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Register a new userEvaluation of ambient dose equivalent rates influenced by vertical and horizontal distribution of radioactive cesium in soil in Fukushima Prefecture
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The air dose rate in an environment contaminated with 134Cs and 137Cs depends on the amount, depth profile and horizontal distribution of these contaminants within the ground. This paper introduces and verifies a tool that models these variables and calculates ambient dose equivalent rates at 1 m above the ground. Good correlation is found between predicted dose rates and dose rates measured with survey meters in Fukushima Prefecture in areas contaminated with radiocesium from the Fukushima Dai-ichi Nuclear Power Plant accident. This finding is insensitive to the choice for modelling the activity depth distribution in the ground using activity measurements of collected soil layers, or by using exponential and hyperbolic secant fits to the measurement data. Better predictions are obtained by modelling the horizontal distribution of radioactive cesium across an area if multiple soil samples are available, as opposed to assuming a spatially homogeneous contamination distribution. Reductions seen in air dose rates above flat, undisturbed fields in Fukushima Prefecture are consistent with decrement by radioactive decay and downward migration of cesium into soil. Analysis of remediation strategies for farmland soils confirmed that topsoil removal and interchanging a topsoil layer with a subsoil layer result in similar reductions in the air dose rate. These two strategies are more effective than reverse tillage to invert and mix the topsoil.
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A new variant of the pencil-beam (PB) algorithm for dose distribution calculation for radiotherapy with protons and heavier ions, the grid-dose spreading (GDS) algorithm, is proposed. The GDS algorithm is intrinsically faster than conventional PB algorithms due to approximations in convolution integral, where physical calculations are decoupled from simple grid-to-grid energy transfer. It was effortlessly implemented to a carbon-ion radiotherapy treatment planning system to enable realistic beam blurring in the field, which was absent with the broad-beam (BB) algorithm. For a typical prostate treatment, the slowing factor of the GDS algorithm relative to the BB algorithm was 1.4, which is a great improvement over the conventional PB algorithms with a typical slowing factor of several tens. The GDS algorithm is mathematically equivalent to the PB algorithm for horizontal and vertical coplanar beams commonly used in carbon-ion radiotherapy while dose deformation within the size of the pristine spread occurs for angled beams, which was within 3 mm for a single proton pencil beam of $30^circ$ incidence, and needs to be assessed against the clinical requirements and tolerances in practical situations.
The aim of this study was to investigate the impact of decay data provided by the newly developed stochastic atomic relaxation model BrIccEmis on dose point kernels (DPKs - radial dose distribution around a unit point source) and S-values (absorbed dose per unit cumulated activity) of 14 Auger electron (AE) emitting radionuclides, namely 67Ga, 80mBr, 89Zr, 90Nb, 99mTc, 111In, 117mSn, 119Sb, 123I, 124I, 125I, 135La, 195mPt and 201Tl. Radiation spectra were based on the nuclear decay data from the medical internal radiation dose (MIRD) RADTABS program and the BrIccEmis code, assuming both an isolated-atom and condensed-phase approach. DPKs were simulated with the PENELOPE Monte Carlo (MC) code using event-by-event electron and photon transport. S-values for concentric spherical cells of various sizes were derived from these DPKS using appropriate geometric reduction factors. The number of Auger and Coster-Kronig (CK) electrons and x-ray photons released per nuclear decay (yield) from MIRD-RADTABS were consistently higher than those calculated using BrIccEmis. DPKs for the electron spectra from BrIccEmis were considerably different from MIRD-RADTABS in the first few hundred nanometres from a point source where most of the Auger electrons are stopped. S-values were, however, not significantly impacted as the differences in DPKS in the sub-micrometre dimension were quickly diminished in larger dimensions. Overestimation in the total AE energy output by MIRD-RADTABS leads to higher predicted energy deposition by AE emitting radionuclides, especially in the immediate vicinity of the decaying radionuclides. This should be taken into account when MIRD-RADTABS data are used to simulate biological damage at nanoscale dimensions.
We present the results of in-situ measurements of $^{134}$Cs and $^{137}$Cs released from the Fukushima Nuclear Power Plant (FNPP) collected at surface and different depths in the western North Pacific in June and July 2012. It was found that 15 month after the incident concentrations of radiocesium in the Japan and Okhotsk seas were at background or slightly increased level, while they had increased values in the subarctic front area east of Japan. The highest concentrations of $^{134}$Cs and $^{137}$Cs up to 13.5 ${pm}$ 0.9 and 22.7 ${pm}$ 1.5 Bq m$^{-3}$ have been found to exceed ten times the background levels before the accident. Maximal content of radiocesium was observed within subsurface and intermediate water layers inside the cores of anticyclonic eddies (100 - 500 m). Even slightly increased content of radiocesium was found at some eddies at depth of 1000 m. It is expected that convergence and subduction of surface water inside eddies are main mechanisms of downward transport of radionuclides. In situ observations are compared with the results of simulated advection of these radioisotopes by the AVISO altimetric velocity field. Different Lagrangian diagnostics are used to reconstruct the history and origin of synthetic tracers imitating measured seawater samples collected in each of those eddies. The results of observations are consistent with the simulated results. It is shown that the tracers, simulating water samples with increased radioactivity to be measured in the cruise, really visited the areas with presumably high level of contamination. Fast water advection between anticyclonic eddies and convergence of surface water inside eddies make them responsible for spreading, accumulation and downward transport of cesium rich water to the intermediate depth in the frontal zone.
Purpose: The purpose of this work was to provide a flexible platform for FLASH research with protons by adapting a former clinical pencil beam scanning gantry to irradiations with ultrahigh dose rates. Methods: PSI Gantry 1 treated patients until December 2018. We optimized the beamline parameters to transport the 250 MeV beam extracted from the PSI COMET accelerator to the treatment room, maximizing the transmission of beam intensity to the sample. We characterized a dose monitor on the gantry to ensure good control of the dose, delivered in spot-scanning mode. We characterized the beam for different dose rates and field sizes for transmission irradiations. We explored scanning possibilities in order to enable conformal irradiations or transmission irradiations of large targets (with transverse scanning). Results: We achieved a transmission of 86 % from the cyclotron to the treatment room. We reached a peak dose rate of 9000 Gy/s at 3 mm water equivalent depth, along the central axis of a single pencil beam. Field sizes of up to 5x5 mm$^{2}$ were achieved for single spot FLASH irradiations. Fast transverse scanning allowed to cover a field of 16x1.2 cm$^{2}$. With the use of a nozzle-mounted range shifter we are able to span depths in water ranging from 19.6 to 37.9 cm. Various dose levels were delivered with a precision within less than 1 %. Conclusions: We have realized a proton FLASH irradiation setup able to investigate continuously a wide dose rate spectrum, from 1 to 9000 Gy/s in a single spot irradiation as well as in the pencil beam scanning mode. As such, we have developed a versatile test bench for FLASH research.
Purpose: Radiation therapy treatment planning is a trial-and-error, often time-consuming process. An optimal dose distribution based on a specific anatomy can be predicted by pre-trained deep learning (DL) models. However, dose distributions are often optimized based on not only patient-specific anatomy but also physician preferred trade-offs between planning target volume (PTV) coverage and organ at risk (OAR) sparing. Therefore, it is desirable to allow physicians to fine-tune the dose distribution predicted based on patient anatomy. In this work, we developed a DL model to predict the individualized 3D dose distributions by using not only the anatomy but also the desired PTV/OAR trade-offs, as represented by a dose volume histogram (DVH), as inputs. Methods: The desired DVH, fine-tuned by physicians from the initially predicted DVH, is first projected onto the Pareto surface, then converted into a vector, and then concatenated with mask feature maps. The network output for training is the dose distribution corresponding to the Pareto optimal DVH. The training/validation datasets contain 77 prostate cancer patients, and the testing dataset has 20 patients. Results: The trained model can predict a 3D dose distribution that is approximately Pareto optimal. We calculated the difference between the predicted and the optimized dose distribution for the PTV and all OARs as a quantitative evaluation. The largest average error in mean dose was about 1.6% of the prescription dose, and the largest average error in the maximum dose was about 1.8%. Conclusions: In this feasibility study, we have developed a 3D U-Net model with the anatomy and desired DVH as inputs to predict an individualized 3D dose distribution. The predicted dose distributions can be used as references for dosimetrists and physicians to rapidly develop a clinically acceptable treatment plan.
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