Experimental validation of the TOPAS Monte Carlo system for passive scattering proton therapy

High-Density Glass Scintillators for Proton Radiography-Relative Luminosity, Proton Response, and Spatial Resolution

Proton radiography is a promising development in proton therapy, and researchers are currently exploring optimal detector materials to construct proton radiography detector arrays. High-density glass scintillators may improve integrating-mode proton radiography detectors by increasing spatial resolution and decreasing detector thickness. We evaluated several new scintillators, activated with europium or terbium, with proton response measurements and Monte Carlo simulations, characterizing relative luminosity, ionization quenching, and proton radiograph spatial resolution. We applied a correction based on Birks's analytical model for ionization quenching. The data demonstrate increased relative luminosity with increased activation element concentration, and higher relative luminosity for samples activated with europium. An increased glass density enables more compact detector geometries and higher spatial resolution. These findings suggest that a tungsten and gadolinium oxide-based glass activated with 4% europium is an ideal scintillator for testing in a full-size proton radiography detector.

Comparison of two methods simulating inter-track interactions using the radiobiological Monte Carlo toolkit TOPAS-nBio

Objective.To compare two independently developed methods that enable modelling inter-track interactions in TOPAS-nBio by examining the yield of radiolytic species in radiobiological Monte Carlo track structure simulations. One method uses a phase space file to assign more than one primary to one event, allowing for inter-track interaction between these primary particles. This method has previously been developed by this working group and published earlier. Using the other method, chemical reactions are simulated based on a new version of the independent reaction time approach to allow inter-track interactions.Approach.G-values were calculated and compared using both methods for different numbers of tracks able to undergo inter-track interactions.Main results.Differences in theG-values simulated with the two methods strongly depend on the molecule type, and deviations can range up to 3.9% (H2O2), although, on average, the deviations are smaller than 1.5%.Significance.Both methods seem to be suitable for simulating inter-track interactions, as they provide comparableG-values even though both techniques were developed independently of each other.

Extension of matRad with a modified microdosimetric kinetic model for carbon ion treatment planning: Comparison with Monte Carlo calculation

BACKGROUND

Treatment planning is essential for in silico particle therapy studies. matRad is an open-source research treatment planning system (TPS) based on the local effect model, which is a type of relative biological effectiveness (RBE) model.

PURPOSE

This study aims to implement a microdosimetric kinetic model (MKM) in matRad and develop an automation algorithm for Monte Carlo (MC) dose recalculation using the TOPAS code. In addition, we provide the developed MKM extension as open-source tool for users.

METHODS

Carbon beam data were generated using TOPAS MC pencil beam irradiation. We parameterized the TOPAS MC beam data with a double-Gaussian fit and modeled the integral depth doses and lateral spot profiles in the range of 100-430 MeV/u. To implement the MKM, the specific energy data table for Z = 1-6 and integrated depth-specific energy data were acquired based on the Kiefer-Chatterjee track structure and TOPAS MC simulation, respectively. Generic data were integrated into matRad, and treatment planning was performed based on these data. The optimized plan parameters were automatically converted into MC simulation input. Finally, the matRad TPS and TOPAS MC simulations were compared using the RBE-weighted dose calculation results. A comparison was made for three geometries: homogeneous water phantom, inhomogeneous phantom, and patient.

RESULTS

The RBE-weighted dose (DRBE ) distribution agreed with TOPAS MC within 1.8% for all target sizes for the homogeneous phantom. For the inhomogeneous phantom, the relative difference in the range of 80% of the prescription dose in the distal fall-off region (R80) between the matRad TPS and TOPAS MC was 0.6% (1.1 mm). DRBE between the TPS and the MC was within 4.0%. In the patient case, the difference in the dose-volume histogram parameters for the target volume between the TPS and the MC was less than 2.7%. The relative difference in R80 was 0.7% (1.2 mm).

CONCLUSIONS

The MKM was successfully implemented in matRad TPS, and the RBE-weighted dose was comparable to that of TOPAS MC. The MKM-implemented matRad was released as an open-source tool. Further investigations with MC simulations can be conducted using this tool, providing a good option for carbon ion research.

Double scattering and pencil beam scanning Monte Carlo workflows for proton therapy retrospective studies on radiation-induced toxicities

PURPOSE

Monte Carlo (MC) simulations can be used to accurately simulate dose and linear energy transfers (LET) distributions, thereby allowing for the calculation of the relative biological effectiveness (RBE) of protons. We present hereby the validation and implementation of a workflow for the Monte Carlo modelling of the double scattered and pencil beam scanning proton beamlines at our institution.

METHODS

The TOPAS/Geant4 MC model of the clinical nozzle has been comprehensively validated against measurements. The validation also included a comparison between simulated clinical treatment plans for four representative patients and the clinical treatment planning system (TPS). Moreover, an in-house tool implemented in Python was tested to assess the variable RBE-weighted dose in proton plans, which was illustrated for a patient case with a developing radiation-induced toxicity.

RESULTS

The simulated range and modulation width closely matches the measurements. Gamma-indexes (3%/3mm 3D), which compare the TPS and MC computations, showed a passing rate superior to 98%. The calculated RBE-weighted dose presented a slight increase at the necrosis location, within the PTV margins. This indicates the need for reporting on the physical and biological effects of irradiation in high dose regions, especially at the healthy tissues and increased LET distributions location.

CONCLUSION

The results demonstrate that the Monte Carlo method can be used to independently validate a TPS calculation, and to estimate LET distributions. The features of the in-house tool can be used to correlate LET and RBE-weighted dose distributions with the incidence of radiation-induced toxicities following proton therapy treatments.

Investigation of In-Field and Out-of-Field Radiation Quality With Microdosimetry and Its Impact on Relative Biological Effectiveness in Proton Therapy

PURPOSE

Using microdosimetry, this study investigated the relative biological effectiveness (RBE) and quality factor (Q¯) variations in field and out of field as a function of radiation quality for clinical protons.

METHODS AND MATERIALS

A water phantom with a spread-out Bragg peak (SOBP) was irradiated to acquire microdosimetric spectra at several distal and lateral depths with a tissue equivalent proportional counter. The measurements were used as inputs to microdosimetric kinetic and Loncol models to determine the RBE spatial distribution and compare it with predictions from the dose-averaged linear energy transfer-based McNamara model. Q¯ values and biological and dose equivalent values were also calculated.

RESULTS

The data demonstrated that radiation quality changed more rapidly with depth than lateral distance from the SOBP. In beam, y_D ranged from approximately 4 keV/μm at the entrance to 8 keV/μm at the SOBP far end, reaching approximately 15 keV/μm at the penumbra. Out of field, the overall highest value of 23 ± 2 keV/μm was observed at the beam-edge penumbra. Radiation quality changes caused RBE deviations from the clinical value of 1.1, whose extent depends on the approach used for assessing radiation quality as well as on the radiobiological model. For RBE₁₀, microdosimetry-based models appeared to better reproduce the radiobiological data than the dose-averaged linear energy transfer model. Out of field, both the RBE and Q¯ values appeared to have limitations in describing the radiation biological effectiveness. This research also presents a first comprehensive benchmark of TOPAS code against in-field and out-of-field microdosimetric spectra of therapeutic protons.

CONCLUSIONS

Further investigation will be necessary to evaluate the quantitative effects of RBE variations on treatment planning and assess the clinical consequences in terms of both tumor control and normal-tissue toxicity. The achievement of this goal calls for accurate radiobiological data to validate the RBE models.

Limitations of phase-sorting based pencil beam scanned 4D proton dose calculations under irregular motion

Objective.4D dose calculation (4DDC) for pencil beam scanned (PBS) proton therapy is typically based on phase-sorting of individual pencil beams onto phases of a single breathing cycle 4DCT. Understanding the dosimetric limitations and uncertainties of this approach is essential, especially for the realistic treatment scenario with irregular free breathing motion.Approach.For three liver and three lung cancer patient CTs, the deformable multi-cycle motion from 4DMRIs was used to generate six synthetic 4DCT(MRI)s, providing irregular motion (11/15 cycles for liver/lung; tumor amplitudes ∼4-18 mm). 4DDCs for two-field plans were performed, with the temporal resolution of the pencil beam delivery (4-200 ms) or with 8 phases per breathing cycle (500-1000 ms). For the phase-sorting approach, the tumor center motion was used to determine the phase assignment of each spot. The dose was calculated either using the full free breathing motion or individually repeating each single cycle. Additionally, the use of an irregular surrogate signal prior to 4DDC on a repeated cycle was simulated. The CTV volume with absolute dose differences >5% (V_dosediff>5%) and differences in CTVV_95%andD_5%-D_95%compared to the free breathing scenario were evaluated.Main results.Compared to 4DDC considering the full free breathing motion with finer spot-wise temporal resolution, 4DDC based on a repeated single 4DCT resulted inV_dosediff>5%of on average 34%, which resulted in an overestimation ofV_95%up to 24%. However, surrogate based phase-sorting prior to 4DDC on a single cycle 4DCT, reduced the averageV_dosediff>5%to 16% (overestimationV_95%up to 19%). The 4DDC results were greatly influenced by the choice of reference cycle (V_dosediff>5%up to 55%) and differences due to temporal resolution were much smaller (V_dosediff>5%up to 10%).Significance.It is important to properly consider motion irregularity in 4D dosimetric evaluations of PBS proton treatments, as 4DDC based on a single 4DCT can lead to an underestimation of motion effects.

An evolutionary optimization algorithm for proton arc therapy

Objective. Proton arc plan normally contains thousands of spot numbers and hundreds of energy layers. A recent study reported that the beam delivery time (BDT) is proportional to the spot numbers. Thus, it is critical to find an optimal plan with a fast delivery speed while maintaining a good plan quality. Thus, we developed a novel evolutionary algorithm to directly search for the optimal spot sparsity solution to balance plan quality and BDT. Approach. The planning platform included a plan quality objective, a generator, and a selector. The generator is based on trust-region-reflective solver. A selector was designed to filter or add the spot according to the expected spot number, based on the user’s input of BDT. The generator and selector are used alternatively to optimize a spot sparsity solution. Three clinical cases’ CT and structure datasets, e.g. brain, lung, and liver cancer, were used for testing purposes. A series of user-defined BDTs from 15 to 250 s were used as direct inputs. The relationship between the plan’s cost function value and BDT was evaluated in these three cases. Main results. The evolutionary algorithm could optimize a proton arc plan based on clinical user input BDT directly. The plan quality remains optimal in the brain, lung, and liver cases until the BDT was shorter than 25 s, 50 s and 100 s, respectively. The plan quality degraded as the input delivery time became too short, indicating that the plan lacked enough spot or degree of freedom. Significance. This is the first proton arc planning framework to directly optimize plan quality with the BDT as an input for the new generation of proton therapy systems. This work paved the roadmap for implementing such new technology in a routine clinic and provided a planning platform to explore the trade-off between the BDT and plan quality.

Experimental validation of proton physics models of Geant4 for calculating stopping power ratio

In this work, we conducted experiments to validate the proton physics models of Geant4 (version 10.6). The stopping power ratios (SPRs) of 11 inserts, such as acrylic, delrin, high density polyethylene, and polytetrafluoroethylene, etc, were measured using a superconducting synchrocyclotron that produces a scattering proton beam. The SPRs of the inserts were also calculated based on Geant4 simulation with six physics lists, i.e. QGSP_ FTFP_ BERT, QGSP_BIC_HP, QGSP_BIC, QGSP_FTFP_BERT, QSGP_BERT, and QBBC. The calculated SPRs were compared to the experimental SPRs, and relative per cent error was used to quantify the accuracy of the simulated SPRs of inserts. The comparison showed that the five physics lists generally agree well with the experimental SPRs with a relative difference of less than 1%. The lowest overall percentage error was observed for QGSP_FTFP_BERT and the highest overall percentage error was observed for QGSP_BIC_HP. The 0.1 mm range cut value consistently led to higher percentage error for all physics lists except for QGSP_BIC_HP and QBBC. Based on the validation, we recommend QGSP_BERT_HP physics list for proton dose calculation.

Quantification of biological range uncertainties in patients treated at the Krakow proton therapy centre

Background

Variable relative biological effectiveness (vRBE) in proton therapy might significantly modify the prediction of RBE-weighted dose delivered to a patient during proton therapy. In this study we will present a method to quantify the biological range extension of the proton beam, which results from the application of vRBE approach in RBE-weighted dose calculation.

Methods and materials

The treatment plans of 95 patients (brain and skull base patients) were used for RBE-weighted dose calculation with constant and the McNamara RBE model. For this purpose the Monte Carlo tool FRED was used. The RBE-weighted dose distributions were analysed using indices from dose-volume histograms. We used the volumes receiving at least 95% of the prescribed dose (V95) to estimate the biological range extension resulting from vRBE approach.

Results

The vRBE model shows higher median value of relative deposited dose and D95 in the planning target volume by around 1% for brain patients and 4% for skull base patients. The maximum doses in organs at risk calculated with vRBE was up to 14 Gy above dose limit. The mean biological range extension was greater than 0.4 cm.

Discussion

Our method of estimation of biological range extension is insensitive for dose inhomogeneities and can be easily used for different proton plans with intensity-modulated proton therapy (IMPT) optimization. Using volumes instead of dose profiles, which is the common method, is more universal. However it was tested only for IMPT plans on fields arranged around the tumor area.

Conclusions

Adopting a vRBE model results in an increase in dose and an extension of the beam range, which is especially disadvantageous in cancers close to organs at risk. Our results support the need to re-optimization of proton treatment plans when considering vRBE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02022-5.

Assessment of secondary neutrons in particle therapy by Monte Carlo simulations

OBJECTIVE

The purpose of this study is to estimate the energy and angular distribution of secondary neutrons inside a phantom in hadron therapy, which will support decisions on detector choice and experimental setup design for in-phantom secondary neutron measurements.

APPROACH

Dedicated Monte Carlo simulations were implemented, considering clinically relevant energies of protons, helium and carbon ions. Since scored quantities can vary from different radiation transport models, the codes FLUKA, TOPAS and MCNP were used. The geometry of an active scanning beam delivery system for heavy ion treatment was implemented, and simulations of pristine and spread-out Bragg peaks were carried out. Previous studies, focused on specific ion types or single energies, are qualitatively in agreement with the obtained results.

MAIN RESULTS

The secondary neutrons energy distributions present a continuous spectrum with two peaks, one centred on the thermal/epithermal region, and one on the high-energy region, with the most probable energy ranging from 19 MeV up to 240 MeV, depending on the ion type and its initial energy. The simulations show that the secondary neutron energies may exceed 400 MeV and, therefore, suitable neutron detectors for this energy range shall be needed. Additionally, the angular distribution of the low energy neutrons is quite isotropic, whereas the fast/relativistic neutrons are mainly scattered in the down-stream direction.

SIGNIFICANCE

It would be possible to minimize the influence of the heavy ions when measuring the neutron-generated recoil protons by selecting appropriate measurement positions within the phantom. Although there are discrepancies among the three Monte Carlo codes, the results agree qualitatively and in order of magnitude, being sufficient to support further investigations with the ultimate goal of mapping the secondary neutron doses both in- and out-of-field in hadrontherapy. The obtained secondary neutron spectra are available as supplementary material.

Dosimetry and radioprotection evaluations of very high energy electron beams

Very high energy electrons (VHEEs) represent a promising alternative for the treatment of deep-seated tumors over conventional radiotherapy (RT), owing to their favourable dosimetric characteristics. Given the high energy of the electrons, one of the concerns has been the production of photoneutrons. In this article we explore the consequence, in terms of neutron yield in a water phantom, of using a typical electron applicator in conjunction with a 2 GeV and 200 MeV VHEE beam. Additionally, we evaluate the resulting ambient neutron dose equivalent at various locations between the phantom and a concrete wall. Through Monte Carlo (MC) simulations it was found that an applicator acts to reduce the depth of the dose build-up region, giving rise to lower exit doses but higher entrance doses. Furthermore, neutrons are injected into the entrance region of the phantom. The highest dose equivalent found was approximately 1.7 mSv/Gy in the vicinity of the concrete wall. Nevertheless, we concluded that configurations of VHEEs studied in this article are similar to conventional proton therapy treatments in terms of their neutron yield and ambient dose equivalent. Therefore, a clinical implementation of VHEEs would likely not warrant additional radioprotection safeguards compared to conventional RT treatments.

Technical note: Extraction of proton pencil beam energy spectrum from measured integral depth dose in a cyclotron proton beam system

PURPOSE

Proton pencil beam energy spectrum is an essential parameter for calculations of dose and linear energy transfer. We extract the energy spectrum from measured integral depth dose (IDD).

METHODS

A measured IDD (measIDD) in water is decomposed into many IDDs of mono-energetic pencil beams (monoIDDs) in water. A simultaneous iterative technique is used to do the decomposition that extracts the energy spectrum of protons from the measIDD. The monoIDDs are generated by our analytic random walk model-based proton dose calculation algorithm. The linear independence of the monoIDDs is considered and high spatial resolution monoIDDs are used to improve their linear independence. To validate the extraction, first we use synthesized IDDs (synIDD) with Gaussian energy spectrum and compare the extracted energy spectrum with the Gaussian; second, for the energy spectrum extracted from measIDDs, the accuracy of the extraction is validated by comparing the calculated IDD from the energy spectrum with the measIDD. The measIDDs are derived from commissioning of a cyclotron proton pencil beam system with a Bragg peak ionization chamber. The nominal energy of the pencil beams is from 70 to 245 MeV. The monoIDDs are generated for energies from 0.05 to 275 MeV in steps of 0.05 MeV with a spatial resolution of 1 mm.

RESULTS

The difference of the extracted and original Gaussian energy spectrum peaked at 75 and 80 MeV was <1%. As the energy decreased, the difference increased but was reduced by using 0.1-mm monoIDDs. The difference was not sensitive to the energy interval of monoIDDs when the interval increased from 0.05 to 1 MeV. For the energy spectrum extraction from measIDDs, there was a main peak near the nominal energy but the spectrum was not in Gaussian distribution. In three example cases (70, 160, and 245 MeV), the relative differences of the measIDDs and calculated IDDs were within 3.4%, 2.9%, and 4.7% of the Bragg peak value, respectively. Fitting the spectrum by Gaussian distribution, we had σ = 0.87, 1.51, and 0.86 MeV, respectively, for these three examples, and the relative differences of the resultant calculated IDDs from the measIDDs were within 4.7%, 7.4%, and 4.5%, respectively.

CONCLUSIONS

Our algorithm accurately extracted the energy spectrum from the synIDDs and measIDDs. High-resolution monoIDDs are necessary to extract low-energy spectrum. Energy spectrum extraction from measIDD reveals important information for beam modeling.

Conceptual Design of a Novel Nozzle Combined with a Clinical Proton Linac for Magnetically Focussed Minibeams

Simple Summary

Proton minibeam radiation therapy (pMBRT) is a novel therapeutic strategy that combines the tissue sparing potential of submillimetric, spatially fractionated beams (minibeams) with the improved ballistics of protons to enhance the tolerance of normal tissue and allow a dose escalation in the tumour. This approach could allow a more effective treatment of radioresistant tumours and has already shown excellent results for rat gliomas. To exploit the full potential of pMBRT, it should be delivered using magnetically focussed and scanned minibeams. However, such an implementation has not yet been demonstrated at clinically relevant beam energies. In this work, we therefore present a new design combining our recently developed minibeam nozzle with the first clinical proton linear accelerator. We show the suitability of this combination for the generation of magnetically focussed and scanned minibeams with clinically relevant parameters as well as for the delivery of conventional pencil beam scanning techniques.

Abstract

(1) Background: Proton minibeam radiation therapy (pMBRT) is a novel therapeutic approach with the potential to significantly increase normal tissue sparing while providing tumour control equivalent or superior to standard proton therapy. For reasons of efficiency, flexibility and minibeam quality, the optimal implementation of pMBRT should use magnetically focussed minibeams which, however, could not yet be generated in a clinical environment. In this study, we evaluated our recently proposed minibeam nozzle together with a new clinical proton linac as a potential implementation. (2) Methods: Monte Carlo simulations were performed to determine under which conditions minibeams can be generated and to evaluate the robustness against focussing magnet errors. Moreover, an example of conventional pencil beam scanning irradiation was simulated. (3) Results: Excellent minibeam sizes between 0.6 and 0.9 mm full width at half maximum could be obtained and a good tolerance to errors was observed. Furthermore, the delivery of a 10 cm × 10 cm field with pencil beams was demonstrated. (4) Conclusion: The combination of the new proton linac and minibeam nozzle could represent an optimal implementation of pMBRT by allowing the generation of magnetically focussed minibeams with clinically relevant parameters. It could furthermore be used for conventional pencil beam scanning.

Monte Carlo methods for device simulations in radiation therapy

Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties. The aim of this article is to review the MC method for device simulations in radiation therapy. After a brief history of the MC method and popular codes in medical physics, we review applications of the MC method to model treatment heads for neutral and charged particle radiation therapy as well as specific in-room devices for imaging and therapy purposes. We conclude by discussing the impact that MCSs had in this field and the role of MC in future device design.

Monte Carlo methods for device simulations in radiation therapy

Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties. The aim of this article is to review the MC method for device simulations in radiation therapy. After a brief history of the MC method and popular codes in medical physics, we review applications of the MC method to model treatment heads for neutral and charged particle radiation therapy as well as specific in-room devices for imaging and therapy purposes. We conclude by discussing the impact that MCSs had in this field and the role of MC in future device design.

Investigating beam range uncertainty in proton prostate treatment using pelvic-like biological phantoms

This study aims to develop a method for verifying site-specific and/or beam path specific proton beam range, which could reduce range uncertainty margins and the associated treatment complications. It investigates the range uncertainties from both CT HU to relative stopping power conversion and patient positioning errors for prostate treatment using pelvic-like biological phantoms. Three 25 × 14 × 12 cm³phantoms, made of fresh animal tissues mimicking the pelvic anatomies of prostate patients, were scanned with a general electric CT simulator. A 22 cm circular passive scattering beam with 29 cm range and 8 cm modulation width was used to measure the water equivalent path lengths (WEPL) through the phantoms at multiple points using the dose extinction method with a MatriXXPT detector. The measured WEPLs were compared to those predicted by TOPAS simulations and ray-tracing WEPL calculations. For the three phantoms, the WEPL differences between measured and theoretical prediction (WDMT) are below 1.8% for TOPAS, and 2.5% for ray-tracing. WDMT varies with phantom anatomies by about 0.5% for both TOPAS and ray-tracing. WDMT also correlates with the tissue types of a specific treated region. For the regions where the proton beam path is parallel to sharp bone edges, the WDMTs of TOPAS and ray-tracing respectively reach up to 1.8% and 2.5%. For the region where proton beams pass through just soft tissues, the WDMT is mostly less than 1% for both TOPAS and ray-tracing. For prostate treatments, range uncertainty depends on the tissue types within a specific treated region, patient anatomies and the range calculation methods in the planning algorithms. Our study indicates range uncertainty is less than 2.5% for the whole treated region with both ray-tracing and TOPAS, which suggests the potential to reduce the current 3.5% range uncertainty margin used in the clinics by at least 1% even for single-energy CT data.

Investigating the feasibility of TOPAS-nBio for Monte Carlo track structure simulations by adapting GEANT4-DNA examples application

Purpose.The purpose of this work is to investigate the feasibility of TOPAS-nBio for track structure simulations using tuple scoring and ROOT/Python-based post-processing.Materials and methods.There are several example applications implemented in GEANT4-DNA demonstrating track structure simulations. These examples are not implemented by default in TOPAS-nBio. In this study, the tuple scorer was used to re-simulate these examples. The simulations contained investigations of different physics lists, calculation of energy-dependent range, stopping power, mean free path andW-value. Additionally, further applications of the TOPAS-nBio tool were investigated, focusing on physical interactions and deposited energies of electrons with initial energies in the range of 10-60 eV, not covered in the recently published GEANT4-DNA simulations. Low-energetic electrons are currently of great interest in the radiobiology research community due to their high effectiveness towards the induction of biological damage.Results.The quantities calculated with TOPAS-nBio show a good agreement with the simulations of GEANT4-DNA with deviations of 5% at maximum. Thus, we have presented a feasible way to implement the example applications included in GEANT4-DNA in TOPAS-nBio. With the extended simulations, an insight could be given, which further tracking information can be gained with the track structure code and how cross sections and physics models influence a particle's fate.Conclusion.With our results, we could show the potentials of applying the tuple scorer in TOPAS-nBio Monte Carlo track structure simulations. Using this scorer, a large amount of information about the track structure can be accessed, which can be analyzed as preferred after the simulation.

Brain-Specific Relative Biological Effectiveness of Protons Based on Long-term Outcome of Patients With Nasopharyngeal Carcinoma

PURPOSE

Uncertainties in relative biological effectiveness (RBE) constitute a major pitfall of the use of protons in clinics. An RBE value of 1.1, which is based on cell culture and animal models, is currently used in clinical proton planning. The purpose of this study was to determine RBE for temporal lobe radiographic changes using long-term follow-up data from patients with nasopharyngeal carcinoma.

METHODS AND MATERIALS

Five hundred sixty-six patients with newly diagnosed nasopharyngeal carcinoma received double-scattering proton therapy or intensity modulated radiation therapy at our institutions. The 2 treatment cohorts were well matched. Proton dose distributions were simulated using Monte Carlo and compared with those obtained from the proton clinical treatment planning system. Late treatment effect was defined as development of enhancement of temporal lobe on T1-weighted magnetic resonance imaging, with or without accompanying clinical symptoms. The tolerance dose was calculated with receiving operator characteristic analysis and the Youden index. Tolerance curves, expressed as a cumulative dose-volume histogram, were generated using the cutoff points.

RESULTS

With a median follow-up period >5 years for both cohorts, 10% of proton patients and 4% of patients undergoing intensity modulated radiation therapy developed temporal lobe enhancement in unilateral temporal lobe. There was no significant difference in dose distributions between the Monte Carlo method and treatment planning system. The tolerance dose-volume levels were V10 (26.1%), V20 (21.9%), V30 (14.0%), V40 (7.7%), V50 (4.8%), and V60 (3.3%) for proton therapy (P < .03). Comparison of the two tolerance curves revealed that tolerance doses of proton treatments were lower than that of photon treatments at all dose levels. The dose tolerance at D1% was 58.56 Gy for protons and 69.07 Gy for photons. The RBE for temporal lobe enhancement from proton treatments were calculated to be 1.18.

CONCLUSIONS

Using long-term clinical outcome of patients with nasopharyngeal carcinoma, our data suggest that the RBE for temporal lobe enhancement is 1.18 at D1%. A prospective study in a large cohort would be necessary to confirm these findings.

Focused VHEE (very high energy electron) beams and dose delivery for radiotherapy applications

This paper presents the first demonstration of deeply penetrating dose delivery using focused very high energy electron (VHEE) beams using quadrupole magnets in Monte Carlo simulations. We show that the focal point is readily modified by linearly changing the quadrupole magnet strength only. We also present a weighted sum of focused electron beams to form a spread-out electron peak (SOEP) over a target region. This has a significantly reduced entrance dose compared to a proton-based spread-out Bragg peak (SOBP). Very high energy electron (VHEE) beams are an exciting prospect in external beam radiotherapy. VHEEs are less sensitive to inhomogeneities than proton and photon beams, have a deep dose reach and could potentially be used to deliver FLASH radiotherapy. The dose distributions of unfocused VHEE produce high entrance and exit doses compared to other radiotherapy modalities unless focusing is employed, and in this case the entrance dose is considerably improved over existing radiations. We have investigated both symmetric and asymmetric focusing as well as focusing with a range of beam energies.

Empirical quenching correction in radiochromic silicone-based three-dimensional dosimetry of spot-scanning proton therapy

Background and purpose

Three-dimensional dosimetry of proton therapy (PT) with chemical dosimeters is challenged by signal quenching, which is a lower dose-response in regions with high ionization density due to high linear-energy-transfer (LET) and dose-rate. This study aimed to assess the viability of an empirical correction model for 3D radiochromic silicone-based dosimeters irradiated with spot-scanning PT, by parametrizing its LET and dose-rate dependency.

Materials and methods

Ten cylindrical radiochromic dosimeters (Ø50 and Ø75 mm) were produced in-house, and irradiated with different spot-scanning proton beam configurations and machine-set dose rates ranging from 56 to 145 Gy/min. Beams with incident energies of 75, 95 and 120 MeV, a spread-out Bragg peak and a plan optimized to an irregular target volume were included. Five of the dosimeters, irradiated with 120 MeV beams, were used to estimate the quenching correction factors. Monte Carlo simulations were used to obtain dose and dose-averaged-LET (LET_d) maps. Additionally, a local dose-rate map was estimated, using the simulated dose maps and the machine-set dose-rate information retrieved from the irradiation log-files. Finally, the correction factor was estimated as a function of LET_d and local dose-rate and tested on the different fields.

Results

Gamma-pass-rates of the corrected measurements were >94% using a 3%-3 mm gamma analysis and >88% using 2%-2 mm, with a dose deviation of <5.6 ± 1.8%. Larger dosimeters showed a 20% systematic increase in dose-response, but the same quenching in signal when compared to the smaller dosimeters.

Conclusion

The quenching correction model was valid for different dosimeter sizes to obtain relative dosimetric maps of complex dose distributions in PT.

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.

Implementation of a double scattering nozzle for Monte Carlo recalculation of proton plans with variable relative biological effectiveness

A constant relative biological effectiveness (RBE) of 1.1 is currently used in clinical proton therapy. However, theRBEvaries with factors such as dose level, linear energy transfer (LET) and tissue type. MultipleRBEmodels have been developed to account for this biological variation. To enable recalculation of patients treated with double scattering (DS) proton therapy, includingLETand variableRBE, we implemented and commissioned a Monte Carlo (MC) model of a DS treatment nozzle. The main components from the IBA nozzle were implemented in the FLUKA MC code. We calibrated and verified the following entities to experimental measurements: range of pristine Bragg peaks (PBPs) and spread-out Bragg peaks (SOBPs), energy spread, lateral profiles, compensator range degradation, and absolute dose. We recalculated two patients with different field setups, comparing FLUKA vs. treatment planning system (TPS) dose, also obtainingLETand variableRBEdoses. We achieved good agreement between FLUKA and measurements. The range differences between FLUKA and measurements were for the PBPs within ±0.9 mm (83% ⩽ 0.5 mm), and for SOBPs ±1.6 mm (82% ⩽ 0.5 mm). The differences in modulation widths were below 5 mm (79% ⩽ 2 mm). The differences in the distal dose fall off (D80%-D20%) were below 0.5 mm for all PBPs and the lateral penumbras diverged from measurements by less than 1 mm. The mean dose difference (RBE= 1.1) in the target between the TPS and FLUKA were below 0.4% in a three-field plan and below 1.4% in a four-field plan. A dose increase of 9.9% and 7.2% occurred when using variableRBEfor the two patients, respectively. We presented a method to recalculate DS proton plans in the FLUKA MC code. The implementation was used to obtainLETand variableRBEdose and can be used for investigating variableRBEfor previously treated patients.

Brain Necrosis in Adult Patients After Proton Therapy: Is There Evidence for Dependency on Linear Energy Transfer?

PURPOSE

To investigate if radiographic imaging changes defined as necrosis correlate with regions in the brain with elevated linear energy transfer (LET) for proton radiation therapy treatments with partial brain involvement in central nervous system and patients with head and neck cancer.

METHODS AND MATERIALS

Fifty patients with head and neck, skull base, or intracranial tumors who underwent proton therapy between 2004 to 2016 with a minimum prescription dose of 59.4 Gy (relative biological effectiveness) and with magnetic resonance imaging changes indicative of brain necrosis after radiation therapy were retrospectively reviewed. Each treatment plan was recalculated using Monte Carlo simulations to provide accurate dose distributions as well as 3-dimensional distributions of LET. To assess the effect of LET on radiographic imaging changes several voxel-based analyses were performed.

RESULTS

In this patient cohort, LET adjusted for dose was not found to be associated with risk of brain necrosis.

CONCLUSIONS

A voxel-based analysis of brain necrosis as an endpoint is difficult owing to uncertainties in the origin of necrosis, timing of imaging, variability in patient specific radiosensitivity, and the simultaneous effect of dose and LET. Even though it is expected that the LET and thus relative biological effectiveness increases at the end of range, effects in patients might be small compared with interpatient variability of radiosensitivity and might be obscured by other confounding factors.

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic MC simulations of an existing pCT scanner prototype, which we describe in detail.

DICOM-RT Ion interface to utilize MC simulations in routine clinical workflow for proton pencil beam radiotherapy

To adopt Monte Carlo (MC) simulations as an independent dose calculation method for proton pencil beam radiotherapy, an interface that converts the plan information in DICOM format into MC components such as geometries and beam source is a crucial element. For this purpose, a DICOM-RT Ion interface (https://github.com/topasmc/dicom-interface) has been developed and integrated into the TOPAS MC code to perform such conversions on-the-fly. DICOM-RT objects utilized in this interface include Ion Plan (RTIP), Ion Beams Treatment Record (RTIBTR), CT image, and Dose. Beamline geometries, gantry and patient coordinate systems, and fluence maps are determined from RTIP and/or RTIBTR. In this interface, DICOM information is processed and delivered to a MC engine in two steps. A MC model, which consists of beamline geometries and beam source, to represent a treatment machine is created by a DICOM parser of the interface. The complexities from different DICOM types, various beamline configurations and source models are handled in this step. Next, geometry information and beam source are transferred to TOPAS on-the-fly via the developed TOPAS extensions. This interface with two treatment machines was successfully deployed into our automated MC workflow which provides simulated dose and LET distributions in a patient or a water phantom automatically when a new plan is identified. The developed interface provides novel features such as handling multiple treatment systems based on different DICOM types, DICOM conversions on-the-fly, and flexible sampling methods that significantly reduce the burden of handling DICOM based plan or treatment record information for MC simulations.

Developing a Monte Carlo model for MEVION S250i with HYPERSCAN and Adaptive Aperture™ pencil beam scanning proton therapy system

Aim:

As the number of proton therapy facilities has steadily increased, the need for the tool to provide precise dose simulation for complicated clinical and research scenarios also increase. In this study, the treatment head of Mevion HYPERSCAN pencil beam scanning (PBS) proton therapy system including energy modulation system (EMS) and Adaptive Aperture™ (AA) was modelled using TOPAS (TOolkit for PArticle Simulation) Monte Carlo (MC) code and was validated during commissioning process.

Materials and methods:

The proton beam characteristics including integral depth doses (IDDs) of pristine Bragg peak and in-air beam spot sizes were simulated and compared with measured beam data. The lateral profiles, with and without AA, were also verified against calculation from treatment planning system (TPS).

Results:

All beam characteristics for IDDs and in-air spot size agreed well within 1 mm and 10% separately. The full width at half maximum and penumbra of lateral dose profile also agree well within 2 mm.

Finding:

The TOPAS MC simulation of the MEVION HYPERSCAN PBS proton therapy system has been modelled and validated; it could be a viable tool for research and verification of the proton treatment in the future.

Simulation of spread-out bragg peaks in proton beams using Geant4/TOPAS

The simulation of proton Spread-Out Bragg Peaks (SOBPs) was implemented using the Geant4-based TOPAS Monte Carlo software. Dynamic proton energy switching was implemented using TOPAS time features, while beam weights were calculated using an empirical power law formalism with Bragg peaks spaced by 0.5 mm. To find power parameters yielding flat SOBPs we sampled power parameters for maximum kinetic energies of 50 MeV to 250 MeV and SOBP widths of 15% to 40% of the depth of the distal SOBP end. Simulations were run in a 50 cm cubic water phantom using a uniform squared proton beam. Depth dose was scored along the central axis in a binned cylinder with 1 cm diameter in 2.5 mm increments. Power parameters yielding a flat SOBPs were found to vary with, both energy and SOBP width and differed significantly from previously reported values based on simulations with MCNPX.

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.

Advancing proton minibeam radiation therapy: magnetically focussed proton minibeams at a clinical centre

Proton minibeam radiation therapy (pMBRT) is a novel therapeutic strategy that has proven to significantly increase dose tolerances and sparing of normal tissue. It uses very narrow proton beams (diameter ≤1 mm), roughly one order of magnitude smaller than state-of-the-art pencil beams. The current implementation of pMBRT with mechanical collimators is suboptimal as it is inflexible, decreases efficiency and produces additional secondary neutrons. As a potential solution, we explore in this article minibeam generation through magnetic focussing and investigate possibilities for the integration of such a technique at existing clinical centres. For this, a model of the pencil beam scanning (PBS) nozzle and beam at the Orsay Proton Therapy Centre was established and Monte Carlo simulations were performed to determine its focussing capabilities. Moreover, various modifications of the nozzle geometry were considered. It was found that the PBS nozzle in its current state is not suitable for magnetic minibeam generation. Instead, a new, optimised nozzle design has been proposed and conditions necessary for minibeam generation were benchmarked. In addition, dose simulations in a water phantom were performed which showed improved dose distributions compared to those obtained with mechanical collimators.

Comparing 2 Monte Carlo Systems in Use for Proton Therapy Research

Purpose

Several Monte Carlo transport codes are available for medical physics users. To ensure confidence in the accuracy of the codes, they must be continually cross-validated. This study provides comparisons between MC² and Tool for Particle Simulation (TOPAS) simulations, that is, between medical physics applications for Monte Carlo N-Particle Transport Code (MCNPX) and Geant4.

Materials and Methods

Monte Carlo simulations were repeated with 2 wrapper codes: TOPAS (based on Geant4) and MC² (based on MCNPX). Simulations increased in geometrical complexity from a monoenergetic beam incident on a water phantom, to a monoenergetic beam incident on a water phantom with a bone or tissue slab at various depths, to a spread-out Bragg peak incident on a voxelized computed tomography (CT) geometry. The CT geometry cases consisted of head and neck tissue and lung tissue. The results of the simulations were compared with one another through dose or energy deposition profiles, r ₉₀ calculations, and γ-analyses.

Results

Both codes gave very similar results with monoenergetic beams incident on a water phantom. Systematic differences were observed between MC² and TOPAS simulations when using a lung or bone slab in a water phantom, particularly in the r ₉₀ values, where TOPAS consistently calculated r ₉₀ to be deeper by about 0.4%. When comparing the performance of the 2 codes in a CT geometry, the results were still very similar, exemplified by a 3-dimensional γ-analysis pass rate > 95% at the 2%-2-mm criterion for tissues from both head and neck and lung.

Conclusion

Differences between TOPAS and MC² were minor and were not considered clinically relevant.

Comparison of penh, fluka, and Geant4/topas for absorbed dose calculations in air cavities representing ionization chambers in high-energy photon and proton beams

Purpose

The purpose of this work is to analyze whether the Monte Carlo codes penh, fluka, and geant4/topas are suitable to calculate absorbed doses and fQ/fQ0 ratios in therapeutic high‐energy photon and proton beams.

Methods

We used penh, fluka, geant4/topas, and egsnrc to calculate the absorbed dose to water in a reference water cavity and the absorbed dose to air in two air cavities representative of a plane‐parallel and a cylindrical ionization chamber in a 1.25 MeV photon beam and a 150 MeV proton beam — egsnrc was only used for the photon beam calculations. The physics and transport settings in each code were adjusted to simulate the particle transport as detailed as reasonably possible. From these absorbed doses, fQ0 factors, fQ factors, and fQ/fQ0 ratios (which are the basis of Monte Carlo calculated beam quality correction factors kQ,Q0) were calculated and compared between the codes. Additionally, we calculated the spectra of primary particles and secondary electrons in the reference water cavity, as well as the integrated depth–dose curve of 150 MeV protons in water.

Results

The absorbed doses agreed within 1.4% or better between the individual codes for both the photon and proton simulations. The fQ0 and fQ factors agreed within 0.5% or better for the individual codes for both beam qualities. The resulting fQ/fQ0 ratios for 150 MeV protons agreed within 0.7% or better. For the 1.25 MeV photon beam, the spectra of photons and secondary electrons agreed almost perfectly. For the 150 MeV proton simulation, we observed differences in the spectra of secondary protons whereas the spectra of primary protons and low‐energy delta electrons also agreed almost perfectly. The first 2 mm of the entrance channel of the 150 MeV proton Bragg curve agreed almost perfectly while for greater depths, the differences in the integrated dose were up to 1.5%.

Conclusion

penh, fluka, and geant4/topas are capable of calculating beam quality correction factors in proton beams. The differences in the fQ0 and fQ factors between the codes are 0.5% at maximum. The differences in the fQ/fQ0 ratios are 0.7% at maximum.

TOPAS Monte Carlo simulation for double scattering proton therapy and dosimetric evaluation

PURPOSE

To construct and commission a double scattering (DS) proton beam model in TOPAS Monte Carlo (MC) code. Dose comparisons of MC calculations to the measured and treatment planning system (TPS) calculated dose were performed.

METHODS

The TOPAS nozzle model was based on the manufacturer blueprints. Nozzle set-up and beam current modulations were calculated using room-specific calibration data. This model was implemented to reproduce pristine peaks, spread-out Bragg peaks (SOBP) and lateral profiles. A stair-shaped target plan in water phantom was calculated and compared to measured data to verify range compensator (RC) modeling.

RESULTS

TOPAS calculated pristine peaks agreed well with measurements, with accuracies of 0.03 cm for range R₉₀ and 0.05 cm for distal dose fall-off (DDF). The calculated SOBP range, modulation width and DDF differences between MC calculations and measurements were within 0.05 cm, 0.5 cm and 0.03 cm respectively. MC calculated lateral penumbra agreed well with measured data, with difference less than 0.05 cm. For RC calculation, TPS underestimated the additional depth dose tail due to the nuclear halo effect. Lateral doses by TPS were 10% lower than measurement outside the target, while maximum difference of MC calculation was within 2%. At deeper depths inside the target volume, TPS overestimated doses by up to 25% while TOPAS predicted the dose to within 5% of measurements.

CONCLUSION

We have successfully developed and commissioned a MC based DS nozzle model. The performance of dose accuracy by TOPAS was superior to TPS, especially for highly inhomogeneous compensator.

Log file based Monte Carlo calculations for proton pencil beam scanning therapy

Patient specific quality assurance is crucial to guarantee safety in proton pencil beam scanning. In current clinical practice, this requires extensive, time consuming measurements. Additionally, these measurements do not consider the influence of density heterogeneities in the patient and are insensitive to delivery errors. In this work, we investigate the use of log file based Monte Carlo calculations for dose reconstructions in the patient CT, which takes the combined influence of calculational and delivery errors into account. For one example field, 87%/90% of the voxels agree within  ±3% when taking either calculational or delivery uncertainties into account (analytical versus Monte Carlo calculation/Monte Carlo from planned versus Monte Carlo from log file). 78% agree when considering both uncertainties simultaneously (nominal field versus Monte Carlo from log files). We then show the application of the log file based Monte Carlo calculations as a patient specific quality assurance tool for a set of five patients (16 fields) treated for different indications. For all fields, absolute dose scaling factors based on the log file Monte Carlo agree within  ±3% to the measurement based absolute dose scaling. Relative comparison shows that more than 90% of the voxels agree within  ±  5% between the analytical calculated plan and the Monte Carlo based on log files. The log file based Monte Carlo approach is an end-to-end test incorporating all requirements of patient specific quality assurance. It has the potential to reduce the workload and therefore to increase the patient throughput, while simultaneously enabling more accurate dose verification directly in the patient geometry.

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.

Report of a National Cancer Institute special panel: Characterization of the physical parameters of particle beams for biological research

PURPOSE

To define the physical parameters needed to characterize a particle beam in order to allow intercomparison of different experiments performed using different ions at the same facility and using the same ion at different facilities.

METHODS

At the request of the National Cancer Institute (NCI), a special panel was convened to review the current status of the field and to provide suggested metrics for reporting the physical parameters of particle beams to be used for biological research. A set of physical parameters and measurements that should be performed by facilities and understood and reported by researchers supported by NCI to perform pre-clinical radiobiology and medical physics of heavy ions were generated.

RESULTS

Standard measures such as radiation delivery technique, beam modifiers used, nominal energy, field size, physical dose and dose rate should all be reported. However, more advanced physical measurements, including detailed characterization of beam quality by microdosimetric spectrum and fragmentation spectra, should also be established and reported. Details regarding how such data should be incorporated into Monte Carlo simulations and the proper reporting of simulation details are also discussed.

CONCLUSIONS

In order to allow for a clear relation of physical parameters to biological effects, facilities and researchers should establish and report detailed physical characteristics of the irradiation beams utilized including both standard and advanced measures. Biological researchers are encouraged to actively engage facility staff and physicists in the design and conduct of experiments. Modeling individual experimental setups will allow for the reporting of the uncertainties in the measurement or calculation of physical parameters which should be routinely reported.

A complete workflow for utilizing Monte Carlo toolkits in clinical cases for a double-scattering proton therapy system

The methods described in this paper allow end users to utilize Monte Carlo (MC) toolkits for patient‐specific dose simulation and perform analysis and plan comparisons for double‐scattering proton therapy systems. The authors aim to fill two aspects of this process previously not explicitly published. The first one addresses the modeling of field‐specific components in simulation space. Patient‐specific compensator and aperture models are exported from treatment planning system and converted to STL format using a combination of software tools including Matlab and Autodesk's Netfabb. They are then loaded into the MC geometry for simulation purpose. The second details a method for easily visualizing and comparing simulated doses with the dose calculated from the treatment planning system. This system is established by utilizing the open source software 3D Slicer. The methodology was demonstrated with a two‐field proton treatment plan on the IROC lung phantom. Profiles and two‐dimensional (2D) dose planes through the target isocenter were analyzed using our in‐house software tools. This present workflow and set of codes can be easily adapted by other groups for their clinical practice.

Validation and application of a fast Monte Carlo algorithm for assessing the clinical impact of approximations in analytical dose calculations for pencil beam scanning proton therapy

PURPOSE

Monte Carlo (MC) dose calculation is generally superior to analytical dose calculation (ADC) used in commercial TPS to model the dose distribution especially for heterogeneous sites, such as lung and head/neck patients. The purpose of this study was to provide a validated, fast, and open-source MC code, MCsquare, to assess the impact of approximations in ADC on clinical pencil beam scanning (PBS) plans covering various sites.

METHODS

First, MCsquare was validated using tissue-mimicking IROC lung phantom measurements as well as benchmarked with the general purpose Monte Carlo TOPAS for patient dose calculation. Then a comparative analysis between MCsquare and ADC was performed for a total of 50 patients with 10 patients per site (including liver, pelvis, brain, head-and-neck, and lung). Differences among TOPAS, MCsquare, and ADC were evaluated using four dosimetric indices based on the dose-volume histogram (target Dmean, D95, homogeneity index, V95), a 3D gamma index analysis (using 3%/3 mm criteria), and estimations of tumor control probability (TCP).

RESULTS

Comparison between MCsquare and TOPAS showed less than 1.8% difference for all of the dosimetric indices/TCP values and resulted in a 3D gamma index passing rate for voxels within the target in excess of 99%. When comparing ADC and MCsquare, the variances of all the indices were found to increase as the degree of tissue heterogeneity increased. In the case of lung, the D95s for ADC were found to differ by as much as 6.5% from the corresponding MCsquare statistic. The median gamma index passing rate for voxels within the target volume decreased from 99.3% for liver to 75.8% for lung. Resulting TCP differences can be large for lung (≤10.5%) and head-and-neck (≤6.2%), while smaller for brain, pelvis and liver (≤1.5%).

CONCLUSIONS

Given the differences found in the analysis, accurate dose calculation algorithms such as Monte Carlo simulations are needed for proton therapy, especially for disease sites with high heterogeneity, such as head-and-neck and lung. The establishment of MCsquare can facilitate patient plan reviews at any institution and can potentially provide unbiased comparison in clinical trials given its accuracy, speed and open-source availability.

The impact of secondary fragments on the image quality of helium ion imaging

Single-event ion imaging enables the direct reconstruction of the relative stopping power (RSP) information required for ion-beam therapy. Helium ions were recently hypothesized to be the optimal species for such technique. The purpose of this work is to investigate the effect of secondary fragments on the image quality of helium CT (HeCT) and to assess the performance of a prototype proton CT (pCT) scanner when operated with helium beams in Monte Carlo simulations and experiment. Experiments were conducted installing the U.S. pCT consortium prototype scanner at the Heidelberg Ion-Beam Therapy Center (HIT). Simulations were performed with the scanner using the TOPAS toolkit. HeCT images were reconstructed for a cylindrical water phantom, the CTP404 (sensitometry), and the CTP528 (line-pair) [Formula: see text] ® modules. To identify and remove individual events caused by fragmentation, the multistage energy detector of the scanner was adapted to function as a [Formula: see text] telescope. The use of the developed filter eliminated the otherwise arising ring artifacts in the HeCT reconstructed images. For the HeCT reconstructed images of a water phantom, the maximum RSP error was improved by almost a factor 8 with respect to unfiltered images in the simulation and a factor 10 in the experiment. Similarly, for the CTP404 module, the mean RSP accuracy improved by a factor 6 in both the simulation and the experiment when the filter was applied (mean relative error 0.40% in simulation, 0.45% in experiment). In the evaluation of the spatial resolution through the CTP528 module, the main effect of the filter was noise reduction. For both simulated and experimental images the spatial resolution was  ∼4 lp cm-1. In conclusion, the novel filter developed for secondary fragments proved to be effective in improving the visual quality and RSP accuracy of the reconstructed images. With the filter, the pCT scanner is capable of accurate HeCT imaging.

Impact of potentially variable RBE in liver proton therapy

Currently, the relative biological effectiveness (RBE) is assumed to be constant with a value of 1.1 in proton therapy. Although trends of RBE variations are well known, absolute values in patients are associated with considerable uncertainties. This study aims to evaluate the impact of a variable proton RBE in proton therapy liver trials using different fractionation schemes. Sixteen liver cancer cases were evaluated assuming two clinical schedules of 40 Gy/5 fractions and 58.05 Gy/15 fractions. The linear energy transfer (LET) and physical dose distribution in patients were simulated using Monte Carlo. The variable RBE distribution was calculated using a phenomenological model, considering the influence of the LET, fraction size and α/β value. Further, models to predict normal tissue complication probability (NTCP) and tumor control probability (TCP) were used to investigate potential RBE effects on outcome predictions. Applying the variable RBE model to the 5 and 15 fractions schedules results in an increase in mean fraction-size equivalent dose (FED) to the normal liver of 5.0% and 9.6% respectively. For patients with a mean FED to the normal liver larger than 29.8 Gy, this results in a non-negligible increase in the predicted NTCP of the normal liver averaging 11.6%, ranging from 2.7% to 25.6%. On the other hand, decrease in TCP was less than 5% for both fractionation regimens for all patients when assuming a variable RBE instead of constant. Consequently, the difference in TCP between the two fractionation schedules did not change significantly assuming a variable RBE while the impact on the NTCP difference was highly case specific. In addition, both the NTCP and TCP decrease with increasing α/β value for both fractionation schemes, with the decreases being more pronounced when using a variable RBE compared to using RBE  =  1.1. Assuming a constant RBE of 1.1 most likely overestimates the therapeutic ratio in proton therapy for liver cancer, predominantly due to underestimation of the RBE-weighted dose to the normal liver. The impact of applying a variable RBE (as compared to RBE  =  1.1) on the NTCP difference of the two fractionation regimens is case dependent. A variable RBE results in a slight increase in TCP difference. Variations in patient radiosensitivity increase when using a variable RBE.

Investigation on Patient/Compensator Scatter Factor for Monitor Unit Calculation in Proton Therapy

Purpose:

It is the goal of this study to use both Monte Carlo (MC) simulation and the pencil beam dose algorithm (PBA) in the treatment planning system to investigate Patient scatter factor (PSF) and Compensator scatter factor (CSF) for calibrating the dose per monitor unit (DMU) for a passive scattering proton therapy system.

Materials and Methods:

PSFs and CSFs for brain, lung, pancreas, and prostate treatment sites were calculated by using MC simulation and PBA from the treatment planning software to evaluate the agreement between the two.

Results:

This study shows that the CSF values are always greater than 1, with some reaching nearly 4% above unity, and depending strongly on the shape of the compensator. Monte Carlo and PBA-calculated CSF factors agree very well, with average differences below 1%. PSF values calculated in this study ranged from 0.919 to 1.023 and are largely dependent on the type of tissue heterogeneities in the treatment field. Monte Carlo and PBA-calculated PSF factors show differences, with the largest discrepancies seen in lung cases, with an average difference of 1.9%. It is also shown that dense bone will drive a PSF to values greater than unity, while large quantities of air decrease the PSF to below unity.

Conclusion:

We have showed that the compensator and patient anatomy can have a significant impact on clinical proton dose distribution. It is recommended that both Monte Carlo and treatment planning system should be used to take these factors into account in the final DMU calculation.

Helium CT: Monte Carlo simulation results for an ideal source and detector with comparison to proton CT

PURPOSE

To evaluate the accuracy of relative stopping power and spatial resolution of images reconstructed with simulated helium CT (HeCT) in comparison to proton CT (pCT).

METHODS

A Monte Carlo (MC) study with the TOPAS tool was performed to compare the accuracy of relative stopping power (RSP) reconstruction and spatial resolution of low-fluence HeCT to pCT, both using 200 MeV/u particles. An ideal setup consisting of a flat beam source and a totally absorbing energy-range detector was implemented to estimate the theoretically best achievable RSP accuracy for the calibration and reconstruction methods currently used for pCT. The phantoms imaged included a cylindrical water phantom with inserts of different materials, sizes, and positions, a Catphan phantom with a module containing high-contrast line pairs (CTP528) and a module with cylindrical inserts of different RSP (CTP404), as well as a voxelized 10-year-old female phantom. Dose to the cylindrical water phantom was also calculated. The RSP accuracy was studied for all phantoms except the CTP528 module. The latter was used for the estimation of the spatial resolution, evaluated as the modulation transfer function (MTF) at 10%.

RESULTS

An overall error under 0.5% was achieved for HeCT for the water phantoms with the different inserts, in all cases better than that for pCT, in some cases by a factor 3. The inserts in the CTP404 module were reconstructed with an average RSP accuracy of 0.3% for HeCT and 0.2% for pCT. Anatomic structures (brain, bones, air cavities, etc.) in the digitized head phantom were well recognizable and no artifacts were visible with both HeCT and pCT. The three main tissue materials (soft tissue, brain, and cranium) were well identifiable in the reconstructed RSP-volume distribution with both imaging modalities. Using 360 projection angles, the spatial resolution was 4 lp/cm for HeCT and 3 lp/cm for pCT. Generally, spatial resolution increased with the number of projection angles and was always higher for HeCT than for pCT for the same number of projections. When HeCT and pCT scan were performed to deliver the same dose in the phantom, the resolution for HeCT was higher than pCT.

CONCLUSION

MC simulations were used to compare HeCT and pCT image reconstruction. HeCT images had similar or better RSP accuracy and higher spatial resolution compared to pCT. Further investigation of the potential of helium ion imaging is warranted.

Time-resolved diode dosimetry calibration through Monte Carlo modeling for in vivo passive scattered proton therapy range verification

Purpose

Our group previously introduced an in vivo proton range verification methodology in which a silicon diode array system is used to correlate the dose rate profile per range modulation wheel cycle of the detector signal to the water‐equivalent path length (WEPL) for passively scattered proton beam delivery. The implementation of this system requires a set of calibration data to establish a beam‐specific response to WEPL fit for the selected ‘scout’ beam (a 1 cm overshoot of the predicted detector depth with a dose of 4 cGy) in water‐equivalent plastic. This necessitates a separate set of measurements for every ‘scout’ beam that may be appropriate to the clinical case. The current study demonstrates the use of Monte Carlo simulations for calibration of the time‐resolved diode dosimetry technique.

Methods

Measurements for three ‘scout’ beams were compared against simulated detector response with Monte Carlo methods using the Tool for Particle Simulation (TOPAS). The ‘scout’ beams were then applied in the simulation environment to simulated water‐equivalent plastic, a CT of water‐equivalent plastic, and a patient CT data set to assess uncertainty.

Results

Simulated detector response in water‐equivalent plastic was validated against measurements for ‘scout’ spread out Bragg peaks of range 10 cm, 15 cm, and 21 cm (168 MeV, 177 MeV, and 210 MeV) to within 3.4 mm for all beams, and to within 1 mm in the region where the detector is expected to lie.

Conclusion

Feasibility has been shown for performing the calibration of the detector response for three ‘scout’ beams through simulation for the time‐resolved diode dosimetry technique in passive scattered proton delivery.