Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4.

PURPOSE: Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain. METHODS: The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment. RESULTS: Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of ß-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively. CONCLUSIONS: The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

Neutron Capture Enhances Dose and Reduces Cancer Cell Viability in and out of Beam During Helium and Carbon Ion Therapy.

PURPOSE: Neutron capture enhanced particle therapy (NCEPT) is a proposed augmentation of charged particle therapy that exploits thermal neutrons generated internally, within the treatment volume via nuclear fragmentation, to deliver a biochemically targeted radiation dose to cancer cells. This work is the first experimental demonstration of NCEPT, performed using both carbon and helium ion beams with 2 different targeted neutron capture agents (NCAs). METHODS AND MATERIALS: Human glioblastoma cells (T98G) were irradiated by carbon and helium ion beams in the presence of NCAs [10B]-BPA and [157Gd]-DOTA-TPP. Cells were positioned within a polymethyl methacrylate phantom either laterally adjacent to or within a 100 × 100 × 60 mm spread out Bragg peak (SOBP). The effect of NCAs and location relative to the SOBP on the cells was measured by cell growth and survival assays in 6 independent experiments. Neutron fluence within the phantom was characterized by quantifying the neutron activation of gold foil. RESULTS: Cells placed inside the treatment volume reached 10% survival by 2 Gy of carbon or 2 to 3 Gy of helium in the presence of NCAs compared with 5 Gy of carbon and 7 Gy of helium with no NCA. Cells placed adjacent to the treatment volume showed a dose-dependent decrease in cell growth when treated with NCAs, reaching 10% survival by 6 Gy of carbon or helium (to the treatment volume), compared with no detectable effect on cells without NCA. The mean thermal neutron fluence at the center of the SOBP was approximately 2.2 × 109 n/cm2/Gy (relative biological effectiveness) for the carbon beam and 5.8 × 109 n/cm2/Gy (relative biological effectiveness) for the helium beam and gradually decreased in all directions. CONCLUSIONS: The addition of NCAs to cancer cells during carbon and helium beam irradiation has a measurable effect on cell survival and growth in vitro. Through the capture of internally generated neutrons, NCEPT introduces the concept of a biochemically targeted radiation dose to charged particle therapy. NCEPT enables the established pharmaceuticals and concepts of neutron capture therapy to be applied to a wider range of deeply situated and diffuse tumors, by targeting this dose to microinfiltrates and cells outside of defined treatment regions. These results also demonstrate the potential for NCEPT to provide an increased dose to tumor tissue within the treatment volume, with a reduction in radiation doses to off-target tissue.

First experimental demonstration of real-time neutron capture discrimination in helium and carbon ion therapy.

This work provides the first experimental proof of an increased neutron capture photon signal following the introduction of boron to a PMMA phantom during helium and carbon ion therapies in Neutron Capture Enhanced Particle Therapy (NCEPT). NCEPT leverages [Formula: see text]B neutron capture, leading to the emission of detectable 478 keV photons. Experiments were performed at the Heavy Ion Medical Accelerator in Chiba, Japan, with two Poly(methyl methacrylate) (PMMA) targets, one bearing a boron insert. The BeNEdiCTE gamma-ray detector measured an increase in the 478 keV signal of 45 ± 7% and 26 ± 2% for carbon and helium ion irradiation, respectively. Our Geant4 Monte Carlo simulation model, developed to investigate photon origins, found less than 30% of detected photons originated from the insert, while boron in the detector's circuit boards contributed over 65%. Further, the model investigated detector sensitivity, establishing its capability to record a 10% increase in 478 keV photon detection at a target [Formula: see text]B concentration of 500 ppm using spectral windowing alone, and 25% when combined with temporal windowing. The linear response extended to concentrations up to 20,000 ppm. The increase in the signal in all evaluated cases confirm the potential of the proposed detector design for neutron capture quantification in NCEPT.

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.

Energy imparted and ionisation yield at the nanometre scale: results for extended beams.

The metrological problem of interpreting ionisation-based micro- and nanodosimetric measurements in terms of quantities proportional to energy imparted becomes particularly relevant when the sensitive volume (SV) size is in the nanometre range. At these scales, a constant W-value cannot be assumed, and the stochastics of the energy transfer per single collision could play a more important role. This problem was recently analysed by our group by means of track-structure Monte Carlo simulations with the Geant4-DNA code, finding a strong correlation between the energy imparted and ionisation yield also for SV diameters of 1 nm. As the previous study was limited to primary beams of radius zero crossing the sensitive sphere along its diameter, it is the aim of the present work to extend the analysis to beams with a radius larger than the dimensions of the SV, to better assess the role played by secondary electrons.

In-silico calculations of DNA damage induced by α-particles in the 224Ra DaRT decay chain for a better understanding of the radiobiological effectiveness of this treatment.

Diffusing alpha-emitters radiation Therapy (DaRT) is an interstitial brachytherapy technique using 224Ra seeds. For accurate treatment planning a good understanding of the early DNA damage due to α-particles is required. Geant4-DNA was used to calculate the initial DNA damage and radiobiological effectiveness due to α-particles with linear energy transfer (LET) values in the range 57.5-225.9 keV/µm from the 224Ra decay chain. The impact of DNA base pair density on DNA damage has been modelled, as this parameter varies between human cell lines. Results show that the quantity and complexity of DNA damage changes with LET as expected. Indirect damage, due to water radical reactions with the DNA, decreases and becomes less significant at higher LET values as shown in previous studies. As expected, the yield of complex double strand breaks (DSBs), which are harder for a cell to repair, increases approximately linearly with LET. The level of complexity of DSBs and radiobiological effectiveness have been found to increase with LET as expected. The quantity of DNA damage has been shown to increase for increased DNA density in the expected base pair density range of human cells. The change in damage yield as a function of base pair density is largest for higher LET α-particles, an increase of over 50% for individual strand breaks between 62.7 and 127.4 keV/µm. This change in yield shows that the DNA base pair density is an important parameter for modelling DNA damage particularly at higher LET where the DNA damage is greatest and most complex.

Assessment of cross-dose contributions from tumors within computational phantoms using a Geant4 radiation dosimetry tool exploiting hybrid analytical/voxelised geometries.

BACKGROUND: Dosimetry software tools developed for Radiopharmaceutical Therapy, such as OLINDA/EXM or IDAC-Dose, account only for radiation dose to organs from radiopharmaceutical taken up in other organs. PURPOSE: The aim of this study is to present a methodology, that can be applied to any voxelised computational model, able to account for cross-dose to organs from tumors of any shape and number enclosed within an organ. METHODS: A Geant4 application using hybrid analytical/voxelised geometries has been developed as an extension to the ICRP110_HumanPhantom Geant4 advanced example and validated against ICRP publication 133. In this new Geant4 application, tumors are defined using the Geant4 Parallel Geometry functionality, which allows the co-existence of two independent geometries in the same Monte Carlo simulation. The methodology was validated by estimating total dose to healthy tissue from 90 Y and from 177 Lu distributed within tumors of various sizes localized within the liver of the ICRP110 adult male phantom. RESULTS: Agreement of the Geant4 application with ICRP133 was within 5% when masses were adjusted for blood content. Total dose to healthy liver and to tumors was found to agree within 1% when compared to the ground truth. CONCLUSIONS: The methodology presented in this work can be extended to investigate total dose to healthy tissue from systemic uptake of radiopharmaceuticals in tumors of different sizes using any voxelised computational dosimetric model.

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

PURPOSE: This study aimed to develop a computational environment for the accurate simulation of human cancer cell irradiation using Geant4-DNA. New cell geometrical models were developed and irradiated by alpha particle beams to induce DNA damage. The proposed approach may help further investigation of the benefits of external alpha irradiation therapy. METHODS: The Geant4-DNA Monte Carlo (MC) toolkit allows the simulation of cancer cell geometries that can be combined with accurate modelling of physical, physicochemical and chemical stages of liquid water irradiation, including radiolytic processes. Geant4-DNA is used to calculate direct and non-direct DNA damage yields, such as single and double strand breaks, produced by the deposition of energy or by the interaction of DNA with free radicals. RESULTS: In this study, the "molecularDNA" example application of Geant4-DNA was used to quantify early DNA damage in human cancer cells upon irradiation with alpha particle beams, as a function of linear energy transfer (LET). The MC simulation results are compared to experimental data, as well as previously published simulation data. The simulation results agree well with the experimental data on DSB yields in the lower LET range, while the experimental data on DSB yields are lower than the results obtained with the "molecularDNA" example in the higher LET range. CONCLUSION: This study explored and demonstrated the possibilities of the Geant4-DNA toolkit together with the "molecularDNA" example to simulate the helium beam irradiation of cancer cell lines, to quantify the early DNA damage, or even the following DNA damage response.

Accurate and Fast Deep Learning Dose Prediction for a Preclinical Microbeam Radiation Therapy Study Using Low-Statistics Monte Carlo Simulations.

Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumor diagnoses that currently have poor clinical treatment outcomes, such as gliosarcomas. Monte Carlo (MC) simulations are one of the most used methods at the Imaging and Medical Beamline, Australian Synchrotron to calculate the dose in MRT preclinical studies. The steep dose gradients associated with the 50µm-wide coplanar beamlets present a significant challenge for precise MC simulation of the dose deposition of an MRT irradiation treatment field in a short time frame. The long computation times inhibit the ability to perform dose optimization in treatment planning or apply online image-adaptive radiotherapy techniques to MRT. Much research has been conducted on fast dose estimation methods for clinically available treatments. However, such methods, including GPU Monte Carlo implementations and machine learning (ML) models, are unavailable for novel and emerging cancer radiotherapy options such as MRT. In this work, the successful application of a fast and accurate ML dose prediction model for a preclinical MRT rodent study is presented for the first time. The ML model predicts the peak doses in the path of the microbeams and the valley doses between them, delivered to the tumor target in rat patients. A CT imaging dataset is used to generate digital phantoms for each patient. Augmented variations of the digital phantoms are used to simulate with Geant4 the energy depositions of an MRT beam inside the phantoms with 15% (high-noise) and 2% (low-noise) statistical uncertainty. The high-noise MC simulation data are used to train the ML model to predict the energy depositions in the digital phantoms. The low-noise MC simulations data are used to test the predictive power of the ML model. The predictions of the ML model show an agreement within 3% with low-noise MC simulations for at least 77.6% of all predicted voxels (at least 95.9% of voxels containing tumor) in the case of the valley dose prediction and for at least 93.9% of all predicted voxels (100.0% of voxels containing tumor) in the case of the peak dose prediction. The successful use of high-noise MC simulations for the training, which are much faster to produce, accelerates the production of the training data of the ML model and encourages transfer of the ML model to different treatment modalities for other future applications in novel radiation cancer therapies.

A Geant4 shielding design for the first US carbon multi-ion hybrid synchrotron facility.

The Mayo Clinic Florida Integrated Oncology Building will be the home of the first spot-scanning only carbon/proton hybrid therapy system by Hitachi, Ltd. It will provide proton beams up to kinetic energies of 230 MeV and carbon beams up to 430 MeV n-1for clinical deployment. To provide adequate radiation protection, the Geant4 (v10.6) Monte Carlo toolkit was utilized to quantify the ambient dose equivalent at a 10 mm depth (H*(10)) for photons and neutrons. To perform accurate calculations of the ambient dose equivalent, three-dimensional computer-aided design files of the entire planned facility were imported into Geant4, as well as certain particle system components such as the bending magnets, fast Faraday cup, and gantry. Particle fluence was scored using 60 cm diameter spheres, which were strategically placed throughout areas of interests. Analytical calculations were performed as first-pass design checks. Major shielding slabs were optimized using Geant4 simulations iteratively, with more than 20 alternative designs evaluated within Geant4. The 430 MeV n-1carbon beams played the most significant role in concrete thickness Requirements. The primary wall thickness for the carbon fixed beam room is 4 meters. The presence of the proton gantry structure in the simulation caused the ambient dose equivalent to increase by around 67% at the maze entrance, but a decrease in the high energy beam transport corridor. All shielding primary and secondary goals for clinical operations were met per state regulation and national guidelines.

Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA.

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.

Development of a more accurate Geant4 quantum molecular dynamics model for hadron therapy.

Objective. Although in heavy-ion therapy, the quantum molecular dynamics (QMD) model is one of the most fundamental physics models providing an accurate daughter-ion production yield in the final state, there are still non-negligible differences with the experimental results. The aim of this study is to improve fragment production in water phantoms by developing a more accurate QMD model in Geant4.Approach. A QMD model was developed by implementing modern Skyrme interaction parameter sets, as well as by incorporating with an ad hocα-cluster model in the initial nuclear state. Two adjusting parameters were selected that can significantly affect the fragment productions in the QMD model: the radius to discriminate a cluster to which nucleons belong after the nucleus-nucleus reaction, denoted byR, and the squared standard deviation of the Gaussian packet, denoted byL. Squared Mahalanobis's distance of fragment yields and angular distributions with 1, 2, and the higher atomic number for the produced fragments were employed as objective functions, and multi-objective optimization (MOO), which make it possible to compare quantitatively the simulated production yields with the reference experimental data, was performed.Main results. The MOO analysis showed that the QMD model with modern Skyrme parameters coupled with the proposedα-cluster model, denoted as SkM*α, can drastically improve light fragments yields in water. In addition, the proposed model reproduced the kinetic energy distribution of the fragments accurately. The optimizedLin SkM*αwas confirmed to be realistic by the charge radii analysis in the ground state formation.Significance. The proposed framework using MOO was demonstrated to be very useful in judging the superiority of the proposed nuclear model. The optimized QMD model is expected to improve the accuracy of heavy-ion therapy dosimetry.

An inception network for positron emission tomography based dose estimation in carbon ion therapy.

Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image.Approach. A set of dose deposition and positron annihilation profiles for monoenergetic12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a12C ion beam at QST's Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental12C SOBP profiles.Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm.Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.

Detection and discrimination of neutron capture events for NCEPT dose quantification.

Neutron Capture Enhanced Particle Therapy (NCEPT) boosts the effectiveness of particle therapy by capturing thermal neutrons produced by beam-target nuclear interactions in and around the treatment site, using tumour-specific [Formula: see text]B or [Formula: see text]Gd-based neutron capture agents. Neutron captures release high-LET secondary particles together with gamma photons with energies of 478 keV or one of several energies up to 7.94 MeV, for [Formula: see text]B and [Formula: see text]Gd, respectively. A key requirement for NCEPT's translation is the development of in vivo dosimetry techniques which can measure both the direct ion dose and the dose due to neutron capture. In this work, we report signatures which can be used to discriminate between photons resulting from neutron capture and those originating from other processes. A Geant4 Monte Carlo simulation study into timing and energy thresholds for discrimination of prompt gamma photons resulting from thermal neutron capture during NCEPT was conducted. Three simulated [Formula: see text] mm[Formula: see text] cubic PMMA targets were irradiated by [Formula: see text]He or [Formula: see text]C ion beams with a spread out Bragg peak (SOBP) depth range of 60 mm; one target is homogeneous while the others include [Formula: see text] mm[Formula: see text] neutron capture inserts (NCIs) of pure [Formula: see text]B or [Formula: see text]Gd located at the distal edge of the SOBP. The arrival times of photons and neutrons entering a simulated [Formula: see text] mm[Formula: see text] ideal detector were recorded. A temporal mask of 50-60 ns was found to be optimal for maximising the discrimination of the photons resulting from the neutron capture by boron and gadolinium. A range of candidate detector and thermal neutron shielding materials were simulated, and detections meeting the proposed acceptance criteria (i.e. falling within the target energy window and arriving 60 ns post beam-off) were classified as true or false positives, depending on their origin. The ratio of true/false positives ([Formula: see text]) was calculated; for targets with [Formula: see text]B and [Formula: see text]Gd NCIs, the detector materials which resulted in the highest [Formula: see text] were cadmium-shielded CdTe and boron-shielded LSO, respectively. The optimal irradiation period for both carbon and helium ions was 1 µs for the [Formula: see text]B NCI and 1 ms for the [Formula: see text]Gd NCI.

Fast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D-UNet generative adversarial networks.

PURPOSE: Novel radiotherapy techniques like synchrotron X-ray microbeam radiation therapy (MRT) require fast dose distribution predictions that are accurate at the sub-mm level, especially close to tissue/bone/air interfaces. Monte Carlo (MC) physics simulations are recognized to be one of the most accurate tools to predict the dose delivered in a target tissue but can be very time consuming and therefore prohibitive for treatment planning. Faster dose prediction algorithms are usually developed for clinically deployed treatments only. In this work, we explore a new approach for fast and accurate dose estimations suitable for novel treatments using digital phantoms used in preclinical development and modern machine learning techniques. We develop a generative adversarial network (GAN) model, which is able to emulate the equivalent Geant4 MC simulation with adequate accuracy and use it to predict the radiation dose delivered by a broad synchrotron beam to various phantoms. METHODS: The energy depositions used for the training of the GAN are obtained using full Geant4 MC simulations of a synchrotron radiation broad beam passing through the phantoms. The energy deposition is scored and predicted in voxel matrices of size 140 × 18 × 18 with a voxel edge length of 1 mm. The GAN model consists of two competing 3D convolutional neural networks, which are conditioned on the photon beam and phantom properties. The generator network has a U-Net structure and is designed to predict the energy depositions of the photon beam inside three phantoms of variable geometry with increasing complexity. The critic network is a relatively simple convolutional network, which is trained to distinguish energy depositions predicted by the generator from the ones obtained with the full MC simulation. RESULTS: The energy deposition predictions inside all phantom geometries under investigation show deviations of less than 3% of the maximum deposited energy from the simulation for roughly 99% of the voxels in the field of the beam. Inside the most realistic phantom, a simple pediatric head, the model predictions deviate by less than 1% of the maximal energy deposition from the simulations in more than 96% of the in-field voxels. For all three phantoms, the model generalizes the energy deposition predictions well to phantom geometries, which have not been used for training the model but are interpolations of the training data in multiple dimensions. The computing time for a single prediction is reduced from several hundred hours using Geant4 simulation to less than a second using the GAN model. CONCLUSIONS: The proposed GAN model predicts dose distributions inside unknown phantoms with only small deviations from the full MC simulation with computations times of less than a second. It demonstrates good interpolation ability to unseen but similar phantom geometries and is flexible enough to be trained on data with different radiation scenarios without the need for optimization of the model parameter. This proof-of-concept encourages to apply and further develop the model for the use in MRT treatment planning, which requires fast and accurate predictions with sub-mm resolutions.

Implementation of the EPICS2017 database for photons in Geant4.

This paper describes in detail the implementation of Geant4 Livermore electromagnetic physics models based on the EPICS2017 database for the low energy transport of photons. These models describe four photon processes: gamma conversion, Compton scattering, photoelectric effect and Rayleigh scattering. New parameterizations based on EPICS2017 were performed for scattering functions of Compton effect, subshell cross-sections of the photoelectric effect and form factors of Rayleigh scattering, in order to improve the precision of fitted values compared to tabulated values. Comparisons between new and old parameterizations were also carried out to evaluate the precision of the new parameterizations. The models were tested through a comparative study, in which the mass attenuation coefficient was calculated for both total photon interaction and each process using Geant4 simulations based on EPICS2017 and EPDL97 respectively. The results obtained from the simulations were found in good agreement with the XCOM reference data.

Evaluation of silicon strip detectors in transmission mode for online beam monitoring in microbeam radiation therapy at the Australian Synchrotron.

Successful transition of synchrotron-based microbeam radiation therapy (MRT) from pre-clinical animal studies to human trials is dependent upon ensuring that there are sufficient and adequate measures in place for quality assurance purposes. Transmission detectors provide researchers and clinicians with a real-time quality assurance and beam-monitoring instrument to ensure safe and accurate dose delivery. In this work, the effect of transmission detectors of different thicknesses (10 and 375 µm) upon the photon energy spectra and dose deposition of spatially fractionated synchrotron radiation is quantified experimentally and by means of a dedicated Geant4 simulation study. The simulation and experimental results confirm that the presence of the 375 µm thick transmission detector results in an approximately 1-6% decrease in broad-beam and microbeam peak dose. The capability to account for the reduction in dose and change to the peak-to-valley dose ratio justifies the use of transmission detectors as thick as 375 µm in MRT provided that treatment planning systems are able to account for their presence. The simulation and experimental results confirm that the presence of the 10 µm thick transmission detector shows a negligible impact (<0.5%) on the photon energy spectra, dose delivery and microbeam structure for both broad-beam and microbeam cases. Whilst the use of 375 µm thick detectors would certainly be appropriate, based upon the idea of best practice the authors recommend that 10 µm thick transmission detectors of this sort be utilized as a real-time quality assurance and beam-monitoring tool during MRT.

Performance Evaluation for Repair of HSGc-C5 Carcinoma Cell Using Geant4-DNA.

Track-structure Monte Carlo simulations are useful tools to evaluate initial DNA damage induced by irradiation. In the previous study, we have developed a Gean4-DNA-based application to estimate the cell surviving fraction of V79 cells after irradiation, bridging the gap between the initial DNA damage and the DNA rejoining kinetics by means of the two-lesion kinetics (TLK) model. However, since the DNA repair performance depends on cell line, the same model parameters cannot be used for different cell lines. Thus, we extended the Geant4-DNA application with a TLK model for the evaluation of DNA damage repair performance in HSGc-C5 carcinoma cells which are typically used for evaluating proton/carbon radiation treatment effects. For this evaluation, we also performed experimental measurements for cell surviving fractions and DNA rejoining kinetics of the HSGc-C5 cells irradiated by 70 MeV protons at the cyclotron facility at the National Institutes for Quantum and Radiological Science and Technology (QST). Concerning fast- and slow-DNA rejoining, the TLK model parameters were adequately optimized with the simulated initial DNA damage. The optimized DNA rejoining speeds were reasonably agreed with the experimental DNA rejoining speeds. Using the optimized TLK model, the Geant4-DNA simulation is now able to predict cell survival and DNA-rejoining kinetics for HSGc-C5 cells.

Flexible Polymer X-ray Detectors with Non-fullerene Acceptors for Enhanced Stability: Toward Printable Tissue Equivalent Devices for Medical Applications.

There is growing interest in the development of novel materials and devices capable of ionizing radiation detection for medical applications. Organic semiconductors are promising candidates to meet the demands of modern detectors, such as low manufacturing costs, mechanical flexibility, and a response to radiation equivalent to human tissue. However, organic semiconductors have typically been employed in applications that convert low energy photons into high current densities, for example, solar cells and LEDs, and thus existing design rules must be re-explored for ionizing radiation detection where high energy photons are converted into typically much lower current densities. In this work, we report the optoelectronic and X-ray dosimetric response of a tissue equivalent organic photodetector fabricated with solution-based inks prepared from polymer donor poly(3-hexylthiophene) (P3HT) blended with either a non-fullerene acceptor (5Z,5'Z)-5,5'-((7,7'-(4,4,9,9-tetraoctyl-4,9-dihydro-s-indaceno[1,2-b:5,6-b']dithiophene-2,7-diyl)bis(benzo[c][1,2,5]thiadiazole-7,4-diyl))bis(methanylylidene))bis(3-ethyl-2-thioxothiazolidin-4-one) (o-IDTBR) or a fullerene acceptor, [6,6]-phenyl-C61-butyric acid methyl ester (PCBM). Indirect detection of X-rays was achieved via coupling of organic photodiodes with a plastic scintillator. Both detectors displayed an excellent response linearity with dose, with sensitivities to 6 MV photons of 263.4 ± 0.6 and 114.2 ± 0.7 pC/cGy recorded for P3HT:PCBM and P3HT:o-IDTBR detectors, respectively. Both detectors also exhibited a fast temporal response, able to resolve individual 3.6 µs pulses from the linear accelerator. Energy dependence measurements highlighted that the photodetectors were highly tissue equivalent, though an under-response in devices compared to water by up to a factor of 2.3 was found for photon energies of 30-200 keV due to the response of the plastic scintillator. The P3HT:o-IDTBR device exhibited a higher stability to radiation, showing just an 18.4% reduction in performance when exposed to radiation doses of up to 10 kGy. The reported devices provide a successful demonstration of stable, printable, flexible, and tissue-equivalent radiation detectors with energy dependence similar to other scintillator-based detectors used in radiotherapy.