A digital male pelvis phantom series showing anatomical variations over the course of fractionated radiotherapy treatment

BACKGROUND

Daily IGRT images show day-to-day anatomical variations in patients undergoing fractionated prostate radiotherapy. This is of particular importance in particle beam treatments.

PURPOSE

To develop a digital phantom series showing variation in pelvic anatomy for evaluating treatment planning and IGRT procedures in particle radiotherapy.

METHODS

A pelvic phantom series was developed from the planning MRI and kVCT (planning CT) images along with six of the daily serial MVCT images taken of a single patient treated with a full bladder on a Tomotherapy unit. The selected patient had clearly visible yet unexceptional internal anatomy variation. Prostate, urethra, bladder, rectum, bowel, bowel gas, bone and soft tissue were contoured and a single Hounsfield Unit was assigned to each region. Treatment plans developed on the kVCT for photon, proton and carbon beams were recalculated on each phantom to demonstrate a clinical application of the series. Proton plans were developed with and without robust optimization.

RESULTS

Limited to axial slices with prostate, the bladder volume varied from 6 to 46 cm3, the rectal volume (excluding gas) from 22 to 52 cm3, and rectal gas volume from zero to 18 cm3. The water equivalent path length to the prostate varied by up to 1.5 cm . The variations resulted in larger changes in the RBE-weighted Dose Volume Histograms of the non-robust proton plan and the carbon plan compared to the robust proton plan, the latter similar to the photon plan. The prostate coverage (V100%) decreased by an average of 18% in the carbon plan, 16% in the non-robust proton plan, 1.8% in the robust proton plan, and 4.4% in the photon plan. The volume of rectum receiving 75% of the prescription dose (V75%) increased by an average of 3.7 cm3, 4.7 cm3, 1.9 cm3, and 0.6 cm3 in those four plans, respectively.

CONCLUSIONS

The digital pelvic phantom series provides for quantitative investigation of IGRT procedures and new methods for improving accuracy in particle therapy and may be used in cross-institutional comparisons for clinical trial quality assurance.

Cellular lethal damage of 64Cu incorporated in mammalian genome evaluated with Monte Carlo methods

Purpose

Targeted Radionuclide Therapy (TRT) with Auger Emitters (AE) is a technique that allows targeting specific sites on tumor cells using radionuclides. The toxicity of AE is critically dependent on its proximity to the DNA. The aim of this study is to quantify the DNA damage and radiotherapeutic potential of the promising AE radionuclide copper-64 (64Cu) incorporated into the DNA of mammalian cells using Monte Carlo track-structure simulations.

Methods

A mammalian cell nucleus model with a diameter of 9.3 μm available in TOPAS-nBio was used. The cellular nucleus consisted of double-helix DNA geometrical model of 2.3 nm diameter surrounded by a hydration shell with a thickness of 0.16 nm, organized in 46 chromosomes giving a total of 6.08 giga base-pairs (DNA density of 14.4 Mbp/μm3). The cellular nucleus was irradiated with monoenergetic electrons and radiation emissions from several radionuclides including 111In, 125I, 123I, and 99mTc in addition to 64Cu. For monoenergetic electrons, isotropic point sources randomly distributed within the nucleus were modeled. The radionuclides were incorporated in randomly chosen DNA base pairs at two positions near to the central axis of the double-helix DNA model at (1) 0.25 nm off the central axis and (2) at the periphery of the DNA (1.15 nm off the central axis). For all the radionuclides except for 99mTc, the complete physical decay process was explicitly simulated. For 99mTc only total electron spectrum from published data was used. The DNA Double Strand Breaks (DSB) yield per decay from direct and indirect actions were quantified. Results obtained for monoenergetic electrons and radionuclides 111In, 125I, 123I, and 99mTc were compared with measured and calculated data from the literature for verification purposes. The DSB yields per decay incorporated in DNA for 64Cu are first reported in this work. The therapeutic effect of 64Cu (activity that led 37% cell survival after two cell divisions) was determined in terms of the number of atoms incorporated into the nucleus that would lead to the same DSBs that 100 decays of 125I. Simulations were run until a 2% statistical uncertainty (1 standard deviation) was achieved.

Results

The behavior of DSBs as a function of the energy for monoenergetic electrons was consistent with published data, the DSBs increased with the energy until it reached a maximum value near 500 eV followed by a continuous decrement. For 64Cu, when incorporated in the genome at evaluated positions (1) and (2), the DSB were 0.171 ± 0.003 and 0.190 ± 0.003 DSB/decay, respectively. The number of initial atoms incorporated into the genome (per cell) for 64Cu that would cause a therapeutic effect was estimated as 3,107 ± 28, that corresponds to an initial activity of 47.1 ± 0.4 × 10-3 Bq.

Conclusion

Our results showed that TRT with 64Cu has comparable therapeutic effects in cells as that of TRT with radionuclides currently used in clinical practice.

Microdosimetric Analysis for Boron Neutron Capture Therapy via Monte Carlo Track Structure Simulation with Modified Lithium Cross-sections

Boron neutron capture therapy (BNCT) is a cellular-level hadron therapy achieving therapeutic effects via the synergistic action of multiple particles, including Lithium, alpha, proton, and photon. However, evaluating the relative biological effectiveness (RBE) in BNCT remains challenging. In this research, we performed a microdosimetric calculation for BNCT using the Monte Carlo track structure (MCTS) simulation toolkit, TOPAS-nBio. This paper reports the first attempt to derive the ionization cross-sections of low-energy (>0.025 MeV/u) Lithium for MCTS simulation based on the effective charge cross-section scalation method and phenomenological double-parameter modification. The fitting parameters λ1=1.101,λ2=3.486 were determined to reproduce the range and stopping power data from the ICRU report 73. Besides, the lineal energy spectra of charged particles in BNCT were calculated, and the influence of sensitive volume (SV) size was discussed. Condensed history simulation obtained similar results with MCTS when using Micron-SV while overestimating the lineal energy when using Nano-SV. Furthermore, we found that the microscopic boron distribution can significantly affect the lineal energy for Lithium, while the effect for alpha is minimal. Similar results to the published data by PHITS simulation were observed for the compound particles and monoenergetic protons when using micron-SV. Spectra with nano-SV reflected that the different track densities and absorbed doses in the nucleus together result in the dramatic difference in the macroscopic biological response of BPA and BSH. This work and the developed methodology could impact the research fields in BNCT where understanding radiation effects is crucial, such as the treatment planning system, source evaluation, and new boron drug development.

Impact of DNA Geometry and Scoring on Monte Carlo Track-Structure Simulations of Initial Radiation-Induced Damage

Track structure Monte Carlo simulations are a useful tool to investigate the damage induced to DNA by ionizing radiation. These simulations usually rely on simplified geometrical representations of the DNA subcomponents. DNA damage is determined by the physical and physicochemical processes occurring within these volumes. In particular, damage to the DNA backbone is generally assumed to result in strand breaks. DNA damage can be categorized as direct (ionization of an atom part of the DNA molecule) or indirect (damage from reactive chemical species following water radiolysis). We also consider quasi-direct effects, i.e., damage originated by charge transfers after ionization of the hydration shell surrounding the DNA. DNA geometries are needed to account for the damage induced by ionizing radiation, and different geometry models can be used for speed or accuracy reasons. In this work, we use the Monte Carlo track structure tool TOPAS-nBio, built on top of Geant4-DNA, for simulation at the nanometer scale to evaluate differences among three DNA geometrical models in an entire cell nucleus, including a sphere/spheroid model specifically designed for this work. In addition to strand breaks, we explicitly consider the direct, quasi-direct, and indirect damage induced to DNA base moieties. We use results from the literature to determine the best values for the relevant parameters. For example, the proportion of hydroxyl radical reactions between base moieties was 80%, and between backbone, moieties was 20%, the proportion of radical attacks leading to a strand break was 11%, and the expected ratio of base damages and strand breaks was 2.5-3. Our results show that failure to update parameters for new geometric models can lead to significant differences in predicted damage yields.

TOPAS-nBio simulation of temperature-dependent indirect DNA strand break yields

Current Monte Carlo simulations of DNA damage have been reported only at ambient temperature. The aim of this work is to use TOPAS-nBio to simulate the yields of DNA single-strand breaks (SSBs) and double-strand breaks (DSBs) produced in plasmids under low-LET irradiation incorporating the effect of the temperature changes in the environment. A new feature was implemented in TOPAS-nBio to incorporate reaction rates used in the simulation of the chemical stage of water radiolysis as a function of temperature. The implemented feature was verified by simulating temperature-dependent G-values of chemical species in liquid water from 20 °C to 90 °C. For radiobiology applications, temperature dependent SSB and DSB yields were calculated from 0 °C to 42 °C, the range of available published measured data. For that, supercoiled DNA plasmids dissolved in aerated solutions containing EDTA irradiated by Cobalt-60 gamma-rays were simulated. TOPAS-nBio well reproduced published temperature-dependent G-values in liquid water and the yields of SSB and DSB for the temperature range considered. For strand break simulations, the model shows that the yield of SSB and DSB increased linearly with the temperature at a rate of (2.94 ± 0.17) × 10−10 Gy–1 Da–1 °C–1 (R 2 = 0.99) and (0.13 ± 0.01) × 10−10 Gy–1 Da–1 °C–1 (R 2 = 0.99), respectively. The extended capability of TOPAS-nBio is a complementary tool to simulate realistic conditions for a large range of environmental temperatures, allowing refined investigations of the biological effects of radiation.

Development of Ultra-High Dose-Rate (FLASH) Particle Therapy

Research efforts in FLASH radiotherapy have increased at an accelerated pace recently. FLASH radiotherapy involves ultra-high dose rates and has shown to reduce toxicity to normal tissue while maintaining tumor response in pre-clinical studies when compared to conventional dose rate radiotherapy. The goal of this review is to summarize the studies performed to-date with proton, electron, and heavy ion FLASH radiotherapy, with particular emphasis on the physical aspects of each study and the advantages and disadvantages of each modality. Beam delivery parameters, experimental set-up, and the dosimetry tools used are described for each FLASH modality. In addition, modeling efforts and treatment planning for FLASH radiotherapy is discussed along with potential drawbacks when translated into the clinical setting. The final section concludes with further questions that have yet to be answered before safe clinical implementation of FLASH radiotherapy.

DNA damage modeled with Geant4-DNA: effects of plasmid DNA conformation and experimental conditions

The chemical stage of the Monte Carlo track-structure (MCTS) code Geant4-DNA was extended for its use in DNA strand break (SB) simulations and compared against published experimental data. Geant4-DNA simulations were performed using pUC19 plasmids (2686 base pairs) in a buffered solution of DMSO irradiated by⁶⁰Co or¹³⁷Csγ-rays. A comprehensive evaluation of SSB yields was performed considering DMSO, DNA concentration, dose and plasmid supercoiling. The latter was measured using the super helix density value used in a Brownian dynamics plasmid generation algorithm. The Geant4-DNA implementation of the independent reaction times method (IRT), developed to simulate the reaction kinetics of radiochemical species, allowed to score the fraction of supercoiled, relaxed and linearized plasmid fractions as a function of the absorbed dose. The percentage of the number of SB after •OH + DNA and H• + DNA reactions, referred as SSB efficiency, obtained using MCTS were 13.77% and 0.74% respectively. This is in reasonable agreement with published values of 12% and 0.8%. The SSB yields as a function of DMSO concentration, DNA concentration and super helix density recreated the expected published experimental behaviors within 5%, one standard deviation. The dose response of SSB and DSB yields agreed with published measurements within 5%, one standard deviation. We demonstrated that the developed extension of IRT in Geant4-DNA, facilitated the reproduction of experimental conditions. Furthermore, its calculations were strongly in agreement with experimental data. These two facts will facilitate the use of this extension in future radiobiological applications, aiding the study of DNA damage mechanisms with a high level of detail.

TOPAS-nBio validation for simulating water radiolysis and DNA damage under low-LET irradiation

The chemical stage of the Monte Carlo track-structure simulation code Geant4-DNA has been revised and validated. The root-mean-square (RMS) empirical parameter that dictates the displacement of water molecules after an ionization and excitation event in Geant4-DNA has been shortened to better fit experimental data. The pre-defined dissociation channels and branching ratios were not modified, but the reaction rate coefficients for simulating the chemical stage of water radiolysis were updated. The evaluation of Geant4-DNA was accomplished with TOPAS-nBio. For that, we compared predicted time-dependentGvalues in pure liquid water for^·OH, e^-_aq, and H₂with published experimental data. For H₂O₂and H^·, simulation of added scavengers at different concentrations resulted in better agreement with measurements. In addition, DNA geometry information was integrated with chemistry simulation in TOPAS-nBio to realize reactions between radiolytic chemical species and DNA. This was used in the estimation of the yield of single-strand breaks (SSB) induced by¹³⁷Csγ-ray radiolysis of supercoiled pUC18 plasmids dissolved in aerated solutions containing DMSO. The efficiency of SSB induction by reaction between radiolytic species and DNA used in the simulation was chosen to provide the best agreement with published measurements. An RMS displacement of 1.24 nm provided agreement with measured data within experimental uncertainties for time-dependentGvalues and under the presence of scavengers. SSB efficiencies of 24% and 0.5% for^·OH and H^·, respectively, led to an overall agreement of TOPAS-nBio results within experimental uncertainties. The efficiencies obtained agreed with values obtained with published non-homogeneous kinetic model and step-by-step Monte Carlo simulations but disagreed by 12% with published direct measurements. Improvement of the spatial resolution of the DNA damage model might mitigate such disagreement. In conclusion, with these improvements, Geant4-DNA/TOPAS-nBio provides a fast, accurate, and user-friendly tool for simulating DNA damage under low linear energy transfer irradiation.

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

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

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

PURPOSE

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications.

METHODS AND MATERIALS

Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. The four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated.

RESULTS

The air-kerma strength was (9.772 ± 0.001) × 10-8 U Bq-1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h-1 U-1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data.

CONCLUSIONS

TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.

Boronated Condensed DNA as a Heterochromatic Radiation Target Model

The compound 4-dihydroxyboryl-l-phenylalanine (BPA) has found use in clinical trials of boron neutron capture therapy (BNCT). Here, we have examined the interaction with DNA of an amide-blocked BPA derivative of hexa-l-arginine (Ac-BPA-Arg6-NH2). Physical and spectroscopic assays show that this peptide binds to and condenses DNA. The resulting condensates are highly resistant to the effects of nuclease incubation (68-fold) and gamma (38-fold) irradiation. Radioprotection was modeled by Monte Carlo track structure simulations of DNA single strand breaks (SSBs) with TOPAS-nBio. The differences between experimental and simulated SSB yields for uncondensed and condensed DNAs were ca. 2 and 18%, respectively. These observations indicate that the combination of a plasmid DNA target, the BPA-containing peptide, and track structure simulation provides a powerful approach to characterize DNA damage by the high-LET radiation associated with neutron capture on boron.

Dispersion calibration for the National Ignition Facility electron-positron-proton spectrometers for intense laser matter interactions

Electron-positron pairs, produced in intense laser-solid interactions, are diagnosed using magnetic spectrometers with image plates, such as the National Ignition Facility Electron-Positron-Proton Spectrometers (EPPSs). Although modeling can help infer the quantitative value, the accuracy of the models needs to be verified to ensure measurement quality. The dispersion of low-energy electrons and positrons may be affected by fringe magnetic fields near the entrance of the EPPS. We have calibrated the EPPS with six electron beams from a Siemens Oncor linear accelerator (linac) ranging in energy from 2.7 MeV to 15.2 MeV as they enter the spectrometer. A Geant4 traveling-wave optical parametric amplifier of superfluorescence Monte Carlo simulation was set up to match depth dose curves and lateral profiles measured in water at 100 cm source-surface distance. An accurate relationship was established between the bending magnet current setting and the energy of the electron beam at the exit window. The simulations and measurements were used to determine the energy distributions of the six electron beams at the EPPS slit. Analysis of the scanned image plates together with the determined energy distribution arriving in the spectrometer provides improved dispersion curves for the EPPS.

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

BACKGROUND

Geant4 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.

AIMS

To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.

MATERIALS AND METHODS

G4-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.

RESULTS

This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

DISCUSSION

Our 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.

CONCLUSION

The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

Assessment of DNA damage with an adapted independent reaction time approach implemented in Geant4-DNA for the simulation of diffusion-controlled reactions between radio-induced reactive species and a chromatin fiber

Purpose

Simulation of indirect damage originating from the attack of free radical species produced by ionizing radiation on biological molecules based on the independent pair approximation is investigated in this work. In addition, a new approach, relying on the independent pair approximation that is at the origin of the independent reaction time (IRT) method, is proposed in the chemical stage of Geant4‐DNA.

Methods

This new approach has been designed to respect the current Geant4‐DNA chemistry framework while proposing a variant IRT method. Based on the synchronous algorithm, this implementation allows us to access the information concerning the position of radicals and may make it more convenient for biological damage simulations. Estimates of the evolution of free species as well as biological hits in a segment of DNA chromatin fiber in Geant4‐DNA were compared for the dynamic time step approach of the step‐by‐step (SBS) method, currently used in Geant4‐DNA, and this newly implemented IRT.

Results

Results show a gain in computation time of a factor of 30 for high LET particle tracks with a better than 10% agreement on the number of DNA hits between the value obtained with the IRT method as implemented in this work and the SBS method currently available in Geant4‐DNA.

Conclusion

Offering in Geant4‐DNA more efficient methods for the chemical step based on the IRT method is a task in progress. For the calculation of biological damage, information on the position of chemical species is a crucial point. This can be achieved using the method presented in this paper.

Independent reaction times method in Geant4-DNA: Implementation and performance

PURPOSE

The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy.

METHODS

The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for ^• OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented.

RESULTS

The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, ^• OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for ^• OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities.

CONCLUSION

The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Monte Carlo simulation of the effect of magnetic fields on brachytherapy dose distributions in lung tissue material

The aim of this work was to use TOPAS Monte Carlo simulations to model the effect of magnetic fields on dose distributions in brachytherapy lung treatments, under ideal and clinical conditions. Idealistic studies were modeled consisting of either a monoenergetic electron source of 432 keV, or a polyenergetic electron source using the spectrum of secondary electrons produced by ¹⁹²Ir gamma-ray irradiation. The electron source was positioned in the center of a homogeneous, lung tissue phantom (ρ = 0.26 g/cm³). Conversely, the clinical study was simulated using the VariSource VS2000 ¹⁹²Ir source in a patient with a lung tumor. Three contoured volumes were considered: the tumor, the planning tumor volume (PTV), and the lung. In all studies, dose distributions were calculated in the presence or absence of a constant magnetic field of 3T. Also, TG-43 parameters were calculated for the VariSource and compared with published data from EGS-brachy (EGSnrc) and PENELOPE. The magnetic field affected the dose distributions in the idealistic studies. For the monoenergetic and poly-energetic studies, the radial distance of the 10% iso-dose line was reduced in the presence of the magnetic field by 64.9% and 24.6%, respectively. For the clinical study, the magnetic field caused differences of 10% on average in the patient dose distributions. Nevertheless, differences in dose-volume histograms were below 2%. Finally, for TG-43 parameters, the dose-rate constant from TOPAS differed by 0.09% ± 0.33% and 0.18% ± 0.33% with respect to EGS-brachy and PENELOPE, respectively. The geometry and anisotropy functions differed within 1.2% ± 1.1%, and within 0.0% ± 0.3%, respectively. The Lorentz forces inside a 3T magnetic resonance machine during ¹⁹²Ir brachytherapy treatment of the lung are not large enough to affect the tumor dose distributions significantly, as expected. Nevertheless, large local differences were found in the lung tissue. Applications of this effect are therefore limited by the fact that meaningful differences appeared only in regions containing air, which is not abundant inside the human.

LET-Dependent Intertrack Yields in Proton Irradiation at Ultra-High Dose Rates Relevant for FLASH Therapy

FLASH radiotherapy delivers a high dose (≥10 Gy) at a high rate (≥40 Gy/s). In this way, particles are delivered in pulses as short as a few nanoseconds. At that rate, intertrack reactions between chemical species produced within the same pulse may affect the heterogeneous chemistry stage of water radiolysis. This stochastic process suits the capabilities of the Monte Carlo method, which can model intertrack effects to aid in radiobiology research, including the design and interpretation of experiments. In this work, the TOPAS-nBio Monte Carlo track-structure code was expanded to allow simulations of intertrack effects in the chemical stage of water radiolysis. Simulation of the behavior of radiolytic yields over a long period of time (up to 50 s) was verified by simulating radiolysis in a Fricke dosimeter irradiated by 60Co γ rays. In addition, LET-dependent G values of protons delivered in single squared pulses of widths, 1 ns, 1 µs and 10 µs, were obtained and compared to simulations using no intertrack considerations. The Fricke simulation for the calculated G value of Fe3+ ion at 50 s was within 0.4% of the accepted value from ICRU Report 34. For LET-dependent G values at the end of the chemical stage, intertrack effects were significant at LET values below 2 keV/µm. Above 2 keV/µm the reaction kinetics remained limited locally within each track and thus, effects of intertrack reactions remained low. Therefore, when track structure simulations are used to investigate the biological damage of FLASH irradiation, these intertrack reactions should be considered. The TOPAS-nBio framework with the expansion to intertrack chemistry simulation provides a useful tool to assist in this task.

Monte Carlo track-structure for the radionuclide Copper-64: characterization of S-values, nanodosimetry and quantification of direct damage to DNA

TOPAS-nBio was used to simulate, collision-to-collision, the complete trajectories of electrons in water generated during the explicit simulation of ⁶⁴Cu decay. S-values and direct damage to the DNA were calculated representing the cell (C) and the cell nucleus (N) with concentric spheres of 5 μm and 4 μm in radius, respectively. The considered 'target'←'source' configurations, including the cell surface (Cs) and cytoplasm (Cy), were: C←C, C←Cs, N←N, N←Cy and N←Cs. Ionization cluster size distributions were also calculated in a cylinder immersed in water corresponding to a DNA segment of 10 base-pairs in length (diameter 2.3 nm, length 3.4 nm), modeling a radioactive point source moving from the central axis to the edge of the cylinder. For that, the first moment (M₁) and cumulative probability of having a cluster size of 2 or more ionizations in the cylindrical volume (F₂) were obtained. Finally, the direct damage to the DNA was estimated by quantifying double-strand breaks (DSBs) using the clustering algorithm DBSCAN. The S-values obtained with TOPAS-nBio for ⁶⁴Cu were 7.879 × 10^-4 ± 5 × 10^-7, 4.351 × 10^-4 ± 6 × 10^-7, 1.442 × 10^-3 ± 1 × 10^-6, 2.596 × 10^-4 ± 8 × 10^-7, 1.127 × 10^-4 ± 4 × 10^-7 Gy Bq-s^-1 for the configurations C←C, C←Cs, N←N, N←Cy and N←Cs, respectively. The difference of these values, compared with previously reported S-values for ⁶⁴Cu with the code MNCP and software MIRDCell, ranged from -4% to -25% for the configurations N←N and N←Cs, respectively. On the other hand, F₂ was maximum with the source at the center of the cylinder 0.373 ± 0.001, and monotonically decreased until reaching a value of 0.058 ± 0.001 at 2.3 nm. The same behavior was observed for M₁ with values ranging from 2.188 ± 0.004 to 0.242 ± 0.002. Finally, the DBSCAN algorithm showed that the mean number of DNA DSBs per decay were 0.187 ± 0.001, 0.0317 ± 0.0005, and 0.0125 ± 0.0002 DSB-(Bq-s)^-1 for the configurations N←N, N←Cs, and N←Cy, respectively. In conclusion, the results of the S-values show that the absorbed dose strongly depends on the distribution of the radionuclide in the cell, the dose being higher when ⁶⁴Cu is internalized in the cell nucleus, which is reinforced by the nanodosimetric study by the presence of DNA DSBs attributable to the Auger electrons emitted during the decay of ⁶⁴Cu.

The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research

PURPOSE

This paper covers recent developments and applications of the TOPAS TOol for PArticle Simulation and presents the approaches used to disseminate TOPAS.

MATERIALS AND METHODS

Fundamental understanding of radiotherapy and imaging is greatly facilitated through accurate and detailed simulation of the passage of ionizing radiation through apparatus and into a patient using Monte Carlo (MC). TOPAS brings Geant4, a reliable, experimentally validated MC tool mainly developed for high energy physics, within easy reach of medical physicists, radiobiologists and clinicians. Requiring no programming knowledge, TOPAS provides all of the flexibility of Geant4.

RESULTS

After 5 years of development followed by its initial release, TOPAS was subsequently expanded from its focus on proton therapy physics to incorporate radiobiology modeling. Next, in 2018, the developers expanded their user support and code maintenance as well as the scope of TOPAS towards supporting X-ray and electron therapy and medical imaging. Improvements have been achieved in user enhancement through software engineering and a graphical user interface, calculational efficiency, validation through experimental benchmarks and QA measurements, and either newly available or recently published applications. A large and rapidly increasing user base demonstrates success in our approach to dissemination of this uniquely accessible and flexible MC research tool.

CONCLUSIONS

The TOPAS developers continue to make strides in addressing the needs of the medical community in applications of ionizing radiation to medicine, creating the only fully integrated platform for four-dimensional simulation of all forms of radiotherapy and imaging with ionizing radiation, with a design that promotes inter-institutional collaboration.

Simultaneous optimization of RBE-weighted dose and nanometric ionization distributions in treatment planning with carbon ions

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon-ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon-ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon-ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology

The TOPAS Monte Carlo (MC) system is used in radiation therapy and medical imaging research, having played a significant role in making Monte Carlo simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. Thus, our goal was to develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub-cellular) scale. TOPAS-nBio was designed as a set of open source classes that extends TOPAS to model radiobiological experiments. TOPAS-nBio is based on and extends Geant4-DNA, which extends the Geant4 toolkit, the basis of TOPAS, to include very low-energy interactions of particles down to vibrational energies, explicitly simulates every particle interaction (i.e., without using condensed histories) and propagates radiolysis products. To further facilitate the use of TOPAS-nBio, a graphical user interface was developed. TOPAS-nBio offers full track-structure Monte Carlo simulations, integration of chemical reactions within the first millisecond, an extensive catalogue of specialized cell geometries as well as sub-cellular structures such as DNA and mitochondria, and interfaces to mechanistic models of DNA repair kinetics. We compared TOPAS-nBio simulations to measured and published data of energy deposition patterns and chemical reaction rates (G values). Our simulations agreed well within the experimental uncertainties. Additionally, we expanded the chemical reactions and species provided in Geant4-DNA and developed a new method based on independent reaction times (IRT), including a total of 72 reactions classified into 6 types between neutral and charged species. Chemical stage simulations using IRT were a factor of 145 faster than with step-by-step tracking. Finally, we applied the geometric/chemical modeling to obtain initial yields of double-strand breaks (DSBs) in DNA fibers for proton irradiations of 3 and 50 MeV and compared the effect of including chemical reactions on the number and complexity of DSB induction. Over half of the DSBs were found to include chemical reactions with approximately 5% of DSBs caused only by chemical reactions. In conclusion, the TOPAS-nBio extension to the TOPAS MC application offers access to accurate and detailed multiscale simulations, from a macroscopic description of the radiation field to microscopic description of biological outcome for selected cells. TOPAS-nBio offers detailed physics and chemistry simulations of radiobiological experiments on cells simulating the initially induced damage and links to models of DNA repair kinetics.

Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit

Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. The modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Here we present the geometries available in TOPAS-nBio.

Monte Carlo simulation of chemistry following radiolysis with TOPAS-nBio

Simulation of water radiolysis and the subsequent chemistry provides important information on the effect of ionizing radiation on biological material. The Geant4 Monte Carlo toolkit has added chemical processes via the Geant4-DNA project. The TOPAS tool simplifies the modeling of complex radiotherapy applications with Geant4 without requiring advanced computational skills, extending the pool of users. Thus, a new extension to TOPAS, TOPAS-nBio, is under development to facilitate the configuration of track-structure simulations as well as water radiolysis simulations with Geant4-DNA for radiobiological studies. In this work, radiolysis simulations were implemented in TOPAS-nBio. Users may now easily add chemical species and their reactions, and set parameters including branching ratios, dissociation schemes, diffusion coefficients, and reaction rates. In addition, parameters for the chemical stage were re-evaluated and updated from those used by default in Geant4-DNA to improve the accuracy of chemical yields. Simulation results of time-dependent and LET-dependent primary yields Gx (chemical species per 100 eV deposited) produced at neutral pH and 25 °C by short track-segments of charged particles were compared to published measurements. The LET range was 0.05-230 keV µm-1. The calculated Gx values for electrons satisfied the material balance equation within 0.3%, similar for protons albeit with long calculation time. A smaller geometry was used to speed up proton and alpha simulations, with an acceptable difference in the balance equation of 1.3%. Available experimental data of time-dependent G-values for [Formula: see text] agreed with simulated results within 7%  ±  8% over the entire time range; for [Formula: see text] over the full time range within 3%  ±  4%; for H2O2 from 49%  ±  7% at earliest stages and 3%  ±  12% at saturation. For the LET-dependent Gx, the mean ratios to the experimental data were 1.11  ±  0.98, 1.21  ±  1.11, 1.05  ±  0.52, 1.23  ±  0.59 and 1.49  ±  0.63 (1 standard deviation) for [Formula: see text], [Formula: see text], H2, H2O2 and [Formula: see text], respectively. In conclusion, radiolysis and subsequent chemistry with Geant4-DNA has been successfully incorporated in TOPAS-nBio. Results are in reasonable agreement with published measured and simulated data.

Flagged uniform particle splitting for variance reduction in proton and carbon ion track-structure simulations

Flagged uniform particle splitting was implemented with two methods to improve the computational efficiency of Monte Carlo track structure simulations with TOPAS-nBio by enhancing the production of secondary electrons in ionization events. In method 1 the Geant4 kernel was modified. In method 2 Geant4 was not modified. In both methods a unique flag number assigned to each new split electron was inherited by its progeny, permitting reclassification of the split events as if produced by independent histories. Computational efficiency and accuracy were evaluated for simulations of 0.5-20 MeV protons and 1-20 MeV u^-1 carbon ions for three endpoints: (1) mean of the ionization cluster size distribution, (2) mean number of DNA single-strand breaks (SSBs) and double-strand breaks (DSBs) classified with DBSCAN, and (3) mean number of SSBs and DSBs classified with a geometry-based algorithm. For endpoint (1), simulation efficiency was 3 times lower when splitting electrons generated by direct ionization events of primary particles than when splitting electrons generated by the first ionization events of secondary electrons. The latter technique was selected for further investigation. The following results are for method 2, with relative efficiencies about 4.5 times lower for method 1. For endpoint (1), relative efficiency at 128 split electrons approached maximum, increasing with energy from 47.2  ±  0.2 to 66.9  ±  0.2 for protons, decreasing with energy from 51.3  ±  0.4 to 41.7  ±  0.2 for carbon. For endpoint (2), relative efficiency increased with energy, from 20.7  ±  0.1 to 50.2  ±  0.3 for protons, 15.6  ±  0.1 to 20.2  ±  0.1 for carbon. For endpoint (3) relative efficiency increased with energy, from 31.0  ±  0.2 to 58.2  ±  0.4 for protons, 23.9  ±  0.1 to 26.2  ±  0.2 for carbon. Simulation results with and without splitting agreed within 1% (2 standard deviations) for endpoints (1) and (2), within 2% (1 standard deviation) for endpoint (3). In conclusion, standard particle splitting variance reduction techniques can be successfully implemented in Monte Carlo track structure codes.

The effect of beam purity and scanner complexity on proton CT accuracy

PURPOSE

To determine the dependence of the accuracy in reconstruction of relative stopping power (RSP) with proton computerized tomography (pCT) scans on the purity of the proton beam and the technological complexity of the pCT scanner using standard phantoms and a digital representation of a pediatric patient.

METHODS

The Monte Carlo method was applied to simulate the pCT scanner, using both a pure proton beam (uniform 200 MeV mono-energetic, parallel beam) and the Northwestern Medicine Chicago Proton Center (NMCPC) clinical beam in uniform scanning mode. The accuracy of the simulation was validated with measurements performed at NMCPC including reconstructed RSP images obtained with a preclinical prototype pCT scanner. The pCT scanner energy detector was then simulated in three configurations of increasing complexity: an ideal totally absorbing detector, a single stage detector and a multi-stage detector. A set of 15 cm diameter water cylinders containing either water alone or inserts of different material, size, and position were simulated at 90 projection angles (4° steps) for the pure and clinical proton beams and the three pCT configurations. A pCT image of the head of a detailed digital pediatric phantom was also reconstructed from the simulated pCT scan with the prototype detector.

RESULTS

The RSP error increased for all configurations for insert sizes under 7.5 mm in radius, with a sharp increase below 5 mm in radius, attributed to a limit in spatial resolution. The highest accuracy achievable using the current pCT calibration step phantom and reconstruction algorithm, calculated for the ideal case of a pure beam with totally absorbing energy detector, was 1.3% error in RSP for inserts of 5 mm radius or more, 0.7 mm in range for the 2.5 mm radius inserts, or better. When the highest complexity of the scanner geometry was introduced, some artifacts arose in the reconstructed images, particularly in the center of the phantom. Replacing the step phantom used for calibration with a wedge phantom led to RSP accuracy close to the ideal case, with no significant dependence of RSP error on insert location or material. The accuracy with the multi-stage detector and NMCPC beam for the cylindrical phantoms was 2.2% in RSP error for inserts of 5 mm radius or more, 0.7 mm in range for the 2.5 mm radius inserts, or better. The pCT scan of the pediatric phantom resulted in mean RSP values within 1.3% of the reference RSP, with a range error under 1 mm, except in exceptional situations of parallel incidence on a boundary between low and high density.

CONCLUSIONS

The pCT imaging technique proved to be a precise and accurate imaging tool, rivaling the current x-rays based techniques, with the advantage of being directly sensitive to proton stopping power rather than photon interaction coefficients. Measured and simulated pCT images were obtained from a wobbled proton beam for the first time. Since the in-silico results are expected to accurately represent the prototype pCT, upcoming measurements using the wedge phantom for calibration are expected to show similar accuracy in the reconstructed RSP.

Experimental depth dose curves of a 67.5 MeV proton beam for benchmarking and validation of Monte Carlo simulation

PURPOSE

To measure depth dose curves for a 67.5 ± 0.1 MeV proton beam for benchmarking and validation of Monte Carlo simulation.

METHODS

Depth dose curves were measured in 2 beam lines. Protons in the raw beam line traversed a Ta scattering foil, 0.1016 or 0.381 mm thick, a secondary emission monitor comprised of thin Al foils, and a thin Kapton exit window. The beam energy and peak width and the composition and density of material traversed by the beam were known with sufficient accuracy to permit benchmark quality measurements. Diodes for charged particle dosimetry from two different manufacturers were used to scan the depth dose curves with 0.003 mm depth reproducibility in a water tank placed 300 mm from the exit window. Depth in water was determined with an uncertainty of 0.15 mm, including the uncertainty in the water equivalent depth of the sensitive volume of the detector. Parallel-plate chambers were used to verify the accuracy of the shape of the Bragg peak and the peak-to-plateau ratio measured with the diodes. The uncertainty in the measured peak-to-plateau ratio was 4%. Depth dose curves were also measured with a diode for a Bragg curve and treatment beam spread out Bragg peak (SOBP) on the beam line used for eye treatment. The measurements were compared to Monte Carlo simulation done with geant4 using topas.

RESULTS

The 80% dose at the distal side of the Bragg peak for the thinner foil was at 37.47 ± 0.11 mm (average of measurement with diodes from two different manufacturers), compared to the simulated value of 37.20 mm. The 80% dose for the thicker foil was at 35.08 ± 0.15 mm, compared to the simulated value of 34.90 mm. The measured peak-to-plateau ratio was within one standard deviation experimental uncertainty of the simulated result for the thinnest foil and two standard deviations for the thickest foil. It was necessary to include the collimation in the simulation, which had a more pronounced effect on the peak-to-plateau ratio for the thicker foil. The treatment beam, being unfocussed, had a broader Bragg peak than the raw beam. A 1.3 ± 0.1 MeV FWHM peak width in the energy distribution was used in the simulation to match the Bragg peak width. An additional 1.3-2.24 mm of water in the water column was required over the nominal values to match the measured depth penetration.

CONCLUSIONS

The proton Bragg curve measured for the 0.1016 mm thick Ta foil provided the most accurate benchmark, having a low contribution of proton scatter from upstream of the water tank. The accuracy was 0.15% in measured beam energy and 0.3% in measured depth penetration at the Bragg peak. The depth of the distal edge of the Bragg peak in the simulation fell short of measurement, suggesting that the mean ionization potential of water is 2-5 eV higher than the 78 eV used in the stopping power calculation for the simulation. The eye treatment beam line depth dose curves provide validation of Monte Carlo simulation of a Bragg curve and SOBP with 4%/2 mm accuracy.

A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy

The aim of this work was to develop a framework for modeling organ effects within TOPAS (TOol for PArticle Simulation), a wrapper of the Geant4 Monte Carlo toolkit that facilitates particle therapy simulation. The DICOM interface for TOPAS was extended to permit contour input, used to assign voxels to organs. The following dose response models were implemented: The Lyman-Kutcher-Burman model, the critical element model, the population based critical volume model, the parallel-serial model, a sigmoid-based model of Niemierko for normal tissue complication probability and tumor control probability (TCP), and a Poisson-based model for TCP. The framework allows easy manipulation of the parameters of these models and the implementation of other models. As part of the verification, results for the parallel-serial and Poisson model for x-ray irradiation of a water phantom were compared to data from the AAPM Task Group 166. When using the task group dose-volume histograms (DVHs), results were found to be sensitive to the number of points in the DVH, with differences up to 2.4%, some of which are attributable to differences between the implemented models. New results are given with the point spacing specified. When using Monte Carlo calculations with TOPAS, despite the relatively good match to the published DVH's, differences up to 9% were found for the parallel-serial model (for a maximum DVH difference of 2%) and up to 0.5% for the Poisson model (for a maximum DVH difference of 0.5%). However, differences of 74.5% (in Rectangle1), 34.8% (in PTV) and 52.1% (in Triangle) for the critical element, critical volume and the sigmoid-based models were found respectively. We propose a new benchmark for verification of organ effect models in proton therapy. The benchmark consists of customized structures in the spread out Bragg peak plateau, normal tissue, tumor, penumbra and in the distal region. The DVH's, DVH point spacing, and results of the organ effect models are provided. The models were used to calculate dose response for a Head and Neck patient to demonstrate functionality of the new framework and indicate the degree of variability between the models in proton therapy.

Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy

PURPOSE

To present the implementation and validation of a geometrical based variance reduction technique for the calculation of phase space data for proton therapy dose calculation.

METHODS

The treatment heads at the Francis H Burr Proton Therapy Center were modeled with a new Monte Carlo tool (TOPAS based on Geant4). For variance reduction purposes, two particle-splitting planes were implemented. First, the particles were split upstream of the second scatterer or at the second ionization chamber. Then, particles reaching another plane immediately upstream of the field specific aperture were split again. In each case, particles were split by a factor of 8. At the second ionization chamber and at the latter plane, the cylindrical symmetry of the proton beam was exploited to position the split particles at randomly spaced locations rotated around the beam axis. Phase space data in IAEA format were recorded at the treatment head exit and the computational efficiency was calculated. Depth-dose curves and beam profiles were analyzed. Dose distributions were compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. In addition, dose in two patients was simulated with and without particle splitting to compare the efficiency and accuracy of the technique.

RESULTS

A normalized computational efficiency gain of a factor of 10-20.3 was reached for phase space calculations for the different treatment head options simulated. Depth-dose curves and beam profiles were in reasonable agreement with the simulation done without splitting: within 1% for depth-dose with an average difference of (0.2 ± 0.4)%, 1 standard deviation, and a 0.3% statistical uncertainty of the simulations in the high dose region; 1.6% for planar fluence with an average difference of (0.4 ± 0.5)% and a statistical uncertainty of 0.3% in the high fluence region. The percentage differences between dose distributions in water for simulations done with and without particle splitting were within the accepted clinical tolerance of 2%, with a 0.4% statistical uncertainty. For the two patient geometries considered, head and prostate, the efficiency gain was 20.9 and 14.7, respectively, with the percentages of voxels with gamma indices lower than unity 98.9% and 99.7%, respectively, using 2% and 2 mm criteria.

CONCLUSIONS

The authors have implemented an efficient variance reduction technique with significant speed improvements for proton Monte Carlo simulations. The method can be transferred to other codes and other treatment heads.