Pesticide risk assessment in European agriculture: Distribution patterns, ban-substitution effects and regulatory implications.

This study estimates the risks of agricultural pesticides on non-target organisms and the environment by combining detailed pesticide application data for 2015 with the Danish risk indicator Pesticide Load. We quantify and map the pesticide load of 59 pesticides on 28 crops and pastures in the EU. Furthermore, we investigate how recent bans on 14 pesticides in the EU could reduce pesticide use and load. Key findings show that the highest pesticide loads per hectare occur in Cyprus and the Netherlands due to high application rates and a high proportion of vegetable production. Chlorpyrifos caused the highest pesticide load per hectare on more than half of the assessed crops before its ban. The ban of 14 pesticides between 2018 and 2023 potentially reduced pesticide loads by 94%, but unobserved substitution effects could offset pesticide load reductions. Although bans on active substances are justified to control certain endpoint risks, our results highlight the potential weaknesses of bans that merely shift risks. These findings contribute to the ongoing scientific and societal discourse on efficiently mitigating pesticides' impacts on non-target organisms and the environment. However, to improve the evaluation of pesticide use, it is vital to enhance the reporting on detailed pesticide use for individual crop-pesticide combinations.

Monte Carlo model for ion mobility and diffusion for characteristic electric fields in nanodosimetry.

The quantification of the effects of space radiation for manned spaceflight can be approximated by nanodosimetric measurements. For the development of nanodosimetric detectors, a Monte Carlo model for ion mobility and diffusion for characteristic electric fields is presented. This model can be used to describe the interactions of ions in their parent gas based solely on commonly known input parameters, such as the ionization potential, kinetic diameter, molar mass, and polarizability of the gas. A model for approximating the resonant charge exchange cross section has been proposed, requiring only the ionization energy and mass of the parent gas as input parameters. The method proposed in this work was tested against experimental drift velocity data for a wide range of gases (helium, neon, nitrogen, argon, krypton, carbon monoxide, carbon dioxide, oxygen, propane). The transverse diffusion coefficients were compared to experimental values for helium, nitrogen, neon, argon, and propane gas. With the Monte Carlo code and resonant charge exchange cross section approximation model presented in this work, it is now possible to calculate an estimate of the drift velocities, transverse diffusion, and thus the ion mobility of ions in their parent gas. This is essential for further nanodosimetric detector development, as those parameters are often not well known for the gas mixtures used in nanodosimetry.

European astronaut radiation related cancer risk assessment using dosimetric calculations of organ dose equivalents.

An illustrative sample mission of a Mars swing-by mission lasting one calendar year was chosen to highlight the application of European risk assessment software to cancer (all solid cancer plus leukaemia) risks from radiation exposures in space quantified with organ dose equivalent rates from model calculations based on the quantity Radiation Attributed Decrease of Survival (RADS). The relevant dose equivalent to the colon for radiation exposures from this Mars swing-by mission were found to vary between 198 and 482 mSv. These doses depend on sex and the two other factors investigated here of: solar activity phase (maximum or minimum); and the choice of space radiation quality factor used in the calculations of dose equivalent. Such doses received at typical astronaut ages around 40 years old will result in: the probability of surviving until retirement age (65 years) being reduced by a range from 0.38% (95%CI: 0.29; 0.49) to 1.29% (95%CI: 1.06; 1.56); and the probability of surviving cancer free until retirement age being reduced by a range from 0.78% (95%CI: 0.59; 0.99) to 2.63% (95%CI: 2.16; 3.18). As expected from the features of the models applied to quantify the general dosimetric and radiation epidemiology parameters, the cancer incidence risks in terms of surviving cancer free, are higher than the cancer mortality risks in terms of surviving, the risks for females are higher than for males, and the risks at solar minimum are higher than at solar maximum.

Quality assessment of automatically planned O-Ring linac SBRT plans for pelvic lymph node metastases, finding the optimal minimum target size by comparison with robotic SBRT.

PURPOSE: The purpose of this study is to assess the quality of automatic planned O-Ring Halcyon linac SBRT plans for pelvic lymph node metastases and to establish an absolute PTV volume threshold as a plan quality prediction criterion. Compliance of the plans to institutional SBRT plan evaluation criteria and differences in plan quality and treatment delivery times between Halcyon Linac and CyberKnife robotic SBRT were evaluated. METHODS: Twenty-one CyberKnife treatment plans were replanned for Halcyon. Prescription doses range was 26-40 Gy in mean three fractions. The mean/median planning target volume was 4.0/3.6 cm3 . Institutional criteria for the plan evaluation were: New Conformity Index (NCI), Conformity Index (CI), Modified Gradient Index (MGI), selectivity index reciprocal (PIV/TVPIV ), and the target coverage by prescription isodose (%PIV). Statistical analysis based on the receiver operating characteristic (ROC) curve was used to determine a plan quality predictor threshold of the PTV volume. Comparative analysis of normal tissue complication probabilities (NTCP) was used to assess the risk of toxicity in healthy tissues. RESULTS: Seventy-one percent (n = 15)/95% (n = 20) of Halcyon and 81% (n = 17)/100% (n = 21) of CK plans fulfilled all ideal/tolerance criteria. For PTVs above a found optimal threshold of 2.6 cm3 (71%, n = 15), no statistically significant difference was observed between the CI, NCI, PIV/TVPIV , and MGI indexes of both groups, while the coverage (%PIV) was statistically but not clinically significantly different between cohorts. Significantly shorter delivery times are expected with Halcyon. No significant differences in NTCP were observed. CONCLUSION: All but one automatically optimized Halcyon treatment plans demonstrated ideal or acceptable performance. PTV threshold of 2.6 cm3 can be used as decision criteria in clinical settings. The results of our study demonstrated the promising performance of the Halcyon for pelvic SBRT, although plan-specific QA is required to verify machine performance during plan delivery.

Experimental Validation of an Analytical Program and a Monte Carlo Simulation for the Computation of the Far Out-of-Field Dose in External Beam Photon Therapy Applied to Pediatric Patients.

Background: The out-of-the-field absorbed dose affects the probability of primary second radiation-induced cancers. This is particularly relevant in the case of pediatric treatments. There are currently no methods employed in the clinical routine for the computation of dose distributions from stray radiation in radiotherapy. To overcome this limitation in the framework of conventional teletherapy with photon beams, two computational tools have been developed-one based on an analytical approach and another depending on a fast Monte Carlo algorithm. The purpose of this work is to evaluate the accuracy of these approaches by comparison with experimental data obtained from anthropomorphic phantom irradiations. Materials and Methods: An anthropomorphic phantom representing a 5-year-old child (ATOM, CIRS) was irradiated considering a brain tumor using a Varian TrueBeam linac. Two treatments for the same planned target volume (PTV) were considered, namely, intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). In all cases, the irradiation was conducted with a 6-MV energy beam using the flattening filter for a prescribed dose of 3.6 Gy to the PTV. The phantom had natLiF : Mg, Cu, P (MCP-N) thermoluminescent dosimeters (TLDs) in its 180 holes. The uncertainty of the experimental data was around 20%, which was mostly attributed to the MCP-N energy dependence. To calculate the out-of-field dose, an analytical algorithm was implemented to be run from a Varian Eclipse TPS. This algorithm considers that all anatomical structures are filled with water, with the exception of the lungs which are made of air. The fast Monte Carlo code dose planning method was also used for computing the out-of-field dose. It was executed from the dose verification system PRIMO using a phase-space file containing 3x109 histories, reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1 ) on all voxels scoring more than 50% of the maximum dose. The standard statistical uncertainty of out-of-field voxels in the Monte Carlo simulation did not exceed 5%. For the Monte Carlo simulation the actual chemical composition of the materials used in ATOM, as provided by the manufacturer, was employed. Results: In the out-of-the-field region, the absorbed dose was on average four orders of magnitude lower than the dose at the PTV. For the two modalities employed, the discrepancy between the central values of the TLDs located in the out-of-the-field region and the corresponding positions in the analytic model were in general less than 40%. The discrepancy in the lung doses was more pronounced for IMRT. The same comparison between the experimental and the Monte Carlo data yielded differences which are, in general, smaller than 20%. It was observed that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT. Conclusions: The proposed computational methods for the routine calculation of the out-of-the-field dose produce results that are similar, in most cases, with the experimental data. It has been experimentally found that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT for a given PTV.

Validation of a Monte Carlo Framework for Out-of-Field Dose Calculations in Proton Therapy.

Proton therapy enables to deliver highly conformed dose distributions owing to the characteristic Bragg peak and the finite range of protons. However, during proton therapy, secondary neutrons are created, which can travel long distances and deposit dose in out-of-field volumes. This out-of-field absorbed dose needs to be considered for radiation-induced secondary cancers, which are particularly relevant in the case of pediatric treatments. Unfortunately, no method exists in clinics for the computation of the out-of-field dose distributions in proton therapy. To help overcome this limitation, a computational tool has been developed based on the Monte Carlo code TOPAS. The purpose of this work is to evaluate the accuracy of this tool in comparison to experimental data obtained from an anthropomorphic phantom irradiation. An anthropomorphic phantom of a 5-year-old child (ATOM, CIRS) was irradiated for a brain tumor treatment in an IBA Proteus Plus facility using a pencil beam dedicated nozzle. The treatment consisted of three pencil beam scanning fields employing a lucite range shifter. Proton energies ranged from 100 to 165 MeV. A median dose of 50.4 Gy(RBE) with 1.8 Gy(RBE) per fraction was prescribed to the initial planning target volume (PTV), which was located in the cerebellum. Thermoluminescent detectors (TLDs), namely, Li-7-enriched LiF : Mg, Ti (MTS-7) type, were used to detect gamma radiation, which is produced by nuclear reactions, and secondary as well as recoil protons created out-of-field by secondary neutrons. Li-6-enriched LiF : Mg,Cu,P (MCP-6) was combined with Li-7-enriched MCP-7 to measure thermal neutrons. TLDs were calibrated in Co-60 and reported on absorbed dose in water per target dose (µGy/Gy) as well as thermal neutron dose equivalent per target dose (µSv/Gy). Additionally, bubble detectors for personal neutron dosimetry (BD-PND) were used for measuring neutrons (>50 keV), which were calibrated in a Cf-252 neutron beam to report on neutron dose equivalent dose data. The Monte Carlo code TOPAS (version 3.6) was run using a phase-space file containing 1010 histories reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1) on all voxels scoring more than 50% of the maximum dose. The primary beam was modeled following a Fermi-Eyges description of the spot envelope fitted to measurements. For the Monte Carlo simulation, the chemical composition of the tissues represented in ATOM was employed. The dose was tallied as dose-to-water, and data were normalized to the target dose (physical dose) to report on absorbed doses per target dose (mSv/Gy) or neutron dose equivalent per target dose (µSv/Gy), while also an estimate of the total organ dose was provided for a target dose of 50.4 Gy(RBE). Out-of-field doses showed absorbed doses that were 5 to 6 orders of magnitude lower than the target dose. The discrepancy between TLD data and the corresponding scored values in the Monte Carlo calculations involving proton and gamma contributions was on average 18%. The comparison between the neutron equivalent doses between the Monte Carlo simulation and the measured neutron doses was on average 8%. Organ dose calculations revealed the highest dose for the thyroid, which was 120 mSv, while other organ doses ranged from 18 mSv in the lungs to 0.6 mSv in the testes. The proposed computational method for routine calculation of the out-of-the-field dose in proton therapy produces results that are compatible with the experimental data and allow to calculate out-of-field organ doses during proton therapy.

Investigation of the effect of air gap size on the spatial resolution in proton- and helium radio- and tomography.

PURPOSE: Proton computed (transmission) tomography (pCT) refers to the process of imaging an object by letting protons pass through it, while measuring their energy after, and their position and (optionally) direction both before and after their traversal through that object. The so far experimental technique has potential to improve treatment planning of proton therapy by enabling the direct acquisition of a proton stopping power map of tissue, thus removing the need to obtain it by converting X-ray CT attenuation data and thereby eliminating uncertainties which arise in the mentioned conversion process. The image reconstruction in pCT requires accurate estimates of the proton trajectories. In experimental pCT detector setups where the direction of the protons is not measured, the air gap between the detector planes and the imaged object worsens the spatial resolution of the image obtained. In this work we determined the mean proton paths and the corresponding spatial uncertainty, taking into account the presence of the air gap. METHODS: We used Monte Carlo simulations of radiation transport to systematically investigate the effect of the air gap size between detector and patient on the spatial resolution of proton (ion) computed tomography for protons with an energy of 200MeV and 250MeV as well as for helium ions (He-4) with an energy of 798MeV. For the simulations we used TOPAS which itself is based on Geant4. RESULTS: For all particles, which are detected at the same entrance and exit coordinate, the average ion path and the corresponding standard deviation was computed. From this information, the dependence of the spatial resolution on the air gap size and the angular confusion of the particle beam was inferred. CONCLUSION: The presence of the airgap does not pose a problem for perfect fan beams. In realistic scenarios, where the initial angular confusion is around 5mrad and for typical air gap sizes up to 10cm, using an energy of 200MeV a spatial resolution of about 1.6mm can be achieved. Using protons with E=250MeV a spatial resolution of about 1.1mm and using helium ions (He-4) with E=798MeV even a spatial resolution below 0.7mm respectively is attainable.

A bespoke health risk assessment methodology for the radiation protection of astronauts.

An alternative approach that is particularly suitable for the radiation health risk assessment (HRA) of astronauts is presented. The quantity, Radiation Attributed Decrease of Survival (RADS), representing the cumulative decrease in the unknown survival curve at a certain attained age, due to the radiation exposure at an earlier age, forms the basis for this alternative approach. Results are provided for all solid cancer plus leukemia incidence RADS from estimated doses from theoretical radiation exposures accumulated during long-term missions to the Moon or Mars. For example, it is shown that a 1000-day Mars exploration mission with a hypothetical mission effective dose of 1.07 Sv at typical astronaut ages around 40 years old, will result in the probability of surviving free of all types of solid cancer and leukemia until retirement age (65 years) being reduced by 4.2% (95% CI 3.2; 5.3) for males and 5.8% (95% CI 4.8; 7.0) for females. RADS dose-responses are given, for the outcomes for incidence of all solid cancer, leukemia, lung and female breast cancer. Results showing how RADS varies with age at exposure, attained age and other factors are also presented. The advantages of this alternative approach, over currently applied methodologies for the long-term radiation protection of astronauts after mission exposures, are presented with example calculations applicable to European astronaut occupational HRA. Some tentative suggestions for new types of occupational risk limits for space missions are given while acknowledging that the setting of astronaut radiation-related risk limits will ultimately be decided by the Space Agencies. Suggestions are provided for further work which builds on and extends this new HRA approach, e.g., by eventually including non-cancer effects and detailed space dosimetry.

First measurements of ionization cluster-size distributions with a compact nanodosimeter.

PURPOSE: A nanodosimeter is a type of detector which measures single ionizations in a small gaseous volume in order to obtain ionization cluster size probability distributions for characterization of radiation types. Working nanodosimeter detectors are usually bulky machines which require a lot of space. In this work, the authors present a compact ceramic nanodosimeter detector and report on first measurements of cluster size distributions of 5 MeV alpha particles. METHODS: Single ionization measurements are achieved by applying a weak electric field to collect positive ions in a hole in a ceramic plate. Inside the ceramic plate, due to a strong electric field, the ions are accelerated and produce impact-ionizations. The resulting electron avalanche is detected in a read-out electrode. A Bayesian unfolding algorithm is then applied to the experimentally obtained cluster size distributions to reconstruct the true cluster size distributions. RESULTS: Experimentally obtained cluster size distributions by the compact nanodosimeter detector are presented. The reconstructed cluster size distributions agreed well with Monte Carlo simulated cluster size distributions for small volumes (diameter = 2.5 nm). For larger volumes, discrepancies between the reconstructed cluster size distributions and cluster size distributions from Monte Carlo simulations were observed. CONCLUSIONS: For the first time, ionization cluster size probability distributions could be obtained by a small and compact nanodosimeter detector. This signifies the achievement of a critical step toward the wide application of nanodosimetric characterization of radiation types including in clinical environments.

Comparing second cancer risk for multiple radiotherapy modalities in survivors of hodgkin lymphoma.

OBJECTIVES: To assess if excess absolute risk (EAR) of radiation-induced solid cancer can be used to rank radiotherapy plans for treatment of Hodgkin lymphoma (HL) in a statistically significant way. METHODS: EAR models, calibrated with data from the Life Span Study and HL survivors, have been incorporated into a voxelised risk-calculation software, which is used to compare four treatment modalities planned for five virtual HL patients. Organ-specific parameters are generated repeatedly in a Monte Carlo fashion to model their uncertainties. This in turn enables a quantitative estimation of the EAR uncertainties. RESULTS: Parameter-driven uncertainties on total EAR are around 13%, decreasing to around 2-5% for relative EAR comparisons. Total EAR estimations indicate that intensity modulated proton therapy decreases the average risk by 40% compared to the intensity modulated radiation therapy plan, 28% compared to the volumetric modulated arc therapy plan whereas the three-dimensional conformal radiation therapy plan is equivalent within the uncertainty. CONCLUSION: Relative EAR is a useful metric for distinguishing between radiotherapy plans in terms of second cancer risk. ADVANCES IN KNOWLEDGE: Relative EAR is not dominated by model or parameter uncertainties and can be used to guide the choice of radiotherapy for HL patients.

Feasibility study of macroscopic simulations of nanodosimetric parameters for proton therapy.

PURPOSE: In view of the potential of treatment plan optimization based on nanodosimetric quantities, fast Monte Carlo methods for obtaining nanodosimetric quantities in macroscopic volumes are important. In this work, a "fast" method for obtaining nanodosimetric parameters from a clinical proton pencil beam in a macroscopic volume is compared with a slow and detailed method. Furthermore, the variations of these parameters, when obtained with the Monte Carlo codes TOPAS and NOREC, are investigated. METHODS: Monte Carlo track structure simulations of 1 keV-100 MeV protons and 12 eV-1 MeV electrons in a volume of 8 nm 3 liquid water provided us with an atlas of cluster size distributions. Two kinds of ionization cluster size distributions were recorded, counting all ionizations or only ionizations directly produced by the primary particle. The simulations of the proton pencil beam were performed in two different ways. A "fast" method where only the protons were simulated and a "slow and detailed" method where protons and electrons were simulated in order to obtain spectra at different depths. The obtained spectra were then convoluted with cluster size distributions. RESULTS: It was shown that the nanodosimetric quantity F 2 from the "fast" method is, depending on the location, between 43.6% and 63.6% smaller than the F 2 obtained by the "slow and detailed" method. However, it was also shown that variations of nanodosimetric quantities are even larger when the cluster size distributions of the electrons are simulated with the Monte Carlo code NOREC, that is, the cumulative F 2 probabilities obtained with NOREC were between 50.8% and 75.5% smaller than the F 2 probabilities obtained with TOPAS. CONCLUSIONS: As long as the uncertainties of different Monte Carlo codes are not improved, it is feasible to only simulate protons in a macroscopic volume. It must be noted, however, that the uncertainty is in the order of 100%.

Neutron dose and its measurement in proton therapy-current State of Knowledge.

Proton therapy has shown dosimetric advantages over conventional radiation therapy using photons. Although the integral dose for patients treated with proton therapy is low, concerns were raised about late effects like secondary cancer caused by dose depositions far away from the treated area. This is especially true for neutrons and therefore the stray dose contribution from neutrons in proton therapy is still being investigated. The higher biological effectiveness of neutrons compared to photons is the main cause of these concerns. The gold-standard in neutron dosimetry is measurements, but performing neutron measurements is challenging. Different approaches have been taken to overcome these difficulties, for instance with newly developed neutron detectors. Monte Carlo simulations is another common technique to assess the dose from secondary neutrons. Measurements and simulations are used to develop analytical models for fast neutron dose estimations. This article tries to summarize the developments in the different aspects of neutron dose in proton therapy since 2017. In general, low neutron doses have been reported, especially in active proton therapy. Although the published biological effectiveness of neutrons relative to photons regarding cancer induction is higher, it is unlikely that the neutron dose has a large impact on the second cancer risk of proton therapy patients.

Tumour size can have an impact on the outcomes of epidemiological studies on second cancers after radiotherapy.

Obtaining a correct dose-response relationship for radiation-induced cancer after radiotherapy presents a major challenge for epidemiological studies. The purpose of this paper is to gain a better understanding of the associated uncertainties. To accomplish this goal, some aspects of an epidemiological study on breast cancer following radiotherapy of Hodgkin's disease were simulated with Monte Carlo methods. It is demonstrated that although the doses to the breast volume are calculated by one treatment plan, the locations and sizes of the induced secondary breast tumours can be simulated and, based on these simulated locations and sizes, the absorbed doses at the site of tumour incidence can also be simulated. For the simulations of point dose at tumour site, linear and non-linear mechanistic models which predict risk of cancer induction as a function of dose were applied randomly to the treatment plan. These simulations provided for each second tumour and each simulated tumour size the predicted dose. The predicted-dose-response-characteristic from the analysis of the simulated epidemiological study was analysed. If a linear dose-response relationship for cancer induction was applied to calculate the theoretical doses at the simulated tumour sites, all Monte-Carlo realizations of the epidemiological study yielded strong evidence for a resulting linear risk to predicted-dose-response. However, if a non-linear dose-response of cancer induction was applied to calculate the theoretical doses, the Monte Carlo simulated epidemiological study resulted in a non-linear risk to predicted-dose-response relationship only if the tumour size was small (< 1.5 cm). If the diagnosed breast tumours exceeded an average diameter of 1.5 cm, an applied non-linear theoretical-dose-response relationship for second cancer falsely resulted in strong evidence for a linear predicted-dose relationship from the epidemiological study realizations. For a typical distribution of breast cancer sizes, the model selection probability for a resulting predicted-dose linear model was 61% although a non-linear theoretical-dose-response relationship for cancer induction had been applied. The results of this study, therefore, provide evidence that the shapes of epidemiologically obtained dose-response relationships for cancer induction can be biased by the finite size of the diagnosed second tumour, even though the epidemiological study was done correctly.

The probabilities of one- and multi-track events for modeling radiation-induced cell kill.

In view of the clinical importance of hypofractionated radiotherapy, track models which are based on multi-hit events are currently reinvestigated. These models are often criticized, because it is believed that the probability of multi-track hits is negligible. In this work, the probabilities for one- and multi-track events are determined for different biological targets. The obtained probabilities can be used with nano-dosimetric cluster size distributions to obtain the parameters of track models. We quantitatively determined the probabilities for one- and multi-track events for 100, 500 and 1000 keV electrons, respectively. It is assumed that the single tracks are statistically independent and follow a Poisson distribution. Three different biological targets were investigated: (1) a DNA strand (2 nm scale); (2) two adjacent chromatin fibers (60 nm); and (3) fiber loops (300 nm). It was shown that the probabilities for one- and multi-track events are increasing with energy, size of the sensitive target structure, and dose. For a 2 × 2 × 2 nm3 target, one-track events are around 10,000 times more frequent than multi-track events. If the size of the sensitive structure is increased to 100-300 nm, the probabilities for one- and multi-track events are of the same order of magnitude. It was shown that target theories can play a role for describing radiation-induced cell death if the targets are of the size of two adjacent chromatin fibers or fiber loops. The obtained probabilities can be used together with the nano-dosimetric cluster size distributions to determine model parameters for target theories.

Neutrons in active proton therapy: Parameterization of dose and dose equivalent.

PURPOSE: One of the essential elements of an epidemiological study to decide if proton therapy may be associated with increased or decreased subsequent malignancies compared to photon therapy is an ability to estimate all doses to non-target tissues, including neutron dose. This work therefore aims to predict for patients using proton pencil beam scanning the spatially localized neutron doses and dose equivalents. METHODS: The proton pencil beam of Gantry 1 at the Paul Scherrer Institute (PSI) was Monte Carlo simulated using GEANT. Based on the simulated neutron dose and neutron spectra an analytical mechanistic dose model was developed. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed model in order to calculate the neutron component of the delivered dose distribution for each treated patient. The neutron dose was estimated for two patient example cases. RESULTS: The analytical neutron dose model represents the three-dimensional Monte Carlo simulated dose distribution up to 85cm from the proton pencil beam with a satisfying precision. The root mean square error between Monte Carlo simulation and model is largest for 138MeV protons and is 19% and 20% for dose and dose equivalent, respectively. The model was successfully integrated into the PSI treatment planning system. In average the neutron dose is increased by 10% or 65% when using 160MeV or 177MeV instead of 138MeV. For the neutron dose equivalent the increase is 8% and 57%. CONCLUSIONS: The presented neutron dose calculations allow for estimates of dose that can be used in subsequent epidemiological studies or, should the need arise, to estimate the neutron dose at any point where a subsequent secondary tumour may occur. It was found that the neutron dose to the patient is heavily increased with proton energy.

The Impact of the Geometrical Structure of the DNA on Parameters of the Track-Event Theory for Radiation Induced Cell Kill.

BACKGROUND AND PURPOSE: When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. An alternative to the LQ-model is the track-event theory which is based on the probabilities for one- and two two-track events. A one-track-event (OTE) is always represented by at least two simultaneous double strand breaks. A two-track-event (TTE) results in one double strand break. Therefore at least two two-track-events on the same or different chromosomes are necessary to produce an event which leads to cell sterilization. It is obvious that the probabilities of OTEs and TTEs must somehow depend on the geometrical structure of the chromatin. In terms of the track-event theory the ratio ε of the probabilities of OTEs and TTEs includes the geometrical dependence and is obtained in this work by simple Monte Carlo simulations. MATERIALS AND METHODS: For this work it was assumed that the anchors of loop forming chromatin are most sensitive to radiation induced cell deaths. Therefore two adjacent tetranucleosomes representing the loop anchors were digitized. The probability ratio ε of OTEs and TTEs was factorized into a radiation quality dependent part and a geometrical part: ε = εion ∙ εgeo. εgeo was obtained for two situations, by applying Monte Carlo simulation for DNA on the tetranucleosomes itself and for linker DNA. Low energy electrons were represented by randomly distributed ionizations and high energy electrons by ionizations which were simulated on rays. εion was determined for electrons by using results from nanodosimetric measurements. The calculated ε was compared to the ε obtained from fits of the track event model to 42 sets of experimental human cell survival data. RESULTS: When the two tetranucleosomes are in direct contact and the hits are randomly distributed εgeo and ε are 0.12 and 0.85, respectively. When the hits are simulated on rays εgeo and ε are 0.10 and 0.71. For the linker-DNA εgeo and ε for randomly distributed hits are 0.010 and 0.073, and for hits on rays 0.0058 and 0.041, respectively. The calculated ε fits the experimentally obtained ε = 0.64±0.32 best for hits on the tetranucleosome when they are close to each other both, for high and low energy electrons. CONCLUSIONS: The parameter εgeo of the track event model was obtained by pure geometrical considerations of the chromatin structure and is 0.095 ± 0.022. It can be used as a fixed parameter in the track-event theory.

Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE.

The biological effectiveness of neutrons produced during proton therapy in inducing cancer is unknown, but potentially large. In particular, since neutron biological effectiveness is energy dependent, it is necessary to estimate, besides the dose, also the energy spectra, in order to obtain quantities which could be a measure of the biological effectiveness and test current models and new approaches against epidemiological studies on cancer induction after proton therapy. For patients treated with proton pencil beam scanning, this work aims to predict the spatially localized neutron energies, the effective quality factor, the weighting factor according to ICRP, and two RBE values, the first obtained from the saturation corrected dose mean lineal energy and the second from DSB cluster induction. A proton pencil beam was Monte Carlo simulated using GEANT. Based on the simulated neutron spectra for three different proton beam energies a parameterization of energy, quality factors and RBE was calculated. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed parameterizations in order to calculate the spatially localized neutron energy, quality factors and RBE for each treated patient. The parameterization represents the simple quantification of neutron energy in two energy bins and the quality factors and RBE with a satisfying precision up to 85 cm away from the proton pencil beam when compared to the results based on 3D Monte Carlo simulations. The root mean square error of the energy estimate between Monte Carlo simulation based results and the parameterization is 3.9%. For the quality factors and RBE estimates it is smaller than 0.9%. The model was successfully integrated into the PSI treatment planning system. It was found that the parameterizations for neutron energy, quality factors and RBE were independent of proton energy in the investigated energy range of interest for proton therapy. The pencil beam algorithm has been extended using the developed parameterizations in order to calculate the neutron energy, quality factor and RBE.

Increasing social welfare by taxing pesticide externalities in the Indian cotton sector.

BACKGROUND: Pesticide use in the Indian cotton industry has decreased with the introduction of Bt cotton, but rates are still high in comparison with other countries. The adoption of alternative strategies, such as integrated pest management, has been slow, even though benefits are potentially high, more so if the full costs of the external effects of the technologies are taken into account. In order to estimate true societal benefits of different strategies, we compare their external costs and economic performance under external cost taxation, using a state-of-the-art partial equilibrium model of the Indian agricultural sector. RESULTS: Pesticide externalities lower social welfare in the Indian cotton sector by $US 400-2200 million, depending on the technologies employed. A full internalisation reduces producer revenues by $US 100 ha-1 if only Bt cotton is used, and by $US 30 ha-1 if IPM is another option. Consumers do not start to lose surplus until 20-70% are internalised, and losses are smaller if all technologies are available. CONCLUSION: External pesticide costs can be internalised partially without substantially affecting consumer surplus while still increasing social welfare, but producers need to have access to and the knowledge to employ all available cotton production technologies to minimise losses. © 2016 Society of Chemical Industry.

Assessment of organ dose reduction and secondary cancer risk associated with the use of proton beam therapy and intensity modulated radiation therapy in treatment of neuroblastomas.

BACKGROUND: To compare proton beam therapy (PBT) and intensity-modulated radiation therapy (IMRT) with conformal radiation therapy (CRT) in terms of their organ doses and ability to cause secondary cancer in normal organs. METHODS: Five patients (median age, 4 years; range, 2-11 years) who underwent PBT for retroperitoneal neuroblastoma were selected for treatment planning simulation. Four patients had stage 4 tumors and one had stage 2A tumor, according to the International Neuroblastoma Staging System. Two patients received 36 Gy, two received 21.6 Gy, and one received 41.4 Gy of radiation. The volume structures of these patients were used for simulations of CRT and IMRT treatment. Dose-volume analyses of liver, stomach, colon, small intestine, pancreas, and bone were performed for the simulations. Secondary cancer risks in these organs were calculated using the organ equivalent dose (OED) model, which took into account the rates of cell killing, repopulation, and the neutron dose from the treatment machine. RESULTS: In all evaluated organs, the mean dose in PBT was 20-80% of that in CRT. IMRT also showed lower mean doses than CRT for two organs (20% and 65%), but higher mean doses for the other four organs (110-120%). The risk of secondary cancer in PBT was 24-83% of that in CRT for five organs, but 121% of that in CRT for pancreas. The risk of secondary cancer in IMRT was equal to or higher than CRT for four organs (range 100-124%). CONCLUSION: Low radiation doses in normal organs are more frequently observed in PBT than in IMRT. Assessments of secondary cancer risk showed that PBT reduces the risk of secondary cancer in most organs, whereas IMRT is associated with a higher risk than CRT.

Assessment of radiation-induced second cancer risks in proton therapy and IMRT for organs inside the primary radiation field.

There is clinical evidence that second malignancies in radiation therapy occur mainly within the beam path, i.e. in the medium or high-dose region. The purpose of this study was to assess the risk for developing a radiation-induced tumor within the treated volume and to compare this risk for proton therapy and intensity-modulated photon therapy (IMRT). Instead of using data for specific patients we have created a representative scenario. Fully contoured age- and gender-specific whole body phantoms (4 year and 14 year old) were uploaded into a treatment planning system and tumor volumes were contoured based on patients treated for optic glioma and vertebral body Ewing's sarcoma. Treatment plans for IMRT and proton therapy treatments were generated. Lifetime attributable risks (LARs) for developing a second malignancy were calculated using a risk model considering cell kill, mutation, repopulation, as well as inhomogeneous organ doses. For standard fractionation schemes, the LAR for developing a second malignancy from radiation therapy alone was found to be up to 2.7% for a 4 year old optic glioma patient treated with IMRT considering a soft-tissue carcinoma risk model only. Sarcoma risks were found to be below 1% in all cases. For a 14 year old, risks were found to be about a factor of 2 lower. For Ewing's sarcoma cases the risks based on a sarcoma model were typically higher than the carcinoma risks, i.e. LAR up to 1.3% for soft-tissue sarcoma. In all cases, the risk from proton therapy turned out to be lower by at least a factor of 2 and up to a factor of 10. This is mainly due to lower total energy deposited in the patient when using proton beams. However, the comparison of a three-field and four-field proton plan also shows that the distribution of the dose, i.e. the particular treatment plan, plays a role. When using different fractionation schemes, the estimated risks roughly scale with the total dose difference in%. In conclusion, proton therapy can significantly reduce the risk for developing an in-field second malignancy. The risk depends on treatment planning parameters, i.e. an analysis based on our formalism could be applied within treatment planning programs to guide treatment plans for pediatric patients.