Tuning spatially fractionated radiotherapy dose profiles using the moiré effect.

Spatially Fractionated Radiotherapy (SFRT) has demonstrated promising potential in cancer treatment, combining the advantages of reduced post-radiation effects and enhanced local control rates. Within this paradigm, proton minibeam radiotherapy (pMBRT) was suggested as a new treatment modality, possibly producing superior normal tissue sparing to conventional proton therapy, leading to improvements in patient outcomes. However, an effective and convenient beam generation method for pMBRT, capable of implementing various optimum dose profiles, is essential for its real-world application. Our study investigates the potential of utilizing the moiré effect in a dual collimator system (DCS) to generate pMBRT dose profiles with the flexibility to modify the center-to-center distance (CTC) of the dose distribution in a technically simple way.We employ the Geant4 Monte Carlo simulations tool to demonstrate that the angle between the two collimators of a DCS can significantly impact the dose profile. Varying the DCS angle from 10 ∘ to 50 ∘ we could cover CTC ranging from 11.8 mm to 2.4 mm, respectively. Further investigations reveal the substantial influence of the multi-slit collimator's (MSC) physical parameters on the spatially fractionated dose profile, such as period (CTC), throughput, and spacing between MSCs. These findings highlight opportunities for precision dose profile adjustments tailored to specific clinical scenarios.The DCS capacity for rapid angle adjustments during the energy transition stages of a spot scanning system can facilitate dynamic alterations in the irradiation profile, enhancing dose contrast in normal tissues. Furthermore, its unique attribute of spatially fractionated doses in both lateral directions could potentially improve normal tissue sparing by minimizing irradiated volume. Beyond the realm of pMBRT, the dual MSC system exhibits remarkable versatility, showing compatibility with different types of beams (X-rays and electrons) and applicability across various SFRT modalities.Our study illuminates the dual MSC system's potential as an efficient and adaptable tool in the refinement of pMBRT techniques. By enabling meticulous control over irradiation profiles, this system may expedite advancements in clinical and experimental applications, thereby contributing to the evolution of SFRT strategies.

Treatment planning of scanned proton beams in RayStation.

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition.

PURPOSE: We present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models. METHODS: The model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit. RESULTS: For protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models. CONCLUSION: These results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system.

BACKGROUND: The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS. PURPOSE: This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LETd ) scoring and (2) physical dose filtration based on LET for future LET-based treatment plan evaluation and optimization studies. METHODS: The LETd scoring and LET-based dose filtering (in which the deposited dose can be separated into the dose below and above the user specified LET threshold) functionalities for carbon ions in the research version RayStation (RS) 9A-IonPG TPS (RaySearch Laboratories, Sweden) were benchmarked against GATE/Geant4 simulations. Pristine Bragg peaks (BPs) and cuboid targets, positioned at different depths in a homogeneous water phantom and a setup with heterogeneity were used for this study. RESULTS: For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LETd difference was less than 1 keV/ µ $\umu$ m (3.5%) in the plateau and target and less than 2 keV/ µ $\umu$ m (8.3%) in the fragmentation tail. The maximum local differences were 4 and 6 keV/ µ $\umu$ m, respectively. The mean absolute (and relative) physical dose differences for both low- and high-LET doses were less than 1 cGy (1.5%) in the plateau, target and tail with a maximum absolute difference of 2 cGy. CONCLUSIONS: No computation error was found in the tested functionalities except for LETd in lateral direction outside the target, showing the limitation of the implemented monochrome model in the tested TPS version.

Measurement-based validation of a commercial Monte Carlo dose calculation algorithm for electron beams.

PURPOSE: This work presents the clinical validation of RayStation's electron Monte Carlo code by the use of diodes and plane parallel radiation detectors in homogenous and heterogeneous tissues. Results are evaluated against internationally accepted criteria. METHODS: The Monte Carlo-based electron beam dose calculation code was validated using diodes, air- and liquid-filled parallel radiation detectors on an Elekta linac with beam energies of 4, 6, 8, 10, and 12 MeV. Treatment setups with varying source-to-skin distances, different applicators, various cutouts, and oblique beam incidences were addressed, together with dose prediction behind lung-, air-, and bone-equivalent inserts. According to NCS (Netherlands Commission for Radiation Dosimetry) report 15 for nonstandard treatment setups, a dose agreement of 3% in the δ1 region (high-dose region around Zref ), a distance-to-agreement (DTA) of 3 mm or a dose agreement of 10% in the δ2 region (regions with high-dose gradients), and 4% in the δ4 region (photon tail/low-dose region) were applied. During validation, clinical routine settings of 2 × 2 × 2-mm3 dose voxels and a statistically dose uncertainty of 0.6% (250 000 histories/cm2 ) were used. RESULTS: RayStation's electron Monte Carlo code dose prediction was able to achieve the tolerances of NCS report 15. Output predictions as a function of the SSD improve with energy and applicator size. Cutout data revealed no field size or energy dependence on the accuracy of the dose prediction. Excellent agreement for the oblique incidence data was achieved and a maximum of one voxel difference was obtained for the DTA behind heterogeneous inserts. CONCLUSIONS: The accuracy of RayStation's Monte Carlo-based electron beam dose prediction for Elekta accelerators is confirmed for clinical treatment planning that is not only performed within an acceptable timeframe in terms of the number of histories but also addresses for homogenous and heterogeneous media.

Handling of beam spectra in training and application of proton RBE models.

Published data from cell survival experiments are frequently used as training data for models of proton relative biological effectiveness (RBE). The publications rarely provide full information about the primary particle spectrum of the used beam, or its content of heavy secondary particles. The purpose of this paper is to assess to what extent heavy secondary particles may have been present in published cell survival experiments, and to investigate the impact of non-primary protons for RBE calculations in treatment planning. We used the Monte Carlo code Geant4 to calculate the occurrence of non-primary protons and heavier secondary particles for clinical protons beams in water for four incident energies in the [100, 250] MeV interval. We used the resulting spectra together with a conservative RBE parameterization and an RBE model to map both the rise of RBE at the beam entry surface due to heavy secondary particle buildup, and the difference in estimated RBE if non-primary protons are included or not in the beam quality metric. If included, non-primary protons cause a difference of 2% of the RBE in the plateau region of an spread out Bragg peak and 1% in the Bragg peak. Including non-primary protons specifically for RBE calculations will consequently have a negligible impact and can be ignored. A buildup distance in water of one millimeter was sufficient to reach an equilibrium state of RBE for the four incident energies selected. For the investigated experimental data, 83 out of the 86 data points were found to have been determined with at least that amount of buildup material. Hence, RBE model training data should be interpreted to include the contribution of heavy secondaries.

A systematic review on the usage of averaged LET in radiation biology for particle therapy.

Linear Energy Transfer (LET) is widely used to express the radiation quality of ion beams, when characterizing the biological effectiveness. However, averaged LET may be defined in multiple ways, and the chosen definition may impact the resulting reported value. We review averaged LET definitions found in the literature, and quantify which impact using these various definitions have for different reference setups. We recorded the averaged LET definitions used in 354 publications quantifying the relative biological effectiveness (RBE) of hadronic beams, and investigated how these various definitions impact the reported averaged LET using a Monte Carlo particle transport code. We find that the kind of averaged LET being applied is, generally, poorly defined. Some definitions of averaged LET may influence the reported averaged LET values up to an order of magnitude. For publications involving protons, most applied dose averaged LET when reporting RBE. The absence of what target medium is used and what secondary particles are included further contributes to an ill-defined averaged LET. We also found evidence of inconsistent usage of averaged LET definitions when deriving LET-based RBE models. To conclude, due to commonly ill-defined averaged LET and to the inherent problems of LET-based RBE models, averaged LET may only be used as a coarse indicator of radiation quality. We propose a more rigorous way of reporting LET values, and suggest that ideally the entire particle fluence spectra should be recorded and provided for future RBE studies, from which any type of averaged LET (or other quantities) may be inferred.

Characteristics of very high-energy electron beams for the irradiation of deep-seated targets.

PURPOSE: Driven by advances in accelerator technology and the potential of exploiting the FLASH effect for the treatment of deep-seated targets (>5 cm), there is an active interest in the construction of devices to deliver very high-energy electron (VHEE) beams for radiation therapy. The application of novel VHEE devices, however, requires an assessment of the tradeoffs between the different beam parameter choices including beam energies, beam divergences, and maximal field sizes. This study systematically examines the dosimetric beam properties of VHEE beams, determining their clinical usefulness while marking their limits of applications for different beam configurations. METHODS: We performed Monte Carlo simulations of the dose distributions of electron beams for different energies (25-250 MeV), source-to-surface distances (SSD) (50 cm, 100 cm, parallel), and field sizes (2 cm2  × 2 cm2 to 15 cm2  × 15 cm2 ) in water using a research version of the RayStation treatment planning system (RaySearch Labs 9A IONPG). The beam was simulated using a monoenergetic point source and perfect collimation. Central axis percentage depth dose (PDD) and transverse dose profiles at multiple depths were evaluated and compared to those of MV photon beams. Profile characteristics including therapeutic range (TR) at 90%, proximal fall-off (PFO) at 90%, lateral penumbra (LP) at 90%-10%, and field width (FW) at 90% were obtained. RESULTS: Very high-energy electrons beams with SSD 100 cm and parallel beams (infinite SSD) exhibit a linear to near-linear increase of TR as a function of energy in the simulated energy range and reach values well beyond the typical depths of lesions encountered in clinics (<20 cm). Their TR show a marked field size dependence only for field sizes <10 cm2  × 10 cm2 . For VHEE beams with SSD 50 cm, TR are largely reduced (4-8 cm). For beam energies >150 MeV with large SSD (>100 cm), for many configurations, there is no substantial difference in PDD when adding an opposed beam. This may potentially reduce the number of VHEE beams needed for treatment by a factor of two compared to a treatment using lower energies and lower SSD. In order to cover deep-seated targets homogeneously, VHEE devices with a parallel beam must provide a maximum field size up to several centimeters larger than the tumor size. For the investigated diverging beams, there is not such a significant field width reduction with depth for larger fields as it is compensated by divergence. Penumbrae of VHEE beams are smaller than those of clinical MV photon beams for lower depths (<5 cm) but increase quickly for larger depths. There is only a relatively small dependence of penumbra on the SSD of the beam. CONCLUSIONS: The findings presented in this study assess the performance of VHEE beams and offer a first estimate of treatment indications and tradeoffs for a given design of a VHEE device. SSD >100 cm results in clinically more favorable PDD. Beam energies of 100 MeV and above are needed to cover common tumors (5-15 cm in-depth) conformally. Higher energies provide an additional benefit specifically for small and deep-seated lesions due to their reduced lateral penumbrae.

Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157.

Dose calculation plays an important role in the accuracy of radiotherapy treatment planning and beam delivery. The Monte Carlo (MC) method is capable of achieving the highest accuracy in radiotherapy dose calculation and has been implemented in many commercial systems for radiotherapy treatment planning. The objective of this task group was to assist clinical physicists with the potentially complex task of acceptance testing and commissioning MC-based treatment planning systems (TPS) for photon and electron beam dose calculations. This report provides an overview on the general approach of clinical implementation and testing of MC-based TPS with a specific focus on models of clinical photon and electron beams. Different types of beam models are described including those that utilize MC simulation of the treatment head and those that rely on analytical methods and measurements. The trade-off between accuracy and efficiency in the various source-modeling approaches is discussed together with guidelines for acceptance testing of MC-based TPS from the clinical standpoint. Specific recommendations are given on methods and practical procedures to commission clinical beam models for MC-based TPS.

Validation of linear energy transfer computed in a Monte Carlo dose engine of a commercial treatment planning system.

The relative biological effectiveness (RBE) of protons is highly variable and difficult to quantify. However, RBE is related to the local ionization density, which can be related to the physical measurable dose weighted linear energy transfer (LETD). The aim of this study was to validate the LETD calculations for proton therapy beams implemented in a commercially available treatment planning system (TPS) using microdosimetry measurements and independent LETD calculations (Open-MCsquare (MCS)). The TPS (RayStation v6R) was used to generate treatment plans on the CIRS-731-HN anthropomorphic phantom for three anatomical sites (brain, nasopharynx, neck) for a spherical target (Ø = 5 cm) with uniform target dose to calculate the LETD distribution. Measurements were performed at the University Medical Center Groningen proton therapy center (Proteus Plus, IBA) using a µ +-probe utilizing silicon on insulator microdosimeters capable of detecting lineal energies as low as 0.15 keV µm-1 in tissue. Dose averaged mean lineal energy [Formula: see text] depth-profiles were measured for 70 and 130 MeV spots in water and for the three treatment plans in water and an anthropomorphic phantom. The [Formula: see text] measurements were compared to the LETD calculated in the TPS and MCS independent dose calculation engine. D · [Formula: see text] was compared to D · LETD in terms of a gamma-index with a distance-to-agreement criteria of 2 mm and increasing dose difference criteria to determine the criteria for which a 90% pass rate was accomplished. Measurements of D · [Formula: see text] were in good agreement with the D · LETD calculated in the TPS and MCS. The 90% passing rate threshold was reached at different D · LETD difference criteria for single spots (TPS: 1% MCS: 1%), treatment plans in water (TPS: 3% MCS: 6%) and treatment plans in an anthropomorphic phantom (TPS: 6% MCS: 1%). We conclude that D · LETD calculations accuracy in the RayStation TPS and open MCSquare are within 6%, and sufficient for clinical D · LETD evaluation and optimization. These findings remove an important obstacle in the road towards clinical implementation of D · LETD evaluation and optimization of proton therapy treatment plans. Novelty and significance The dose weighed linear energy transfer (LETD) distribution can be calculated for proton therapy treatment plans by Monte Carlo dose engines. The relative biological effectiveness (RBE) of protons is known to vary with the LETD distribution. Therefore, there exists a need for accurate calculation of clinical LETD distributions. Previous LETD validations have focused on general purpose Monte Carlo dose engines which are typically not used clinically. We present the first validation of mean lineal energy [Formula: see text] measurements of the LETD against calculations by the Monte Carlo dose engines of the Raystation treatment planning system and open MCSquare.

Clinical examination of proton pencil beam scanning on a moving anthropomorphic lung phantom.

The objective of this study was to examine the use of proton pencil beam scanning for the treatment of moving lung tumors. A single-field uniform dose proton pencil beam scanning (PBS) plan was generated for the standard thorax phantom designed by the Imaging and Radiation Oncology Core (IROC) Houston QA Center. Robust optimization, including range and setup uncertainties as well as volumetric repainting, was used for the plan. Patient-specific quality assurance (QA) measurements were performed using both a water tank and a custom heterogeneous QA phantom. A custom moving phantom was used to find the optimal number of volumetric repainting. Both analytical and Monte Carlo (MC) algorithms were used for dose calculation and their accuracies were compared with actual measurements. A single ionization chamber, a 2-dimensional ionization chamber array, thermoluminescent dosimeters (TLDs), and films were used for dose measurements. The optimal number of volumetric repainting was found to be 4 times in our system. The mean dose overestimations on a moving target by analytical and MC algorithms based on a time-averaged computed tomography (CT) image of the phantom were found to be 4.8% and 2.4%, respectively. The mean gamma indexes for analytical and MC algorithms were 91% and 96%, respectively. The MC dose algorithm calculation was found to have a better agreement with measurements compared with the analytical algorithm. When treating moving lung tumors using proton PBS, the techniques of robust optimization, volumetric repainting, and MC dose calculation were found effective. Extra care needs to be taken when an analytical dose calculation algorithm is used.

Introducing Proton Track-End Objectives in Intensity Modulated Proton Therapy Optimization to Reduce Linear Energy Transfer and Relative Biological Effectiveness in Critical Structures.

PURPOSE: We propose the use of proton track-end objectives in intensity modulated proton therapy (IMPT) optimization to reduce the linear energy transfer (LET) and the relative biological effectiveness (RBE) in critical structures. METHODS AND MATERIALS: IMPT plans were generated for 3 intracranial patient cases (1.8 Gy (RBE) in 30 fractions) and 3 head-and-neck patient cases (2 Gy (RBE) in 35 fractions), assuming a constant RBE of 1.1. Two plans were generated for each patient: (1) physical dose objectives only (DOSEopt) and (2) same dose objectives as the DOSEopt plan, with additional proton track-end objectives (TEopt). The track-end objectives penalized protons stopping in the risk volume of choice. Dose evaluations were made using a RBE of 1.1 and the LET-dependent Wedenberg RBE model, together with estimates of normal tissue complication probabilities (NTCPs). In addition, the distributions of proton track-ends and dose-average LET (LETd) were analyzed. RESULTS: The TEopt plans reduced the mean LETd in the critical structures studied by an average of 37% and increased the mean LETd in the primary clinical target volume (CTV) by an average of 23%. This was achieved through a redistribution of the proton track-ends, concurrently keeping the physical dose distribution virtually unchanged compared to the DOSEopt plans. This resulted in substantial RBE-weighted dose (DRBE) reductions, allowing the TEopt plans to meet all clinical goals for both RBE models and reduce the NTCPs by 0 to 19 percentage points compared to the DOSEopt plans, assuming the Wedenberg RBE model. The DOSEopt plans met all clinical goals assuming a RBE of 1.1 but failed 10 of 19 normal tissue goals assuming the Wedenberg RBE model. CONCLUSIONS: Proton track-end objectives allow for LETd reductions in critical structures without compromising the physical target dose. This approach permits the lowering of DRBE and NTCP in critical structures, independent of the variable RBE model used, and it could be introduced in clinical practice without changing current protocols based on the constant RBE of 1.1.

Toward automated and personalized organ dose determination in CT examinations - A comparison of two tissue characterization models for Monte Carlo organ dose calculation with a Therapy Planning System.

PURPOSE: Computed tomography (CT) is a versatile tool in diagnostic radiology with rapidly increasing number of examinations per year globally. Routine adaption of the exposure level for patient anatomy and examination protocol cause the patients' exposures to become diversified and harder to predict by simple methods. To facilitate individualized organ dose estimates, we explore the possibility to automate organ dose calculations using a radiotherapy treatment planning system (TPS). In particular, the mapping of CT number to elemental composition for Monte Carlo (MC) dose calculations is investigated. METHODS: Organ dose calculations were done for a female thorax examination test case with a TPS (Raystation™, Raysearch Laboratories AB, Stockholm, Sweden) utilizing a MC dose engine with a CT source model presented in a previous study. The TPS's inherent tissue characterization model for mapping of CT number to elemental composition of the tissues was calibrated using a phantom with known elemental compositions and validated through comparison of MC calculated dose with dose measured with Thermo Luminescence Dosimeters (TLD) in an anthropomorphic phantom. Given the segmentation tools of the TPS, organ segmentation strategies suitable for automation were analyzed for high contrast organs, utilizing CT number thresholding and model-based segmentation, and for low contrast organs utilizing water replacements in larger tissue volumes. Organ doses calculated with a selection of organ segmentation methods in combination with mapping of CT numbers to elemental composition (RT model), normally used in radiotherapy, were compared to a tissue characterization model with organ segmentation and elemental compositions defined by replacement materials [International Commission on Radiological Protection (ICRP) model], frequently favored in imaging dosimetry. RESULTS: The results of the validation with the anthropomorphic phantom yielded mean deviations from the dose to water calculated with the RT and ICRP model as measured with TLD of 1.1% and 1.5% with maximum deviations of 6.1% and 8.7% respectively over all locations in the phantom. A strategy for automated organ segmentation was evaluated for two different risk organ groups, that is, low contrast soft organs and high contrast organs. The relative deviation between organ doses calculated with the RT model and with the ICRP model varied between 0% and 20% for the thorax/upper abdomen risk organs. CONCLUSIONS: After calibration, the RT model in the TPS provides accurate MC dose results as compared to measurements with TLD and the ICRP model. Dosimetric feasible segmentation of the risk organs for a female thorax demonstrates a possibility for automation using the segmentation tool available in a TPS for high contrast organs. Low contrast soft organs can be represented by water volumes, but organ dose to the esophagus and thyroid must be determined using standardized organ shapes. The uncertainties of the organ doses are small compared to the overall uncertainty, at least an order of magnitude larger, in the estimates of lifetime attributable risk (LAR) based on organ doses. Large-scale and automated individual organ dose calculations could provide an improvement in cancer incidence estimates from epidemiological studies.

Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness.

BACKGROUND: Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma. METHODS: Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan. RESULTS: Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures. CONCLUSIONS: MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.

Source modeling for Monte Carlo dose calculation of CT examinations with a radiotherapy treatment planning system.

PURPOSE: Radiation dose to patients undergoing examinations with Multislice Computed Tomography (MSCT) as well as Cone Beam Computed Tomography (CBCT) is a matter of concern. Risk management could benefit from efficient replace rational dose calculation tools. The paper aims to verify MSCT dose calculations using a Treatment Planning System (TPS) for radiotherapy and to evaluate four different variations of bow-tie filter characterizations for the beam model used in the dose calculations. METHODS: A TPS (RayStation™, RaySearch Laboratories, Stockholm, Sweden) was configured to calculate dose from a MSCT (GE Healthcare, Wauwatosa, WI, USA). The x-ray beam was characterized in a stationary position the by measurements of the Half-Value Layer (HVL) in aluminum and kerma along the principal axes of the isocenter plane perpendicular to the beam. A Monte Carlo source model for the dose calculation was applied with four different variations on the beam-shaping bow-tie filter, taking into account the different degrees of HVL information but reconstructing the measured kerma distribution after the bow-tie filter by adjusting the photon sampling function. The resulting dose calculations were verified by comparison with measurements in solid water as well as in an anthropomorphic phantom. RESULTS: The calculated depth dose in solid water as well as the relative dose profiles was in agreement with the corresponding measured values. Doses calculated in the anthropomorphic phantom in the range 26-55 mGy agreed with the corresponding thermo luminescence dosimeter (TLD) measurements. Deviations between measurements and calculations were of the order of the measurement uncertainties. There was no significant difference between the different variations on the bow-tie filter modeling. CONCLUSIONS: Under the assumption that the calculated kerma after the bow-tie filter replicates the measured kerma, the central specification of the HVL of the x-ray beam together with the kerma distribution can be used to characterize the beam. Thus, within the limits of the study, a flat bow-tie filter with an HVL specified by the vendor suffices to calculate the dose distribution. The TPS could be successfully configured to replicate the beam movement and intensity modulation of a spiral scan with dose modulation, on the basis of the specifications available in the metadata of the digital images and the log file of the CT.

Comparison of conventional inserts and an add-on electron MLC for chest wall irradiation of left-sided breast cancer.

BACKGROUND: Collimation of irregularly shaped clinical electron beams is currently based on electron inserts made of low melting point alloys. The present investigation compares a conventional electron applicator with insert and add-on eMLC-based dose distributions in the postoperative chest wall irradiation of left-sided breast cancer. MATERIAL AND METHODS: Voxel Monte Carlo++ (VMC++) calculated dose distributions related to electron fields were compared with 10 left-sided breast cancer patients after radical mastectomy. The prescription dose was 50 Gy at a build-up maximum. The same dose was prescribed for the ipsilateral axillary, parasternal and supraclavicular lymph nodes that were treated with photons and calculated with a pencil beam algorithm. The insert beams were shaped with 1.5 cm thick Wood's metal electron inserts in an electron applicator of a Varian 2100 C/D linac. Doses for the eMLC-shaped beams were calculated for an eMLC prototype with 2 cm thick and 5 mm wide steel leaves. The same collimator-to-surface distance (CSD) of 5.8 cm was used for both collimators. RESULTS: The mean PTV dose was slightly higher for the eMLC plans (50.7 vs 49.5 Gy, p<0.001, respectively). The maximum doses assessed by D5% for the eMLC and insert were 60.9 and 59.1 Gy (p<0.001). The difference was due to the slightly higher doses near the field edges for the eMLC. The left lung V20 volumes were 34.5% and 34.0% (p<0.001). There was only a marginal difference in heart doses. DISCUSSION: Despite a slight increase of maximum dose in PTV the add-on electron MLC for chest wall irradiation results in practically no differences in dose distributions compared with the present insert-based collimation.

Parametrization and application of scatter kernels for modelling scanned proton beam collimator scatter dose.

Collimators are routinely used in proton radiotherapy to laterally confine the field and improve the penumbra. Collimator scatter contributes up to 15% of the local dose and is therefore important to include in treatment planning dose calculation. We present a method for reconstruction of the collimator scatter phase space based on the parametrization of pre-calculated scatter kernels. Collimator scatter distributions, generated by the Monte Carlo (MC) package GEANT4.8.2, were scored differential in direction and energy. The distributions were then parametrized so as to enable a fast reconstruction by sampling. MC calculated dose distributions in water based on the parametrized phase space were compared to full MC simulations that included the collimator in the simulation geometry, as well as to experimental data. The experiments were performed at the scanned proton beam line at the The Svedberg Laboratory (TSL) in Uppsala, Sweden. Dose calculations using the parametrization of this work and the full MC for isolated typical cases of collimator scatter were compared by means of the gamma index. The result showed that in total 96.7% (99.3%) of the voxels fulfilled the gamma 2.0%/2.0 mm (3.0%/3.0 mm) criterion. The dose distribution for a collimated field was calculated based on the phase space created by the collimator scatter model incorporated into the generation of the phase space of a scanned proton beam. Comparing these dose distributions to full MC simulations, including particle transport in the MLC, yielded that in total for 18 different collimated fields, 99.1% of the voxels satisfied the gamma 1.0%/1.0 mm criterion and no voxel exceeded the gamma 2.6%/2.6 mm criterion. The dose contribution of collimator scatter along the central axis as predicted by the model showed good agreement with experimental data.

Experimental test of Monte Carlo proton transport at grazing incidence in GEANT4, FLUKA and MCNPX.

The ability of the Monte Carlo (MC) particle transport codes GEANT4.8.1 and GEANT4.8.2, FLUKA2006 and MCNPX2.4.0 to model proton transport at grazing incidence onto tungsten blocks has been tested and compared to experimental measurements. The test geometry consisted of a narrow proton beam of two energies, 98 MeV and 180 MeV, impinging on a thick tungsten alloy block at grazing incidence. The distribution of forward out-scatter from the tungsten alloy block was measured with a fluorescent screen viewed with a CCD camera via a mirror. In the MC simulations, the experimental setup was modelled and the dose deposited to the fluorescent screen material was scored. Simulations and measurements were made for four different incidence angles (3.5, 5.0, 7.5 and 10 degrees ). Several different sets of calculations were performed, studying the impact of different user-defined settings in the different MC packages. The study of different parameters settings in the GEANT4.8.1 simulation showed a strong dependence of the calculated out-scatter probability on the maximum allowed step length. For the largest incidence angle an increase of 60% in the out-scatter probability was found when restricting the maximum allowed step length to 0.05 cm. We also observed that the stepping algorithm of GEANT4.8.1 and 4.8.2 introduces a small non-physical directional and positional asymmetry at the exit boundary of the tungsten alloy block. The shape of the energy spectrum of protons being out-scattered agreed between the codes. The dose-weighted forward out-scatter probability, i.e. the ratio between the total signal from the unscattered beam and the out-scattered beam, showed a qualitative agreement of simulations compared to measurements. Quantitatively, the deviation of the simulations reached as high as 37%, while the experimental uncertainty was 14%. The mean emission angle of the simulations was within 16% of the measurement for all incidence angles with a measurement uncertainty of 8%.

A beam source model for scanned proton beams.

A beam source model, i.e. a model for the initial phase space of the beam, for scanned proton beams has been developed. The beam source model is based on parameterized particle sources with characteristics found by fitting towards measured data per individual beam line. A specific aim for this beam source model is to make it applicable to the majority of the various proton beam systems currently available or under development, with the overall purpose to drive dose calculations in proton beam treatment planning. The proton beam phase space is characterized by an energy spectrum, radial and angular distributions and deflections for the non-modulated elementary pencil beam. The beam propagation through the scanning magnets is modelled by applying experimentally determined focal points for each scanning dimension. The radial and angular distribution parameters are deduced from measured two-dimensional fluence distributions of the elementary beam in air. The energy spectrum is extracted from a depth dose distribution for a fixed broad beam scan pattern measured in water. The impact of a multi-slab range shifter for energy modulation is calculated with an own Monte Carlo code taking multiple scattering, energy loss and straggling, non-elastic and elastic nuclear interactions in the slab assembly into account. Measurements for characterization and verification have been performed with the scanning proton beam system at The Svedberg Laboratory in Uppsala. Both in-air fluence patterns and dose points located in a water phantom were used. For verification, dose-in-water was calculated with the Monte Carlo code GEANT 3.21 instead of using a clinical dose engine with approximations of its own. For a set of four individual pencil beams, both with the full energy and range shifted, 96.5% (99.8%) of the tested dose points satisfied the 1%/1 mm (2%/2 mm) gamma criterion.