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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.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 (LETThe LETFor all setups (homogeneous and heterogeneous), the mean absolute (and relative) LETNo computation error was found in the tested functionalities except for LET

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 able 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 (2x2 cm2 -15x15 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 a 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 at 90% (TR), proximal fall-off at 90% (PFO), lateral beam penumbra (LP) 90%-10% and field width at 90% (FW) were obtained. Results VHEE 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 ( 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 a treatment by a factor of two compared to a treatment using lower energies and lower SSD. In order to cover homogeneously deep-seated targets, 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 ( Conclusions The findings presented in this study assess 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 result 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.

Background: To introduce and compare multiple biological effectiveness guided (BG) proton plan optimization strategies minimizing variable relative biological effectiveness (RBE) induced dose burden in organs at risk (OAR) while maintaining plan quality with a constant RBE. Methods: Dose-optimized (DOSEopt) proton pencil beam scanning reference treatment plans were generated for ten cranial patients with prescription doses ≥ 54 Gy(RBE) and ≥ 1 OAR close to the clinical target volume (CTV). For each patient, four additional BG plans were created. BG objectives minimized either proton track-ends, dose-averaged linear energy transfer (LETd), energy depositions from high-LET protons or variable RBE-weighted dose (DRBE) in adjacent serially structured OARs. Plan quality (RBE = 1.1) was assessed by CTV dose coverage and robustness (2 mm setup, 3.5% density), dose homogeneity and conformity in the planning target volumes and adherence to OAR tolerance doses. LETd, DRBE (Wedenberg model, α/βCTV = 10 Gy, α/βOAR = 2 Gy) and resulting normal tissue complication probabilities (NTCPs) for blindness and brainstem necrosis were derived. Differences between DOSEopt and BG optimized plans were assessed and statistically tested (Wilcoxon signed rank, α = 0.05). Results: All plans were clinically acceptable. DOSEopt and BG optimized plans were comparable in target volume coverage, homogeneity and conformity. For recalculated DRBE in all patients, all BG plans significantly reduced near-maximum DRBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct DRBE optimization primarily reduced absorbed dose in OARs (average ΔDmean = 2.0 Gy; average ΔLETd,mean = 0.1 keV/µm), while the other strategies reduced LETd (average ΔDmean < 0.3 Gy; average ΔLETd,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than DRBE optimization. All BG strategies reduced NTCP for brainstem necrosis and blindness on average by 47% with average and maximum reductions of 5.4 and 18.4 percentage points, respectively. Conclusions: All BG strategies reduced variable RBE-induced NTCPs to OARs. Reducing LETd in high-dose voxels may be favourable due to its adherence to current dose reporting and maintenance of clinical plan quality and the availability of reported LETd and dose levels from clinical toxicity reports after cranial proton therapy. These optimization strategies beyond dose may be a first step towards safely translating variable RBE optimization in the clinics., Radiation oncology;17

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.

The primary objective of our study was to perform a quantitative robustness analysis of the dose-averaged linear energy transfer (LETIn this study, we utilized the 4DCT dataset of six anonymized lung patients. PBS lung plans were generated using a robust optimization technique (range uncertainty: ±3.5% and setup errors: ±5 mm) on the CTV for a total dose of 5000 cGy (RBE) in five fractions using the RBE of 1.1. For each patient, the LETThe mean LETThe addition of setup errors to the range uncertainties resulted in slightly less homogeneous LET

The increased radioresistence of healthy tissues when irradiated at very high dose rates (known as the Flash effect) is a radiobiological mechanism that is currently investigated to increase the therapeutic ratio of radiotherapy treatments. To maximize the benefits of the clinical application of Flash, a patient-specific balance between different properties of the dose distribution should be found, that is, Flash needs to be one of the variables considered in treatment planning. We investigated the Flash potential of three proton therapy planning and beam delivery techniques, each on a different anatomical region. Based on a set of beam delivery parameters, on hypotheses on the dose and dose rate thresholds needed for the Flash effect to occur, and on two definitions of Flash dose rate, we generated exemplary illustrations of the capabilities of current proton therapy equipment to generate Flash dose distributions. All techniques investigated could both produce dose distributions comparable with a conventional proton plan and reach the Flash regime, to an extent that was strongly dependent on the dose per fraction and the Flash dose threshold. The beam current, Flash dose rate threshold, and dose rate definition typically had a more moderate effect on the amount of Flash dose in normal tissue. A systematic estimation of the impact of Flash on different patient anatomies and treatment protocols is possible only if Flash-specific treatment planning features become readily available. Planning evaluation tools such as a voxel-based dose delivery time structure, and the inclusion in the optimization cost function of parameters directly associated with Flash (e.g., beam current, spot delivery sequence, and scanning speed), are needed to generate treatment plans that are taking full advantage of the potential benefits of the Flash effect.

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.

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.

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.

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.

Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved PG distributions for arbitrary tissues. The method estimates PG yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against PET monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.9 mm, with maximum standard deviation of 0.9 mm and 1.1 mm, for positron-emitters and PG shifts, respectively. Normalized mean absolute errors were within 1.2 and 5.3%. When comparing measured and predicted PET data, the same more complex case yielded an average shift of 3 mm, while all other cases were below absolute average shifts of 1.1 mm. Normalized mean absolute errors were below 7.2% for all cases. A novel solution to predict positron-emitter and PG distributions in a treatment planning system is proposed, enabling calculation times of only a few seconds to minutes for entire patient cases, which is suitable for integration in daily clinical routine.

The accuracy of dose calculation is vital to the quality of care for patients undergoing proton beam therapy (PBT). Currently, the dose calculation algorithms available in commercial treatment planning systems (TPS) in PBT are classified into two classes: pencil beam (PB) and Monte-Carlo (MC) algorithms. PB algorithms are still regarded as the standard of practice in PBT, but they are analytical approximations whereas MC algorithms use random sampling of interaction cross-sections that represent the underlying physics to simulate individual particles trajectories. This article provides a brief review of PB and MC dose calculation algorithms employed in commercial treatment planning systems and their performance comparison in phantoms through simulations and measurements. Deficiencies of PB algorithms are first highlighted by a simplified simulation demonstrating the transport of a single sub-spot of proton beam that is incident at an oblique angle in a water phantom. Next, more typical cases of clinical beams in water phantom are presented and compared to measurements. The inability of PB to correctly predict the range and subsequently distal fall-off is emphasized. Through the presented examples, it is shown how dose errors as high as 30% can result with use of a PB algorithm. These dose errors can be minimized to clinically acceptable levels of less than 5%, if MC algorithm is employed in TPS. As a final illustration, comparison between PB and MC algorithm is made for a clinical beam that is use to deliver uniform dose to a target in a lung section of an anthropomorphic phantom. It is shown that MC algorithm is able to correctly predict the dose at all depths and matched with measurements. For PB algorithm, there is an increasing mismatch with the measured doses with increasing tissue heterogeneity. The findings of this article provide a foundation for the second article of this series to compare MC vs. PB based lung cancer treatment planning.

The integration of real-time magnetic resonance imaging (MRI) guidance and proton therapy would potentially improve the proton dose steering capability by reducing daily uncertainties due to anatomical variations. The use of a fixed beamline coupled with an axial patient couch rotation would greatly simplify the proton delivery with MRI guidance. Nonetheless, it is mandatory to assure that the plan quality is not deteriorated by the anatomical deformations due to patient rotation. In this work, an in-house tool allowing for intra-fractional per-beam adaptation of intensity-modulated proton plans (BeamAdapt) was implemented through features available in RayStation. A set of three MRIs was acquired for two healthy volunteers (V 1, V 2): (1) no rotation/static, (2) rotation to the right and (3) left. V 1 was rotated by 15°, to simulate a clinical pediatric abdominal case and V 2 by 45°, to simulate an extreme patient rotation case. For each volunteer, a total of four intensity-modulated pencil beam scanning plans were optimized on the static MRI using virtual abdominal targets and two-three posterior-oblique beams. Beam angles were defined according to the angulations on the rotated MRIs. With BeamAdapt, each original plan was initially converted into separate plans with one beam per plan. In an iterative order, individual beam doses were non-rigidly deformed to the rotated anatomies and re-optimized accounting for the consequent deformations and the beam doses delivered so far. For evaluation, the final accumulated dose distribution was propagated back to the static MRI. Planned and adapted dose distributions were compared by computing relative differences between dose-volume histogram metrics. Absolute target dose differences were on average below 1% and organs-at-risk mean dose differences were below 3%. With BeamAdapt, not only intra-fractional per-beam proton plan adaptation coupled with axial patient rotation is possible but also the need for a rotating gantry during MRI guidance might be mitigated.

Radiation therapy is widely used for treatments of malignant diseases. The search for the optimal radiation treatment approach for a specific case is a complex task, ultimately seeking to maximise ...

Dose calculation in preclinical context with a clinical level of accuracy is a challenge due to the small animal scale and the medium photon energy range. In this work, we evaluate the effectiveness and accuracy of an analytical irradiator model combined with Monte Carlo (MC) calculations in the irradiated volume to calculate the dose delivered by a modern small animal irradiator. A model of the XRAD225Cx was created in µ-RayStation 8B, a preclinical treatment planning system, allowing arc and static beams for seven cylindrical collimators. Calculations with the µ-RayStation MC dose engine were compared with EBT3 measurements in water for all static beams and with a validated GATE model in water, heterogeneous media and a mouse CT. The GATE model is a complete MC representation of the XRAD225Cx. In water, µ-RayStation calculations, compared to GATE calculations and EBT3 measurements, agreed within a maximal error of 3.2% (mean absolute error of 0.6% and 0.8% respectively) and maximal distance-to-agreement (DTA) was 0.2 mm at 50% of the central dose. For a 5 mm static beam in heterogeneous media, the maximal absolute error between µ-RayStation and GATE calculations was below 1.3% in each medium and DTA was 0.1 mm at interfaces. For calculations on a mouse CT, µ-RayStation and GATE calculations agreed well for both static and arc beams. The 2D local gamma passing rate was >98.9% for 1%/0.3 mm criteria and >92.9% for 1%/0.2 mm criteria. Moreover, µ-RayStation reduces calculation time significantly comparing with GATE (speed-up factor between 120 and 680). These findings show that the analytical irradiator model presented in this work combined with the µ-RayStation MC dose engine accurately computes dose for the XRAD225Cx irradiator. The improvements in calculation time and availability of functionality and tools for managing, planning and evaluating the irradiation makes this platform very useful for pre-clinical irradiation research.

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.

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.

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 ...

Additional file 1: Figure S1. RBE for DSB induction (RBEDSB) and the low dose [compared to (α/β)R] RBE for cell survival (RBELD). Left Panel: RBE as a function of proton kinetic energy. A (and grey shaded region) denotes the approximate range of proton energies (“energy layers”) incident on patient (~ 90 to 225 MeV). Right Panel: RBE as a function of the continuous slowing down approximation (CSDA) range for a monoenergetic proton in water. Filled green squares denote estimates of RBE DSB from track structure simulations [64]. Filled red squares [(α/β)R = 10 Gy] and yellow triangles [(α/β)R = 2 Gy] denote LEM IV estimates of the RBE for cell survival after a 1.8 Gy absorbed dose (LEM IV data adapted from [36]). Solid black lines in the left and right panel are estimates of RBEDSB from the MCDS [31, 33]. Dashed lines are computed using Eq. (1) with (α/β)R = 1 Gy, 5 Gy and 10 Gy and an effective cell diameter of 4 μm. At the proton end of range (left panel, blue shaded region), the RBE for the last-traversed-cell may be as large as 2 to 3.7. However, the RBE for most cells near the tip of a pristine Bragg peak (red shaded regions) is likely to be much closer to 1.1 (~ 1.05 to 1.25). Distal to a pristine Bragg peak, RBEDSB and the RBE for cell survival rapidly rises to values that may approach 2.0 to 3.7 (blue shaded region in left panel). Figure S2. Proton RBE as a function of linear energy transfer (LET). Solid black line: MCDS estimate of RBEDSB [31, 33]. Dashed lines: RMF model [35, 36] with (α/β)R = 1 Gy, 5 Gy and 10 Gy (cell diameter = 4 μm). Red filled circles: LEM IV model estimate of the RBE for cell survival with (α/β)R = 2 Gy and 10 Gy [36]. Yellow triangles: Microdosimetric-Kinetic (MK) model estimate of the RBE for cell survival with (α/β)R = 2 Gy and 10 Gy [36]. Filled cyan squares: Wedenberg et al. [63] model of the RBE (1.8 Gy) for cell survival with (α/β)R = 2 Gy and 10 Gy. Filled stars: McNamara et al. [63] model of the RBE (1.8 Gy) for cell survival with (α/β)R = 2 Gy and 10 Gy. Blue shaded region corresponds to an RBE slope in the range from + 0.03 to + 0.09 per keV/μm.

PURPOSE The dose-averaged linear energy transfer (LETD ) is frequently used as representative quantity for the biological effectiveness of a radiation field. Moreover, relative biological effectiveness (RBE) values measured or calculated in mixed radiation fields are typically plotted vs the LETD . In this study, we will investigate whether the LETD is an appropriate quantity to describe the RBE of any mixed radiation field of protons and heavier ions and discuss potential limitations. METHODS To study the reliability of LETD , we investigate model predictions of RBE in monoenergetic beams under track segment conditions and pristine Bragg peaks as well as spread out Bragg peaks (SOBP) in water. Both, the pristine Bragg peaks and the SOBPs are regarded as mixed radiation fields in this analysis, that is, they are characterized by a certain width of the energy spectrum of the projectile, although the underlying energy distribution is much broader in the case of an SOBP as compared to a pristine peak. For both cases, the corresponding RBE values are compared to those of strictly monoenergetic particles under track segment conditions, characterized by a single LET value. For the planning we use the treatment planning software TRiP98 together with the Local Effect Model to predict the RBE of protons, helium, and carbon ions. We further compare our model predictions for protons with a simplistic linear RBE-LET relationship representative for the phenomenological models in literature. RESULTS Regarding pristine Bragg peaks in water, the deviations in RBE compared to monoenergetic particles under track segment conditions for the same LET value are low (mostly 0-5%), except for the distal fall-off region. The situation changes in SOBPs for which we found deviations in the order of up to 25% for the lighter particles and even more pronounced deviations for heavier particles like carbon ions. CONCLUSIONS The analysis showed that LETD is a sufficiently accurate predictor for RBE only in regions with comparably narrow, but not in regions with broad, LET distribution as in a single SOBP or in multiple overlapping fields. The deviations are caused by the nonlinearity of the RBE(LET) relationship in the case of track segment conditions. Thus, independent of the underlying RBE model and the particle type regarded, as long as the RBE(LET) relationship deviates from being purely linear, LETD is not a good predictor for RBE, and especially for heavier particles like carbon ions knowledge of the underlying LET distribution is mandatory to describe the RBE in mixed radiation fields.

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 cm 3 ) was irradiated with a mono-energetic PBS field (10 × 10 cm 2 ). 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%/2 mm, 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.

In a number of recent articles in this journal F. Cardone and collaborators have claimed the observation of several striking nuclear phenomena which they attribute to “piezonuclear reactions”. One such claim [F. Cardone, R. Mignani, A. Petrucci, Phys. Lett. A 373 (2009) 1956] is that subjecting a solution of 228Th to cavitation leads to a “transformation” of thorium nuclei that is 104 times faster than the normal nuclear decay for this isotope. In a “Comment” [G. Ericsson, S. Pomp, H. Sjostrand, E. Traneus, Phys. Lett. A 373 (2009) 3795] to the thorium work, we have criticized the evidence provided for this claim. In a “Reply” [F. Cardone, R. Mignani, A. Petrucci, Phys. Lett. A 373 (2009) 3797] Cardone et al. answer only some minor points but avoid addressing the real issue. The information provided in their Reply displays a worrying lack of control of their experimental situation and the data they put forward as evidence for their claims. We point out several shortcomings and errors in the described experimental preparations, set-up and reporting, as well as in the data analysis. We conclude that the evidence presented by Cardone et al. is insufficient to justify their claims of accelerated thorium decay (by “piezonuclear reactions” or otherwise).

The first magnetic proton recoil type neutron spectrometer has been put to use for diagnosing tokamak plasmas of high neutron yield rates (the range Yn = 1015–6×1018 n/s). The spectrometer principles along with the diagnostic installation are presented. Performance and diagnostic capabilities are illustrated based on results obtained at Joint European Torus. The implications for neutron spectrometry diagnostics on the next step tokamak for burning plasmas (Yn→1022 n/s) are discussed. © 1999 American Institute of Physics.

Previously, we have found that the build-up dose from abutting narrow electron beams formed with unfocussed electron multi-leaf collimator (eMLC) steal leaves was higher than with the respective open field. To investigate more closely the effect of leaf material and shape on dose in the build-up region, straight, round (radius 1.5 cm) and leaf ends with a different front face angle of alpha (leaf front face pointing towards the beam axis at an angle of 90 - alpha) made of steel, brass and tungsten were modelled using the BEAMnrc code. Based on a treatment head simulation of a Varian 2100 C/D linac, depth-dose curves and profiles in water were calculated for narrow 6, 12 and 20 MeV eMLC beams (width 1.0 cm, length 10 cm) at source-to-surface distances (SSD) of 102 and 105 cm. The effects of leaf material and front face angle were evaluated based on electron fluence, angle and energy spectra. With a leaf front face angle of 15 degrees, the dose in the build-up region of the 6 MeV field varied between 91 and 100%, while for straight and round leaf shapes the dose varied between 89 and 100%. The variation was between 94 and 100% for 12 and 20 MeV. For abutting narrow 6 MeV fields with total field size 5 x 10 cm(2), the build-up doses at 5 mm depth for the face angle 15 degrees and straight and round leaf shapes were 96% and 86% (SSD 102 cm) and 89% and 85% (SSD 105 cm). With higher energies, the effect of eMLC leaf shape on dose at 5 mm was slight (3-4% units with 12 MeV) and marginal with 20 MeV. The fluence, energy and angle spectra for total and leaf scattered electrons were practically the same for different leaf materials with 6 MeV. With high energies, the spectra for tungsten were more peaked due to lower leaf transmission. Compared with straight leaf ends, the face angle of 15 degrees and round leaf ends led to a 1 mm (for 6 MeV) and between 1 and 5 mm (12 and 20 MeV at a SSD of 105 cm) decrease of therapeutic range and increase of the field size, respectively. However, profile flatness was better for abutting 6 MeV beams with round (2.5%) and face angle 15 degrees leaves (3.0%) compared to straight leaf shape (5.2%). The eMLC leaves with a face angle of 15 degrees resulted in a marked increase in the build-up dose for the single narrow eMLC beam and thus in the dose in the build-up region from matched abutting fields.

Use of a water-equivalent bolus in electron-beam radiotherapy is sometimes impractical and non-hygienic. Therefore, the feasibility of applying adjacent narrow beams for producing high surface dose electron beams without a bolus was investigated. Depth dose curves and profiles in water were calculated and measured for 6 and 9 MeV electron-beam segments (width 0.3-1.5 cm, length 10 cm) for source-to-surface distances (SSD) 102 and 105 cm. Segment shaping was performed with an add-on electron multi-leaf collimator prototype attached to the Varian 2100 C/D linac. Dose calculations were performed with the Voxel Monte Carlo++ algorithm. Resulting dose distributions in typical clinical cases were compared with the bolus technique. With a composite segmental field with 1.0 cm wide segments the surface dose was over 90% of the depth dose maximum for both energies. The build-up area practically disappeared with a 0.5 cm wide single beam. This led to decrease in the therapeutic range for composite fields with segment widths smaller than 1.0 cm. The new technique yielded similar surface doses as the bolus technique. The photon contamination was 4% with a 9 x 10 cm(2) field (1.0 cm wide segments) compared to 1% for the respective open field with 9 MeV with a bolus. The calculated dose agreed within 2 mm and 3% of the measured dose in 93.7% and 85.2% of the voxels. Adjacent narrow eMLC beams with a 1.0 cm width are suitable to produce electron fields with high surface dose. Despite a slight nonuniformity in the surface profiles in the lateral part of the field at SSD 102 cm, surface dose and target coverage are comparable with the bolus technique.

Dose calculations for treatment planning of photon beam radiotherapy require a model of the beam to drive the dose calculation models. The beam shaping process involves scattering and filtering that yield radiation components which vary with collimator settings. The necessity to model these components has motivated the development of multisource beam models. We describe and evaluate clinical photon beam modeling based on multisource models, including lateral beam quality variations. The evaluation is based on user data for a pencil kernel algorithm and a point kernel algorithm (collapsed cone) used in the clinical treatment planning systems Helax-TMS and Nucletron-Oncentra. The pencil kernel implementations treat the beam spectrum as lateral invariant while the collapsed cone involves off axis softening of the spectrum. Both algorithms include modeling of head scatter components. The parameters of the beam model are derived from measured beam data in a semiautomatic process called RDH (radiation data handling) that, in sequential steps, minimizes the deviations in calculated dose versus the measured data. The RDH procedure is reviewed and the results of processing data from a large number of treatment units are analyzed for the two dose calculation algorithms. The results for both algorithms are similar, with slightly better results for the collapsed cone implementations. For open beams, 87% of the machines have maximum errors less than 2.5%. For wedged beams the errors were found to increase with increasing wedge angle. Internal, motorized wedges did yield slightly larger errors than external wedges. These results reflect the increased complexity, both experimentally and computationally, when wedges are used compared to open beams.

Purpose: Validate implementation of a published RBE model for DSB induction (RBEDSB) in several general purpose Monte Carlo (MC) code systems and the RayStation™ treatment planning system (TPS). For protons and other light ions, DSB induction is a critical initiating molecular event that correlates well with the RBE for cell survival. Methods: An efficient algorithm to incorporate information on proton and light ion RBEDSB from the independently tested Monte Carlo Damage Simulation (MCDS) has now been integrated into MCNP (Stewart et al. PMB 60, 8249–8274, 2015), FLUKA, TOPAS and a research build of the RayStation™ TPS. To cross-validate the RBEDSB model implementation LET distributions, depth-dose and lateral (dose and RBEDSB) profiles for monodirectional monoenergetic (100 to 200 MeV) protons incident on a water phantom are compared. The effects of recoil and secondary ion production (2H+, 3H+, 3He2+, 4He2+), spot size (3 and 10 mm), and transport physics on beam profiles and RBEDSB are examined. Results: Depth-dose and RBEDSB profiles among all of the MC models are in excellent agreement using a 1 mm distance criterion (width of a voxel). For a 100 MeV proton beam (10 mm spot), RBEDSB = 1.2 ± 0.03 (− 2–3%) at the tip of the Bragg peak and increases to 1.59 ± 0.3 two mm distal to the Bragg peak. RBEDSB tends to decrease as the kinetic energy of the incident proton increases. Conclusion: The model for proton RBEDSB has been accurately implemented into FLUKA, MCNP, TOPAS and the RayStation™TPS. The transport of secondary light ions (Z > 1) has a significant impact on RBEDSB, especially distal to the Bragg peak, although light ions have a small effect on (dosexRBEDSB) profiles. The ability to incorporate spatial variations in proton RBE within a TPS creates new opportunities to individualize treatment plans and increase the therapeutic ratio. Dr. Erik Traneus is employed full-time as a Research Scientist at RaySearch Laboratories. The research build of the RayStation used in the study was made available to the University of Washington free of charge. RaySearch Laboratories did not provide any monetary support for the reported studies.

Neutron emission spectroscopy (NES) diagnosis of high-power fusion plasma has been performed with the magnetic proton recoil (MPR) spectrometer installed at the Joint European Torus tokamak. The MPR is a high performance instrument where the setting of working points to prescribed calibration values is essential. This includes the MPR focal plane detector whose photomultipliers must be monitored for gain stability with respect to short- and long-term drifts as well as transient changes. A special monitoring system was developed for the MPR including a light pulser in the form of light emitting diodes. The monitoring system as part of the MPR focal plane detector is described here as well as the monitoring procedures and applications. Results from the use of the monitoring system are presented illustrating its present capabilities and possibilities for further developments in next step NES diagnostics.

The PS185 experiment at LEAR/CERN has investigated strangeness production in antiproton-proton collisions with final states such as $\overline{\Lambda} \Lambda$, $\overline{\Sigma}^0 \Lambda + c.c$, $\overline{\Sigma^+} \Sigma^+$, $\overline{\Sigma^-} \Sigma^-$ and $K_S K_S$. Results are presented from a study of about 32,000 {$K_S K_S X$} events obtained at several antiproton momenta in the regions of 1.45 and 1.7 GeV/c. The $\overline{p} p \to K_S K_S \eta$ cross sections extracted at these momenta constitute the first measurement of this reaction in flight and are broadly consistent with expectations of a phase-space extrapolation of branching ratios from annihilation at rest.

Spectrometry of the neutron emission is discussed as a probe of the fuel ion velocity distribution in tokamak plasmas where the instrumental energy calibration allows determination of Doppler shifts on an absolute scale or relative to the emission of thermal plasma conditions. Such Doppler shifts have been measured for plasmas of different heating methods at the Joint European Torus (JET) using a neutron spectrometer of the magnetic proton recoil (MPR) type. The principles of the MPR spectrometer as a rotation diagnostic are discussed together with the results obtained for the JET plasmas. The development potential of neutron spectrometry as a rotation diagnostic at the accuracy level of ±1 km/s for toroidal and poloidal rotation is projected, especially, for use on burning plasma tokamaks.

Spectrometry of the neutron emission has been used to probe the nonthermal features of the fuel ion velocity distributions in tokamak plasmas, especially, those arising from auxiliary heating. The first time resolved measurements are reported from the use of the new magnetic proton recoil (MPR) spectrometer in observations of deuterium–tritium plasmas at JET with strong ion cyclotron resonance heating. Results from preliminary analysis data are presented and compared with simulated neutron emission spectra based on the assumptions of a thermal plasma (a single Maxwellian ion distribution) or anisotropic Maxwellians with parallel and perpendicular temperatures, beside their relative amplitudes. The diagnostic results attained are also used to assess the diagnostic capabilities and the potential for use of MPR based diagnostics on burning plasma tokamaks.

Purpose: We evaluate the feasibility of using robustness optimization (RO) function to improve the planning efficiency of pencil beam scanning (PBS) craniospinal irradiation (CSI) with gradient matching technique. Methods: A CSI patient was planned with 2 lateral brain fields and 4 posterior fields to cover the entire spine to maximal field of 24 cm × 20 cm on a compact PBS gantry, ProteusONE. CSI plans were generated using traditional volumetric gradient dose optimization (VGDO) and robustness optimization (RO) method respectively. In traditional VGDO, besides the sectioned spine target volumes, gradient volume (GV) were generated as 4 equally spaced structures e.g. 80%, 60%, 40%, and 20% of prescription dose. In RO method, only sectioned spine target volumes with an overlap of 4cm were created. In the robustness optimization settings, 5mm uncertainty in superior and inferior direction was defined for auto gradient optimization. Dosimetric metrics of conformity number (CN), homogeneity index (HI), and maximal cord doses were compared in Raystation version 4.6.100.6. Results: In VGDO method, total 16 GV structures and five 100% dose level target structures were contoured compared to total 5 target structures in RO method which saves 30 min in contour. With the same PTV coverage (95% volume receive 30.6Gy prescription dose), maximum cord dose is 32.64Gy in VGDO and 31.94Gy in RO. HI is 1.03 and 1.04 for VGDO and RO respectively. CN is 0.93 and 0.94 for VGDO and RO respectively. Conclusions: The dosimetric comparison demonstrated both methods are equivalent in terms of plan quality. With robust optimization for CSI gradient matching, it efficiently reduces the amount of planning target contour structure by factor of 4 and thus improves the planning efficiency especially for 4 or more gradient junction area.