tomography (SPECT) applications have been explored, and even fewer experimental prototypes developed. An in-silico investigation into the optimal design of a Philips DPC3200 SiPM photosensor-based thin monolithic scintillator detector for SPECT applications was undertaken using the Monte Carlo radiation transport modelling toolkit Geant4 version 10.5. The performance of the 20 different SPECT radiation detector configurations, 4 scintillator materials (NaI(Tl), GAGG(Ce), CsI(Tl) and LaBr 3 (Ce)) and 5 thicknesses (1-5 mm), were determined through the use of seven figures of merit. It was found that a crystal thickness range of 4-5 mm was required for all four materials to ensure acceptable energy resolution, sensitivity and spatial resolution performance with the Philips DPC3200 SiPM. Any thinner than this and the performance of all four materials was found to degrade rapidly due to a high probability of material specific fluorescence x-ray escape after incident gamma/x-ray photoelectric absorption. When factoring in each material's magnetic resonance imaging compatibility, hygroscopy, and cost, it was found that CsI(Tl) represents the most promising material to construct tileable Philips digital SiPM based thin monolithic scintillator detectors for SPECT applications., (Copyright © 2020. Published by Elsevier Ltd.)

The advancement of multidisciplinary research fields dealing with ionising radiation induced biological damage - radiobiology, radiation physics, radiation protection and, in particular, medical physics - requires a clear mechanistic understanding of how cellular damage is induced by ionising radiation. Monte Carlo (MC) simulations provide a promising approach for the mechanistic simulation of radiation transport and radiation chemistry, towards the in silico simulation of early biological damage. We have recently developed a fully integrated MC simulation that calculates early single strand breaks (SSBs) and double strand breaks (DSBs) in a fractal chromatin based human cell nucleus model. The results of this simulation are almost equivalent to past MC simulations when considering direct/indirect strand break fraction, DSB yields and fragment distribution. The simulation results agree with experimental data on DSB yields within 13.6% on average and fragment distributions agree within an average of 34.8%., (Copyright © 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

This Special Report presents a description of Geant4-DNA user applications dedicated to the simulation of track structures (TS) in liquid water and associated physical quantities (e.g., range, stopping power, mean free path…). These example applications are included in the Geant4 Monte Carlo toolkit and are available in open access. Each application is described and comparisons to recent international recommendations are shown (e.g., ICRU, MIRD), when available. The influence of physics models available in Geant4-DNA for the simulation of electron interactions in liquid water is discussed. Thanks to these applications, the authors show that the most recent sets of physics models available in Geant4-DNA (the so-called "option4" and "option 6" sets) enable more accurate simulation of stopping powers, dose point kernels, and W-values in liquid water, than the default set of models ("option 2") initially provided in Geant4-DNA. They also serve as reference applications for Geant4-DNA users interested in TS simulations., (© 2018 American Association of Physicists in Medicine.)

Mechanistic modelling of DNA damage in Monte Carlo simulations is highly sensitive to the parameters that define DNA damage. In this work, we use a simple testing geometry to investigate how different choices of physics models and damage model parameters can change the estimation of DNA damage in a mechanistic DNA damage simulation built in Geant4-DNA. The choice of physics model can lead to variations by up to a factor of two in the yield of physically induced strand breaks, and the parameters that determine scavenging, and physical and chemical single strand break induction can have even larger consequences. Using low energy electrons as primary particles, a variety of parameters are tested in this geometry in order to arrive at a parameter set consistent with past simulation studies. We find that the modelling of scavenging can play an important role in determining results, and speculate that high-scavenging regimes, where only chemical radicals within 1 nm of DNA are simulated, could provide a good means of testing mechanistic DNA simulations., (Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

We extended a generic Geant4 application for mechanistic DNA damage simulations to an Escherichia coli cell geometry, finding electron damage yields and proton damage yields largely in line with experimental results. Depending on the simulation of radical scavenging, electrons double strand breaks (DSBs) yields range from 0.004 to 0.010 DSB Gy -1  Mbp -1 , while protons have yields ranging from 0.004 DSB Gy -1  Mbp -1 at low LETs and with strict assumptions concerning scavenging, up to 0.020 DSB Gy -1  Mbp -1 at high LETs and when scavenging is weakest. Mechanistic DNA damage simulations can provide important limits on the extent to which physical processes can impact biology in low background experiments. We demonstrate the utility of these studies for low dose radiation biology calculating that in E. coli, the median rate at which the radiation background induces double strand breaks is 2.8 × 10 -8  DSB day -1 , significantly less than the mutation rate per generation measured in E. coli, which is on the order of 10 -3 ., (Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Absolute measurements of the radiolytic yield of Fe3+ in a ferrous sulphate dosimeter formulation (6 mM Fe2+), with a 20 keV x-ray monoenergetic beam, are reported. Dose-rate suppression of the radiolytic yield was observed at dose rates lower than and different in nature to those previously reported with x-rays. We present evidence that this effect is most likely to be due to recombination of free radicals radiolytically produced from water. The method used to make these measurements is also new and it provides radiolytic yields which are directly traceable to the SI standards system. The data presented provides new and exacting tests of radiation chemistry codes.

A novel treatment planning framework, the Relative Biological Effective Dose (RBED), for high Z nanoparticle (NP)-enhanced photon radiotherapy is developed and tested in silico for the medical exemplar of neoadjuvant (preoperative) breast cancer MV photon radiotherapy. Two different treatment scenarios, conventional and high Z NP enhanced, were explored with a custom Geant4 application that was developed to emulate the administration of a single 2 Gy fraction as part of a 50 Gy radiotherapy treatment plan. It was illustrated that there was less than a 1% difference in the dose deposition throughout the standard and high Z NP-doped adult female phantom. Application of the RBED framework found that the extent of possible biological response with high Z NP doping was great than expected via the dose deposition alone. It is anticipated that this framework will assist the scientific community in future high Z NP-enhanced in-silico, pre-clinical and clinical trials.

A local effect model (LEM)-based framework capable of interpolating nanoparticle-enhanced photon-irradiated clonogenic cell survival fraction measurements as a function of nanoparticle concentration was developed and experimentally benchmarked for gold nanoparticle (AuNP)-doped bovine aortic endothelial cells (BAECs) under superficial kilovoltage X-ray irradiation. For three different superficial kilovoltage X-ray spectra, the BAEC survival fraction response was predicted for two different AuNP concentrations and compared to experimental data. The ability of the developed framework to predict the cell survival fraction trends is analysed and discussed. This developed framework is intended to fill in the existing gaps of individual cell line response as a function of NP concentration under photon irradiation and assist the scientific community in planning future pre-clinical trials of high Z nanoparticle-enhanced photon radiotherapy.

Understanding the fundamental mechanisms involved in the induction of biological damage by ionizing radiation remains a major challenge of today's radiobiology research. The Monte Carlo simulation of physical, physicochemical and chemical processes involved may provide a powerful tool for the simulation of early damage induction. The Geant4-DNA extension of the general purpose Monte Carlo Geant4 simulation toolkit aims to provide the scientific community with an open source access platform for the mechanistic simulation of such early damage. This paper presents the most recent review of the Geant4-DNA extension, as available to Geant4 users since June 2015 (release 10.2 Beta). In particular, the review includes the description of new physical models for the description of electron elastic and inelastic interactions in liquid water, as well as new examples dedicated to the simulation of physicochemical and chemical stages of water radiolysis. Several implementations of geometrical models of biological targets are presented as well, and the list of Geant4-DNA examples is described., (Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)