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.

TOPAS: an innovative proton Monte Carlo platform for research and clinical applications.

PURPOSE: While Monte Carlo particle transport has proven useful in many areas (treatment head design, dose calculation, shielding design, and imaging studies) and has been particularly important for proton therapy (due to the conformal dose distributions and a finite beam range in the patient), the available general purpose Monte Carlo codes in proton therapy have been overly complex for most clinical medical physicists. The learning process has large costs not only in time but also in reliability. To address this issue, we developed an innovative proton Monte Carlo platform and tested the tool in a variety of proton therapy applications. METHODS: Our approach was to take one of the already-established general purpose Monte Carlo codes and wrap and extend it to create a specialized user-friendly tool for proton therapy. The resulting tool, TOol for PArticle Simulation (TOPAS), should make Monte Carlo simulation more readily available for research and clinical physicists. TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on computed tomography (CT) images, score dose, fluence, etc., save and restart a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. A custom-designed TOPAS parameter control system was placed at the heart of the code to meet requirements for ease of use, reliability, and repeatability without sacrificing flexibility. RESULTS: We built and tested the TOPAS code. We have shown that the TOPAS parameter system provides easy yet flexible control over all key simulation areas such as geometry setup, particle source setup, scoring setup, etc. Through design consistency, we have insured that user experience gained in configuring one component, scorer or filter applies equally well to configuring any other component, scorer or filter. We have incorporated key lessons from safety management, proactively removing possible sources of user error such as line-ordering mistakes. We have modeled proton therapy treatment examples including the UCSF eye treatment head, the MGH stereotactic alignment in radiosurgery treatment head and the MGH gantry treatment heads in passive scattering and scanning modes, and we have demonstrated dose calculation based on patient-specific CT data. Initial validation results show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D. CONCLUSIONS: We have demonstrated TOPAS accuracy and usability in a variety of proton therapy setups. As we are preparing to make this tool freely available for researchers in medical physics, we anticipate widespread use of this tool in the growing proton therapy community.

Spatiotemporal optimisation of prostate intensity modulated proton therapy (IMPT) treatments.

Objective.In intensity modulated particle therapy (IMPT), the adoption of spatially and temporally heterogeneous dose distributions allows to decouple the fractionation scheme from the patient anatomy, so that an hypofractionated schedule can be selectively created inside the tumour, while simultaneously exploiting the fractionation effect in the healthy tissues. In this paper, the authors show the reproducibility of the method on a set of prostate patients, quantifying the dependencies of the achievable benefit with respect to conventional and hypofractionated schemes and the sensitivity of the method to setup errors and range uncertainty.Approach.On a cohort of 9 patients, non-uniform IMPT plans were optimised and compared to conventional and hypofractionated schedules. For each patient, the comparison of the three strategies has been based on the output of the cost function used to optimise the treatments. The analysis has been repeated considering differentα/ßratios for the tumour, namely 1.5, 3 and 4.5 Gy. For a single patient, setup errors and beam range uncertainty have been analysed: the plans, for each optimisation strategy, have been iteratively forward planned 500 times with randomly varying the patient position in each fraction, and 200 times for systematic range shift.Main results.An average 10% benefit has been shown for the lowestα/ßratio considered for the tumour, where the non-uniform schedule generally converges to hypofractionation; the benefit decreases to 5%-7% for higherα/ßratios, for which the non-uniform schedule always showed better outcomes with respect to the other fractionation schedules. An increased sensitivity to uncertainty, especially for setup errors, has been shown, which can be associated to the spatial non-uniformity of the dose distributions peculiar of the spatiotemporal plans.Significance.This work represents the first investigation of spatiotemporal fractionation for prostate cancer and the beginning of further investigations before clinical implementation can be considered.

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.

Direct absorbed dose to water determination based on water calorimetry in scanning proton beam delivery.

PURPOSE: The aim of this manuscript is to describe the direct measurement of absolute absorbed dose to water in a scanned proton radiotherapy beam using a water calorimeter primary standard. METHODS: The McGill water calorimeter, which has been validated in photon and electron beams as well as in HDR 192Ir brachytherapy, was used to measure the absorbed dose to water in double scattering and scanning proton irradiations. The measurements were made at the Massachusetts General Hospital proton radiotherapy facility. The correction factors in water calorimetry were numerically calculated and various parameters affecting their magnitude and uncertainty were studied. The absorbed dose to water was compared to that obtained using an Exradin T1 Chamber based on the IAEA TRS-398 protocol. RESULTS: The overall 1-sigma uncertainty on absorbed dose to water amounts to 0.4% and 0.6% in scattered and scanned proton water calorimetry, respectively. This compares to an overall uncertainty of 1.9% for currently accepted IAEA TRS-398 reference absorbed dose measurement protocol. The absorbed dose from water calorimetry agrees with the results from TRS-398 well to within 1-sigma uncertainty. CONCLUSIONS: This work demonstrates that a primary absorbed dose standard based on water calorimetry is feasible in scattered and scanned proton beams.

Systematic analysis of biological and physical limitations of proton beam range verification with offline PET/CT scans.

The clinical use of offline positron emission tomography/computed tomography (PET/CT) scans for proton range verification is currently under investigation at the Massachusetts General Hospital (MGH). Validation is achieved by comparing measured activity distributions, acquired in patients after receiving one fraction of proton irradiation, with corresponding Monte Carlo (MC) simulated distributions. Deviations between measured and simulated activity distributions can either reflect errors during the treatment chain from planning to delivery or they can be caused by various inherent challenges of the offline PET/CT verification method. We performed a systematic analysis to assess the impact of the following aspects on the feasibility and accuracy of the offline PET/CT method: (1) biological washout processes, (2) patient motion, (3) Hounsfield unit (HU) based tissue classification for the simulation of the activity distributions and (4) tumor site specific aspects. It was found that the spatial reproducibility of the measured activity distributions is within 1 mm. However, the feasibility of range verification is restricted to a limited amount of positions and tumor sites. Washout effects introduce discrepancies between the measured and simulated ranges of about 4 mm at positions where the proton beam stops in soft tissue. Motion causes spatial deviations of up to 3 cm between measured and simulated activity distributions in abdominopelvic tumor cases. In these later cases, the MC simulated activity distributions were found to be limited to about 35% accuracy in absolute values and about 2 mm in spatial accuracy depending on the correlativity of HU into the physical and biological parameters of the irradiated tissue. Besides, for further specific tumor locations, the beam arrangement, the limited accuracy of rigid co-registration and organ movements can prevent the success of PET/CT range verification. All the addressed factors explain why the proton beam range can only be verified within an accuracy of 1-2 mm in low-perfused bony structures of head and neck patients for which an accurate co-registration of predominant bony anatomy is possible, as shown previously. However, most of the limitations of the current approach are conquerable. By implementing technological and methodological improvements like the use of in-room PET scanners, PET measurements could soon be used to provide proton range verification in clinical routine.

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.

Design and testing of a simulation framework for dosimetric motion studies integrating an anthropomorphic computational phantom into four-dimensional Monte Carlo.

We have designed a simulation framework for motion studies in radiation therapy by integrating the anthropomorphic NCAT phantom into a 4D Monte Carlo dose calculation engine based on DPM. Representing an artifact-free environment, the system can be used to identify class solutions as a function of geometric and dosimetric parameters. A pilot dynamic conformal study for three lesions ( approximately 2.0 cm) in the right lung was performed (70 Gy prescription dose). Tumor motion changed as a function of tumor location, according to the anthropomorphic deformable motion model. Conformal plans were simulated with 0 to 2 cm margin for the aperture, with additional 0.5 cm for beam penumbra. The dosimetric effects of intensity modulated radiotherapy (IMRT) vs. conformal treatments were compared in a static case. Results show that the Monte Carlo simulation framework can model tumor tracking in deformable anatomy with high accuracy, providing absolute doses for IMRT and conformal radiation therapy. A target underdosage of up to 3.67 Gy (lower lung) was highlighted in the composite dose distribution mapped at exhale. Such effects depend on tumor location and treatment margin and are affected by lung deformation and ribcage motion. In summary, the complexity in the irradiation of moving targets has been reduced to a controlled simulation environment, where several treatment options can be accurately modeled and quantified The implemented tools will be utilized for extensive motion study in lung/liver irradiation.

Quantitative assessment of the physical potential of proton beam range verification with PET/CT.

A recent clinical pilot study demonstrated the feasibility of offline PET/CT range verification for proton therapy treatments. In vivo PET measurements are challenged by blood perfusion, variations of tissue compositions, patient motion and image co-registration uncertainties. Besides these biological and treatment specific factors, the accuracy of the method is constrained by the underlying physical processes. This phantom study distinguishes physical factors from other factors, assessing the reproducibility, consistency and sensitivity of the PET/CT range verification method. A spread-out Bragg-peak (SOBP) proton field was delivered to a phantom consisting of poly-methyl methacrylate (PMMA), lung and bone equivalent material slabs. PET data were acquired in listmode at a commercial PET/CT scanner available within 10 min walking distance from the proton therapy unit. The measured PET activity distributions were compared to simulations of the PET signal based on Geant4 and FLUKA Monte Carlo (MC) codes. To test the reproducibility of the measured PET signal, data from two independent measurements at the same geometrical position in the phantom were compared. Furthermore, activation depth profiles within identical material arrangements but at different positions within the irradiation field were compared to test the consistency of the measured PET signal. Finally, activation depth profiles through air/lung, air/bone and lung/bone interfaces parallel as well as at 6 degrees to the beam direction were studied to investigate the sensitivity of the PET/CT range verification method. The reproducibility and the consistency of the measured PET signal were found to be of the same order of magnitude. They determine the physical accuracy of the PET measurement to be about 1 mm. However, range discrepancies up to 2.6 mm between two measurements and range variations up to 2.6 mm within one measurement were found at the beam edge and at the edge of the field of view (FOV) of the PET scanner. PET/CT range verification was found to be able to detect small range modifications in the presence of complex tissue inhomogeneities. This study indicates the physical potential of the PET/CT verification method to detect the full-range characteristic of the delivered dose in the patient.

Online adaption approaches for intensity modulated proton therapy for head and neck patients based on cone beam CTs and Monte Carlo simulations.

To develop an online plan adaptation algorithm for intensity modulated proton therapy (IMPT) based on fast Monte Carlo dose calculation and cone beam CT (CBCT) imaging. A cohort of ten head and neck cancer patients with an average of six CBCT scans were studied. To adapt the treatment plan to the new patient geometry, contours were propagated to the CBCTs with a vector field (VF) calculated with deformable image registration between the CT and the CBCTs. Within the adaptive planning algorithm, beamlets were shifted following the VF at their distal falloff and raytraced in the CBCT to adjust their energies, creating a geometrically adapted plan. Four geometric adaptation modes were studied: unconstrained geometric shifts (Free), isocenter shift (Iso), a range shifter (RS), or isocenter shift and range shifter (Iso-RS). After evaluation of the geometrical adaptation, the weights of a selected subset of beamlets were automatically tuned using MC-generated influence matrices to fulfill the original plan requirements. All beamlet calculations were done with a fast Monte Carlo running on a GPU (graphics processing unit). Geometrical adaptation alone only worked with small anatomy changes. The weight-tuned adaptation worked for every fraction, with the Free and Iso modes performing similarly and being superior than the two range shifters modes. The mean V95 and V107 were 99.4 ± 0.9 and 6.4% ± 4.7% in the Free mode with weight tuning. The calculation time per fraction was ~5 min, but further task parallelization could reduce it to ~1-2 min for delivery adaptation right after patient setup. An online adaptation algorithm was developed that significantly improved the treatment quality for inter-fractional geometry changes. Clinical implementation of the algorithm would allow delivery adaptation right before treatment and thus allow planning margin reductions for IMPT.

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.

Effects of organ motion on IMRT treatments with segments of few monitor units.

Interplay between organ (breathing) motion and leaf motion has been shown in the literature to have a small dosimetric impact for clinical conditions (over a 30 fraction treatment). However, previous studies did not consider the case of treatment beams made up of many few-monitor-unit (MU) segments, where the segment delivery time (1-2 s) is of the order of the breathing period (3-5 s). In this study we assess if breathing compromises the radiotherapy treatment with IMRT segments of low number of MUs. We assess (i) how delivered dose varies, from patient to patient, with the number of MU per segment, (ii) if this delivered dose is identical to the average dose calculated without motion over the path of the motion, and (iii) the impact of the daily variation of the delivered dose as a function of MU per segment. The organ motion was studied along two orthogonal directions, representing the left-right and cranial-caudal directions of organ movement for a patient setup in the supine position. Breathing motion was modeled as sin(x), sin4(x), and sin6(x), based on functions used in the literature to represent organ motion. Measurements were performed with an ionization chamber and films. For a systematic study of motion effects, a MATLAB simulation was written to model organ movement and dose delivery. In the case of a single beam made up of one single segment, the dose delivered to point in a moving target over 30 fractions can vary up to 20% and 10% for segments of 10 MU and 20 MU, respectively. This dose error occurs because the tumor spends most of the time near the edges of the radiation beam. In the case of a single beam made of multiple segments with low MU, we observed 2.4%, 3.3%, and 4.3% differences, respectively, for sin(x), sin4(x), and sin6(x) motion, between delivered dose and motion-averaged dose for points in the penumbra region of the beam and over 30 fractions. In approximately 5-10% of the cases, differences between the motion-averaged dose and the delivered 30-fraction dose could reach 6%, 8% and 10-12%, respectively for sin(x), sin4(x), and sin6(x) motion. To analyze a clinical IMRT beam, two patient plans were randomly selected. For one of the patients, the beams showed a likelihood of up to 25.6% that the delivered dose would deviate from the motion-averaged dose by more than 1%. For the second patient, there was a likelihood of up to 62.8% of delivering a dose that differs by more than 1% from the motion-averaged dose and a likelihood of up to approximately 30% for a 2% dose error. For the entire five-beam IMRT plan, statistical averaging over the beams reduces the overall dose error between the delivered dose and the motion-averaged dose. For both patients there was a likelihood of up to 7.0% and 33.9% that the dose error was greater than 1%, respectively. For one of the patients, there was a 12.6% likelihood of a 2% dose error. Daily intrafraction variation of the delivered dose of more than 10% is non-negligible and can potentially lead to biological effects. We observed [for sin(x), sin4(x), and sin6(x)] that below 10-15 MU leads to large daily variations of the order of 15-35%. Therefore, for small MU segments, non-negligible biological effects can be incurred. We conclude that for most clinical cases the effects may be small because of the use of many beams, it is desirable to avoid low-MU segments when treating moving targets. In addition, dose averaging may not work well for hypo-fractionation, where fewer fractions are used. For hypo-fractionation, PDF modeling of the tumor motion in IMRT optimization may not be adequate.

Clinical CT-based calculations of dose and positron emitter distributions in proton therapy using the FLUKA Monte Carlo code.

Clinical investigations on post-irradiation PET/CT (positron emission tomography/computed tomography) imaging for in vivo verification of treatment delivery and, in particular, beam range in proton therapy are underway at Massachusetts General Hospital (MGH). Within this project, we have developed a Monte Carlo framework for CT-based calculation of dose and irradiation-induced positron emitter distributions. Initial proton beam information is provided by a separate Geant4 Monte Carlo simulation modelling the treatment head. Particle transport in the patient is performed in the CT voxel geometry using the FLUKA Monte Carlo code. The implementation uses a discrete number of different tissue types with composition and mean density deduced from the CT scan. Scaling factors are introduced to account for the continuous Hounsfield unit dependence of the mass density and of the relative stopping power ratio to water used by the treatment planning system (XiO (Computerized Medical Systems Inc.)). Resulting Monte Carlo dose distributions are generally found in good correspondence with calculations of the treatment planning program, except a few cases (e.g. in the presence of air/tissue interfaces). Whereas dose is computed using standard FLUKA utilities, positron emitter distributions are calculated by internally combining proton fluence with experimental and evaluated cross-sections yielding 11C, 15O, 14O, 13N, 38K and 30P. Simulated positron emitter distributions yield PET images in good agreement with measurements. In this paper, we describe in detail the specific implementation of the FLUKA calculation framework, which may be easily adapted to handle arbitrary phase spaces of proton beams delivered by other facilities or include more reaction channels based on additional cross-section data. Further, we demonstrate the effects of different acquisition time regimes (e.g., PET imaging during or after irradiation) on the intensity and spatial distribution of the irradiation-induced beta+-activity signal for the cases of head and neck and para-spinal tumour sites.

Experimental assessment of proton dose calculation accuracy in inhomogeneous media.

PURPOSE: Proton therapy with Pencil Beam Scanning (PBS) has the potential to improve radiotherapy treatments. Unfortunately, its promises are jeopardized by the sensitivity of the dose distributions to uncertainties, including dose calculation accuracy in inhomogeneous media. Monte Carlo dose engines (MC) are expected to handle heterogeneities better than analytical algorithms like the pencil-beam convolution algorithm (PBA). In this study, an experimental phantom has been devised to maximize the effect of heterogeneities and to quantify the capability of several dose engines (MC and PBA) to handle these. METHODS: An inhomogeneous phantom made of water surrounding a long insert of bone tissue substitute (1×10×10 cm3) was irradiated with a mono-energetic PBS field (10×10 cm2). A 2D ion chamber array (MatriXX, IBA Dosimetry GmbH) lied right behind the bone. The beam energy was such that the expected range of the protons exceeded the detector position in water and did not attain it in bone. The measurement was compared to the following engines: Geant4.9.5, PENH, MCsquare, as well as the MC and PBA algorithms of RayStation (RaySearch Laboratories AB). RESULTS: For a γ-index criteria of 2%/2mm, the passing rates are 93.8% for Geant4.9.5, 97.4% for PENH, 93.4% for MCsquare, 95.9% for RayStation MC, and 44.7% for PBA. The differences in γ-index passing rates between MC and RayStation PBA calculations can exceed 50%. CONCLUSION: The performance of dose calculation algorithms in highly inhomogeneous media was evaluated in a dedicated experiment. MC dose engines performed overall satisfactorily while large deviations were observed with PBA as expected.

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.

Methodologies in the modeling of combined chemo-radiation treatments.

The variety of treatment options for cancer patients has increased significantly in recent years. Not only do we combine radiation with surgery and chemotherapy, new therapeutic approaches such as immunotherapy and targeted therapies are starting to play a bigger role. Physics has made significant contributions to radiation therapy treatment planning and delivery. In particular, treatment plan optimization using inverse planning techniques has improved dose conformity considerably. Furthermore, medical physics is often the driving force behind tumor control and normal tissue complication modeling. While treatment optimization and outcome modeling does focus mainly on the effects of radiation, treatment modalities such as chemotherapy are treated independently or are even neglected entirely. This review summarizes the published efforts to model combined modality treatments combining radiation and chemotherapy. These models will play an increasing role in optimizing cancer therapy not only from a radiation and drug dosage standpoint, but also in terms of spatial and temporal optimization of treatment schedules.

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.

Radiological protection in ion beam radiotherapy: practical guidance for clinical use of new technology.

Recently introduced technologies in radiotherapy have significantly improved the clinical outcome for patients. Ion beam radiotherapy, involving proton and carbon ion beams, provides excellent dose distributions in targeted tumours, with reduced doses to the surrounding normal tissues. However, careful treatment planning is required in order to maximise the treatment efficiency and minimise the dose to normal tissues. Radiation exposure from secondary neutrons and photons, particle fragments, and photons from activated materials should also be considered for radiological protection of the patient and medical staff. Appropriate maintenance is needed for the equipment and air in the treatment room, which may be activated by the particle beam and its secondary radiation. This new treatment requires complex procedures and careful adjustment of parameters for each patient. Therefore, education and training for the personnel involved in the procedure are essential for both effective treatment and patient protection. The International Commission on Radiological Protection (ICRP) has provided recommendations for radiological protection in ion beam radiotherapy in Publication 127 Medical staff should be aware of the possible risks resulting from inappropriate use and control of the equipment. They should also consider the necessary procedures for patient protection when new technologies are introduced into clinical practice.

Interpretation of proton relative biological effectiveness using lesion induction, lesion repair, and cellular dose distribution.

Phenomenological biophysical models have been successfully used to estimate the relative biological effectiveness (RBE) of ions. The predictive power of these models is limited because they require measured dose-response data that are not necessarily available for all clinically relevant end points. Furthermore, input parameters often lack mechanistic interpretation. In order to link RBE to more fundamental biological parameters we combine the concepts of two well-established biophysical models, i.e., the phenomenological "track structure" model and the more mechanistic "lethal lesion/potentially lethal lesion" (LPL) model. We parametrize a relation between RBE, dose homogeneity in the cell nucleus and induction rates for different lesion types. The macroscopic dose-response relationship is described in the LPL model and the microscopic, subcellular, relationship is determined by the local dose deposition pattern. The formalism provides a framework for a mechanistic interpretation of RBE values.