TOPAS simulation of photoneutrons in radiotherapy: accuracy and speed with variance reduction.

Objective. We provide optimal particle split numbers for speeding up TOPAS Monte Carlo simulations of linear accelerator (linac) treatment heads while maintaining accuracy. In addition, we provide a new TOPAS physics module for simulating photoneutron production and transport.Approach.TOPAS simulation of a Siemens Oncor linac was used to determine the optimal number of splits for directional bremsstrahlung splitting as a function of the field size for 6 MV and 18 MV x-ray beams. The linac simulation was validated against published data of lateral dose profiles and percentage depth-dose curves (PDD) for the largest square field (40 cm side). In separate simulations, neutron particle split and the custom TOPAS physics module was used to generate and transport photoneutrons, called 'TsPhotoNeutron'. Verification of accuracy was performed by comparing simulations with published measurements of: (1) neutron yields as a function of beam energy for thick targets of Al, Cu, Ta, W, Pb and concrete; and (2) photoneutron energy spectrum at 40 cm laterally from the isocenter of the Oncor linac from an 18 MV beam with closed jaws and MLC.Main results.The optimal number of splits obtained for directional bremsstrahlung splitting enhanced the computational efficiency by two orders of magnitude. The efficiency decreased with increasing beam energy and field size. Calculated lateral profiles in the central region agreed within 1 mm/2% from measured data, PDD curves within 1 mm/1%. For the TOPAS physics module, at a split number of 146, the efficiency of computing photoneutron yields was enhanced by a factor of 27.6, whereas it improved the accuracy over existing Geant4 physics modules.Significance.This work provides simulation parameters and a new TOPAS physics module to improve the efficiency and accuracy of TOPAS simulations that involve photonuclear processes occurring in high-Zmaterials found in linac components, patient devices, and treatment rooms, as well as to explore new therapeutic modalities such as very-high energy electron therapy.

Increased flexibility and efficiency of a double-scattering FLASH proton beamline configuration forin vivoSOBP radiotherapy treatments.

Objective. To commission a proton, double-scattering FLASH beamline by maximizing efficiency and field size, enabling higher-linear energy transfer FLASH radiotherapy to cells and small animals using a spread-out Bragg peak (SOBP) treatment configuration. We further aim to provide a configuration guide for the design of future FLASH proton double-scattering (DS) beamlines.Approach. Beam spot size and spread were measured with film and implemented into TOol for PArticle Simulation (TOPAS). Monte Carlo simulations were optimized to verify the ideal positioning, dimensions, and material of scattering foils, secondary scatterers, ridge filters, range compensators, and apertures. A ridge filter with three discrete heights was used to create a spread-out Bragg peak (SOBP) and was experimentally verified using our in-house experimental FLASH beamline. The increase in dose rate was compared to nominal shoot-through techniques.Results. The configuration and scatterer distance producing the largest field size of acceptable flatness, without drastically compromising dose rate was determined to be an elliptical field of 2 cm × 1.5 cm (25% larger than a previous configuration). SOBP testing yielded three distinct but connected spikes in dose with flatness under 5%. Reducing the thickness of the (first) scattering foil by a factor of two was found to increase efficiency by 50%. The new settings increased the field size, provided a Bragg peak treatment option, and increased the maximum available dose rate by 85%, as compared to the previous, shoot through method.Significance. Beam line updates established FLASH dose rates of over 135 Gy s-1(potentially higher) at our double-scattering beamline, increased the efficiency and field size, and enabled SOBP treatments by incorporating an optimized ridge filter. Based on our simulations we provide parametric suggestions when commissioning a new proton DS beamline. This enhanced FLASH beamline for SOBP irradiations with higher dose rates and larger field sizes will enable a wider variety of experimentation in future studies.

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.

Intercomparison of Monte Carlo calculated dose enhancement ratios for gold nanoparticles irradiated by X-rays: Assessing the uncertainty and correct methodology for extended beams.

Results of a Monte Carlo code intercomparison exercise for simulations of the dose enhancement from a gold nanoparticle (GNP) irradiated by X-rays have been recently reported. To highlight potential differences between codes, the dose enhancement ratios (DERs) were shown for the narrow-beam geometry used in the simulations, which leads to values significantly higher than unity over distances in the order of several tens of micrometers from the GNP surface. As it has come to our attention that the figures in our paper have given rise to misinterpretation as showing 'the' DERs of GNPs under diagnostic X-ray irradiation, this article presents estimates of the DERs that would have been obtained with realistic radiation field extensions and presence of secondary particle equilibrium (SPE). These DER values are much smaller than those for a narrow-beam irradiation shown in our paper, and significant dose enhancement is only found within a few hundred nanometers around the GNP. The approach used to obtain these estimates required the development of a methodology to identify and, where possible, correct results from simulations whose implementation deviated from the initial exercise definition. Based on this methodology, literature on Monte Carlo simulated DERs has been critically assessed.

Consistency checks of results from a Monte Carlo code intercomparison for emitted electron spectra and energy deposition around a single gold nanoparticle irradiated by X-rays.

Organized by the European Radiation Dosimetry Group (EURADOS), a Monte Carlo code intercomparison exercise was conducted where participants simulated the emitted electron spectra and energy deposition around a single gold nanoparticle (GNP) irradiated by X-rays. In the exercise, the participants scored energy imparted in concentric spherical shells around a spherical volume filled with gold or water as well as the spectral distribution of electrons leaving the GNP. Initially, only the ratio of energy deposition with and without GNP was to be reported. During the evaluation of the exercise, however, the data for energy deposition in the presence and absence of the GNP were also requested. A GNP size of 50 nm and 100 nm diameter was considered as well as two different X-ray spectra (50 kVp and 100kVp). This introduced a redundancy that can be used to cross-validate the internal consistency of the simulation results. In this work, evaluation of the reported results is presented in terms of integral quantities that can be benchmarked against values obtained from physical properties of the radiation spectra and materials involved. The impact of different interaction cross-section datasets and their implementation in the different Monte Carlo codes is also discussed.

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.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes.

PURPOSE: Targeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively. METHODS: In this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework. RESULTS: The mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3. CONCLUSIONS: It is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.

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.

A New Standard DNA Damage (SDD) Data Format.

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

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.

Comparing stochastic proton interactions simulated using TOPAS-nBio to experimental data from fluorescent nuclear track detectors.

Whilst Monte Carlo (MC) simulations of proton energy deposition have been well-validated at the macroscopic level, their microscopic validation remains lacking. Equally, no gold-standard yet exists for experimental metrology of individual proton tracks. In this work we compare the distributions of stochastic proton interactions simulated using the TOPAS-nBio MC platform against confocal microscope data for Al2O3:C,Mg fluorescent nuclear track detectors (FNTDs). We irradiated [Formula: see text] mm3 FNTD chips inside a water phantom, positioned at seven positions along a pristine proton Bragg peak with a range in water of 12 cm. MC simulations were implemented in two stages: (1) using TOPAS to model the beam properties within a water phantom and (2) using TOPAS-nBio with Geant4-DNA physics to score particle interactions through a water surrogate of Al2O3:C,Mg. The measured median track integrated brightness (IB) was observed to be strongly correlated to both (i) voxelized track-averaged linear energy transfer (LET) and (ii) frequency mean microdosimetric lineal energy, [Formula: see text], both simulated in pure water. Histograms of FNTD track IB were compared against TOPAS-nBio histograms of the number of terminal electrons per proton, scored in water with mass-density scaled to mimic Al2O3:C,Mg. Trends between exposure depths observed in TOPAS-nBio simulations were experimentally replicated in the study of FNTD track IB. Our results represent an important first step towards the experimental validation of MC simulations on the sub-cellular scale and suggest that FNTDs can enable experimental study of the microdosimetric properties of individual proton tracks.

Dose enhancement effects to the nucleus and mitochondria from gold nanoparticles in the cytosol.

Gold nanoparticles (GNPs) have shown potential as dose enhancers for radiation therapy. Since damage to the genome affects the viability of a cell, it is generally assumed that GNPs have to localise within the cell nucleus. In practice, however, GNPs tend to localise in the cytoplasm yet still appear to have a dose enhancing effect on the cell. Whether this effect can be attributed to stress-induced biological mechanisms or to physical damage to extra-nuclear cellular targets is still unclear. There is however growing evidence to suggest that the cellular response to radiation can also be influenced by indirect processes induced when the nucleus is not directly targeted by radiation. The mitochondrion in particular may be an effective extra-nuclear radiation target given its many important functional roles in the cell. To more accurately predict the physical effect of radiation within different cell organelles, we measured the full chemical composition of a whole human lymphocytic JURKAT cell as well as two separate organelles; the cell nucleus and the mitochondrion. The experimental measurements found that all three biological materials had similar ionisation energies ∼70 eV, substantially lower than that of liquid water ∼78 eV. Monte Carlo simulations for 10-50 keV incident photons showed higher energy deposition and ionisation numbers in the cell and organelle materials compared to liquid water. Adding a 1% mass fraction of gold to each material increased the energy deposition by a factor of ∼1.8 when averaged over all incident photon energies. Simulations of a realistic compartmentalised cell show that the presence of gold in the cytosol increases the energy deposition in the mitochondrial volume more than within the nuclear volume. We find this is due to sub-micron delocalisation of energy by photoelectrons, making the mitochondria a potentially viable indirect radiation target for GNPs that localise to the cytosol.

Dosimetric feasibility of real-time MRI-guided proton therapy.

PURPOSE: Magnetic resonance imaging (MRI) is a prime candidate for image-guided radiotherapy. This study was designed to assess the feasibility of real-time MRI-guided proton therapy by quantifying the dosimetric effects induced by the magnetic field in patients' plans and identifying the associated clinical consequences. METHODS: Monte Carlo dose calculation was performed for nine patients of various treatment sites (lung, liver, prostate, brain, skull-base, and spine) and tissue homogeneities, in the presence of 0.5 and 1.5 T magnetic fields. Dose volume histogram (DVH) parameters such as D95, D5, and V20 as well as equivalent uniform dose were compared for the target and organs at risk, before and after applying the magnetic field. The authors further assessed whether the plans affected by clinically relevant dose distortions could be corrected independent of the planning system. RESULTS: By comparing the resulting dose distributions and analyzing the respective DVHs, it was determined that despite the observed lateral beam deflection, for magnetic fields of up to 0.5 T, neither was the target coverage jeopardized nor was the dose to the nearby organs increased in all cases except for prostate. However, for a 1.5 T magnetic field, the dose distortions were more pronounced and of clinical concern in all cases except for spine. In such circumstances, the target was severely underdosed, as indicated by a decrease in D95 of up to 41% of the prescribed dose compared to the nominal situation (no magnetic field). Sites such as liver and spine were less affected due to higher tissue homogeneity, typically smaller beam range, and the choice of beam directions. Simulations revealed that small modifications to certain plan parameters such as beam isocenter (up to 19 mm) and gantry angle (up to 10°) are sufficient to compensate for the magnetic field-induced dose disturbances. The authors' observations indicate that the degree of required corrections strongly depends on the beam range and direction relative to the magnetic field. This method was also applicable to more heterogeneous scenarios such as skull-base tumors. CONCLUSIONS: This study confirmed the dosimetric feasibility of real-time MRI-guided proton therapy and delivering a clinically acceptable dose to patients with various tumor locations within magnetic fields of up to 1.5 T. This work could serve as a guide and encouragement for further efforts toward clinical implementation of hybrid MRI-proton gantry systems.

Site-specific range uncertainties caused by dose calculation algorithms for proton therapy.

The purpose of this study was to assess the possibility of introducing site-specific range margins to replace current generic margins in proton therapy. Further, the goal was to study the potential of reducing margins with current analytical dose calculations methods. For this purpose we investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo (MC) simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for seven disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head and neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and MC algorithms to obtain the average range differences and root mean square deviation for each field for the distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing MC dose calculations. We recommend range margins of 2.8% + 1.2 mm for liver and prostate treatments and 3.1% + 1.2 mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head and neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3% + 1.2 mm would be needed for breast, lung and head and neck treatments. We conclude that the currently used generic range uncertainty margins in proton therapy should be redefined site specific and that complex geometries may require a field specific adjustment. Routine verifications of treatment plans using MC simulations are recommended for patients with heterogeneous geometries.

An algorithm to assess the need for clinical Monte Carlo dose calculation for small proton therapy fields based on quantification of tissue heterogeneity.

PURPOSE: In proton therapy, complex density heterogeneities within the beam path constitute a challenge to dose calculation algorithms. This might question the reliability of dose distributions predicted by treatment planning systems based on analytical dose calculation. For cases in which substantial dose errors are expected, resorting to Monte Carlo dose calculations might be essential to ensure a successful treatment outcome and therefore the benefit is worth a presumably long computation time. The aim of this study was to define an indicator for the accuracy of dose delivery based on analytical dose calculations in treatment planning systems for small proton therapy fields to identify those patients for which Monte Carlo dose calculation is warranted. METHODS: Fourteen patients treated at our facility with small passively scattered proton beams (apertures diameters below 7 cm) were selected. Plans were generated in the XiO treatment planning system in combination with a pencil beam algorithm developed at the Massachusetts General Hospital and compared to Monte Carlo dose calculations. Differences in the dose to the 50% of the gross tumor volume (D50, GTV) were assessed in a field-by-field basis. A simple and fast methodology was developed to quantify the inhomogeneity of the tissue traversed by a single small proton beam using a heterogeneity index (HI)-a concept presented by Plugfelder et al. [Med. Phys. 34, 1506-1513 (2007)] for scanned proton beams. Finally, the potential correlation between the error made by the pencil beam based treatment planning algorithm for each field and the level of tissue heterogeneity traversed by the proton beam given by the HI was evaluated. RESULTS: Discrepancies up to 5.4% were found in D50 for single fields, although dose differences were within clinical tolerance levels (<3%) when combining all of the fields involved in the treatment. The discrepancies found for each field exhibited a strong correlation to their associated HI-values (Spearman's ρ=0.8, p<0.0001); the higher the level of tissue inhomogeneities for a particular field, the larger the error by the analytical algorithm. With the established correlation a threshold for HI can be set by choosing a tolerance level of 2-3%-commonly accepted in radiotherapy. CONCLUSIONS: The HI is a good indicator for the accuracy of proton field delivery in terms of GTV prescription dose coverage when small fields are delivered. Each HI-value was obtained from the CT image in less than 3 min on a computer with 2 GHz CPU allowing implementation of this methodology in clinical routine. For HI-values exceeding the threshold, either a change in beam direction (if feasible) or a recalculation of the dose with Monte Carlo would be highly recommended.

SU-E-T-473: Performance Assessment of the TOPAS Tool for Particle Simulation for Proton Therapy Applications.

PURPOSE: The TOPAS Tool for Particle Simulation was developed to make Geant4 Monte Carlo simulation more readily available for research and clinical physicists. Before releasing this new tool to the proton therapy community, several test have been performed to ensure accurate simulations in a variety of proton therapy setups. METHODS: TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on CT images, score dose, fluence, etc., save and replay a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. An innovative control system meets requirements for ease of use, reliability and repeatability without sacrificing flexibility. To test the TOPAS code, we modeled proton therapy treatment examples including the UCSF eye treatment beamline (UCSFETB), the MGH STAR radiosurgery beamline and the MGH gantry treatment head in passive scattering and scanning modes. The simulations included time-dependent geometry and time- dependent beam current delivery. RESULTS: At the UCSFETB, time- dependent depth dose distributions were accurately simulated with time- varying energy modulation from a rotating propeller. At the MGH STAR beamline, distal and proximal ranges agreed within measurement uncertainty and the shape of the simulated SOBP followed measured data. For the MGH gantry treatment head in passive scattering mode, SOBPs were simulated for the full set of range modulator wheel and second scatterer combinations. TOPAS simulation was within clinical required accuracy. For the MGH nozzle in scanning mode, a variety of scan patterns were simulated with fluence maps generated for cases including beam current modulation, energy modulation and target tracking. CONCLUSIONS: Our results demonstrate the functionality of TOPAS. They show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D. This work was supported by IH/NCI under R01 CA 140735-01.

SU-E-T-470: Comparison of Proton Treatment Planning and Monte Carlo Calculation Using TOPAS for Liver Cancer.

PURPOSE: To compare Monte Carlo (MC) calculated and planned dose distributions (pencil beam algorithm) for patients with liver cancer treated with proton radiation therapy. METHODS: Six patients with unresectable Hepatocellular carcinoma were chosen from the institutional protocol list. We applied the newly developed TOPAS (Tool for Particle Simulation) Monte Carlo (MC) tool and an in-house (mcauto) program, which connects the planning system with the MC. Two beams, typically right lateral (RL) and anterior-posterior (AP), were simulated for each patient with a total prescribed dose of 58 Gy. The calculated absolute dose was determined by separately simulating an SOBP dose in a water phantom for normalization to the prescription dose. The difference between MC and planned dose were calculated and Dose Volume Histograms (DVHs) for the critical organs with non-negligible dose (whole liver, heart, small and large bowel and chest wall) were analyzed. RESULTS: The resulting dose distributions were in quite good agreement. The main discrepancy in all cases was observed in the lateral penumbrae. These discrepancies can mainly result from the range compensator gradient and tissue composition. The Dose Volume Histograms (DVHs) also presented good agreement between doses for the CTV as well as all the OARs. The difference in D95 ranged from 0.7-1.5 Gy that is translated to 1.3-2.5% of the prescribed dose. CONCLUSIONS: TOPAS Monte Carlo tool presented an efficient and accurate method for dose calculation in liver and to validate clinical treatment planning. Discrepancies with doses calculated using the pencil beam algorithm were seen but were generally quite small.

SU-E-T-475: Nano-Dosimetric Track Structure Scoring including Biological Modeling with TOPAS-NBio.

PURPOSE: To develop a nano-dosimetric Monte Carlo simulation package, TOPAS-nBio, based on the TOPAS (TOol for PArticle Simulations) framework that is being developed in a collaboration between the Massachusetts General Hospital (MGH), the SLAC National Accelerator Laboratory and the University of California, San Francisco. The goal is to incorporate biological processes on a sub-cell level that will provide the basis for a wide range of research in the field of radiobiology, such as bystander effects, biological dose calculations and effects of nano-particles on radiation therapy. METHODS: The TOPAS framework has been utilized to extend the functionality of this tool for particle transport to include nano- dosimetry. The physics lists of TOPAS have been extended to include efforts by the Geant4-DNA group to model physics on nanometer scales, including chemical processes of the first millisecond after irradiation. TOPAS-nBio uses the functionality of TOPAS to score energy depositions on nanometer scales. A simulation of the setup of a cell culture irradiation experiment has been used as to test the feasibility of the project. RESULTS: Track structures for an irradiation of a cell culture experiment were successfully obtained. Delta-electron distributions have been produced and single track delta electrons and their energy depositions were observed. CONCLUSIONS: This study is a first step in the development of TOPAS-nBio, a tool that aims at bringing nanometer scale radiation physics and biology together and make Monte Carlo simulations accessible for all radiobiology researchers. The results presented here show a first proof of concept for the development of TOPAS-nBio.