Using ANN for thermal neutron shield designing for BNCT treatment room.

Occupational radiation protection should be applied to the design of treatment rooms for various radiation therapy techniques, including BNCT, where escaping particles from the beam port of the beam shaping assembly (BSA) may reach the walls or penetrate through the entrance door. The focus of the present study is to design an alternative shielding material, other than the conventional material of lead, that can be considered as the material used in the door and be able to effectively absorb the BSA neutrons which have slowed down to the thermal energy range of < 1 eV after passing through the walls and the maze of the room. To this aim, a thermal neutron shield, composed of polymer composite and polyethylene, has been simulated using the Geant4 Monte Carlo code. The neutron flux and dose values were predicted using an artificial neural network (ANN), eliminating the need for time-consuming Monte Carlo simulations in all possible suggestions. Additionally, this technique enables simultaneous optimization of the parameters involved, which is more effective than the traditional sequential and separate optimization process. The results indicated that the optimized shielding material, chosen through ANN calculations that determined the appropriate thickness and weight percent of its compositions, can decrease the dose behind the door to lower than the allowable limit for occupational exposure. The stability of ANN was tested by considering uncertainties with the Gaussian distributions of random numbers to the testing data. The results are promising as they indicate that ANNs could be used as a reliable tool for accurately predicting the dosimetric results, providing a drastically powerful alternative approach to the time-consuming Monte Carlo simulations.

Thermal neutron beam optimization for PGNAA applications using Q-learning algorithm and neural network.

As a powerful, non-destructive analysis tool based on thermal neutron capture reaction, prompt gamma neutron activation analysis (PGNAA) indeed requires the appropriate neutron source. Neutrons produced by electron Linac-based neutron sources should be thermalized to be appropriate for PGNAA. As a result, thermalization devices (TDs) are used for the usual fast neutron beam to simultaneously maximize the thermal neutron flux and minimize the non- thermal neutron flux at the beam port of TD. To achieve the desired thermal neutron flux, the optimized geometry of TD including the proper materials for moderators and collimator, as well as the optimized dimensions are required. In this context, TD optimization using only Monte Carlo approaches such as MCNP is a multi-parameter problem and time-consuming task. In this work, multilayer perceptron (MLP) neural network has been applied in combination with Q-learning algorithm to optimize the geometry of TD containing collimator and two moderators. Using MLP, both thickness and diameter of the collimator at the beam port of TD have first been optimized for different input electron energies of Linac as well as for moderators' thickness values and the collimator. Then, the MLP has been learned by the thermal and non-thermal neutron flux simultaneously at the beam port of TD calculated by MCNPX2.6 code. After selecting the optimized geometry of the collimator, a combination of Q-learning algorithm and MLP artificial neural network have been used to find the optimal moderators' thickness for different input electron energies of Linac. Results verify that the final optimum setup can be obtained based on the prepared dataset in a considerably smaller number of simulations compared to conventional calculation methods as implemented in MCNP.

Combining CNN and Q-learning for increasing the accuracy of lost gamma source finding.

The increasing use of nuclear technology in various fields makes it necessary to provide the required safety to work with this industry. Gamma source is one of the most widely used sources in industry and medicine. Finding a lost gamma source in a gamma irradiation room without human presence is challenging due to the particular arrangements and barriers in the room for radiation shielding and requires an efficient and robust method. In this paper, locating and routing the lost gamma source in the gamma irradiation room containing radiation blocking barriers are done simultaneously by using two methods, convolutional neural network (CNN) and Q-learning, which are powerful algorithms for deep learning and machine learning. Environment simulation with gamma source was performed using Geant4 simulation. The results show that by combining these two methods in geometries with radiation blocking barriers, in addition to locating with 90% accuracy, routing can also be performed. Although the presence of thick barriers in the room reduces the accuracy, increases the time required to finding the lost gamma source or the inefficiency of other methods, nevertheless, the results show that combination of CNN and Q-learning reduces the time and greatly increases the accuracy.

Development of a novel approach for construction of high gradient braze-free S-band cavities.

Vacuum breakdown is one of the main limitations to the operating accelerating gradient in radio frequency linear accelerators. Recent studies of copper cavities have been shown that harder copper conditions more quickly and can reach higher accelerating gradients than soft copper cavities. Exploiting this advantage requires the development of assembly methods that do not involve the copper-softening high-temperature heating cycles that are used in for example bonding and brazing. A shrink-fit method, which was already implemented successfully in the operation the IPM linac, is proposed for the construction high-gradient test S-band standing wave structure operating at 2998.5 MHz. The three cells cavity is designed to have a maximum gradient in the middle cell that is twice that of the adjacent cells. Mechanical considerations relating to the shrink-fit construction method have been performed using Ansys. To validate the simulations and ensure the feasibility of construction by shrink-fit method, a sample cavity was constructed and cold tests was performed.

Effect of constant collision mean free time on the boundary layer of the active collisional warm plasma.

The plasma boundary layer is analyzed for a plasma in contact with a conducting plain surface where the ion temperature is comparable with the electron temperature and the plasma pressure is sufficiently high. The variations of electrical potential from the plasma-presheath boundary to the wall is studied using the fluidal formalism of plasma in three approaches; plasma and sheath asymptotic solutions and full solution. In the full solution approach, fluidal equations lead to a singularity when the ion velocity reaches the ion thermal speed. It is shown that removing the singularity causes a well-defined eigenvalue problem and leads to smooth solutions for the model equations. Some of the applicable aspects such as the floating velocity and density of ions, the floating electrical potential and an estimation of the floating thickness of the boundary layer are obtained. The dependency of these quantities on the ionization degree, the ion temperature and ion-neutral collision is examined too.

Effect of human body position on gamma radiation dose rate from granite stones.

The use of granite stones as building materials in homes or offices can result in the residents' long-term whole-body exposure to gamma radiation. Although the whole-body annual dose has been investigated in the literature, it is obvious that different human organs receive different equivalent dose due to different position respect to the walls and floor covered by granite stones. In this paper, the effect of distance from the walls and floor of a room on the equivalent dose is investigated by using MCNPX code. An "ORNL" phantom is simulated in three situations; standing (P1), sleeping one meter above the floor (P2) and sleeping on the floor (P3) and the equivalent dose in different organs is calculated. Excess lifetime cancer risk (ELCR) is calculated in the whole of the body for these three positions. By the results, the value of ELCR in the third position is more than the average world value (2.9 × 10-4). The results show the importance of considering body position in dose determination, especially in some organs such as the brain and eyes which are close to the granite stones in certain positions such as sleeping.

Dose reduction in HDR brachytherapy of esophageal cancer using gold and gold alloy plaques: a Monte Carlo study.

In this work, the use of gold and gold alloy plaques is proposed for the first time, to reduce the dose to healthy organs in brachytherapy with Ir-192 sources. For dose simulations in tumour and healthy tissue, the MCNPX Monte Carlo code was used. The radiation source implemented in those simulations was benchmarked with well-known TG-43 criteria of dose rate constant, air-kerma strength, radial dose function, and 2D anisotropy function. For various arrangements of iridium sources and plaques of gold and gold alloy of various thicknesses, the dose distributions in an esophagus tumour and in surrounding healthy organs were simulated. The results showed that while the dose to the tumour is not much affected by the presence of gold plaques with a thickness of 3.5 mm in an optimized 192Ir sources' configuration, a relative reduction in average organ dose of 64%, 65%, 73%, 67%, and 35% was observed, for esophagus, thyroid, heart, stomach, and liver, respectively. Moreover, it was found that a gold plaque leads to smaller doses to healthy organs than a gold alloy plaque. It is concluded that gold plaques can be used to improve the treatment of esophageal cancer by HDR brachytherapy and to protect surrounding non-target organs.

Distribution modeling of nanoparticles for brachytherapy of human eye tumor.

BACKGROUND: Due to their unique properties, gold nanoparticles (GNPs) have been proposed to be used for a wide range of applications, especially for photon radiation therapy. In addition to experimental works, there are worthwhile simulation-based studies focused on the investigation of the effect of parameters governing the dose enhancement due to the presence of GNPs in tissue. In a recently published study, we found that the distribution of GNPs in a single cell plays an important role in nucleus dose enhancement. METHODS: The present work investigates the sensitivity of dose enhancement of a macroscopic phantom to the modeling of GNPs at the cellular level by using the MCNPX Monte Carlo code. A human eye phantom containing the realistic structures and materials was simulated, with a typical tumor located in its corner filled with three different patterns of distribution of GNPs around the nuclei of the cells. The primary photons emit from a COMS eye plaque brachytherapy containing thirteen 131Cs seeds in the vicinity of the tumor. RESULTS: The study was extended to estimate dose enhancement for various concentration, size, and density of the GNPs accumulated around the nuclei of the tumor. Moreover, the dose delivered to the healthy eye structures for different models has been investigated and discussed. The results show obvious differences between the dose enhancements in the tumor depending on the modeling of GNPs. CONCLUSION: The results emphasized that an appropriate small-scale model for the distribution of GNPs in the cell would be of high importance to estimate the degree of dose enhancement in a macroscopic phantom to provide a trustworthy prediction to move towards clinical application.

Effect of modeling porous media on the response of gamma-gamma well-logging tool.

The well logging is known as a technique of making petrophysical measurements in the sub-surface earth formations through a drilled borehole to reach the characterization of the physical properties of rocks and fluids. Considering the fact that reservoirs are complex fractured media which the fluid can flow through the porosities, the distribution model of oil in the medium needs to be investigated in detail and to be well quantified. To study this effect, a typical gamma-gamma logging tool containing 137Cs source and two NaI detectors was modeled by using the MCNPX code. The medium was filled with numerous matrix-shaped blocks, each including rectangular cubes for modeling the oil flow in the formation. For an arbitrary set of oil concentrations and various formation materials, the response of the detectors for this model was studied. Taking into account the results corresponding to the traditional homogeneous mixture model for the formation, it was found that the deviations between the count rates for two models reach to about 10% and 22% for short spacing and far spacing detectors, respectively. The results also show that the slopes of the straight-line fits to the count rates, which is important for the evaluation of the density, deviate between about 73.3% and 53.8% for two simulated models. Investigating the effect of the presence of the drilling fluid on the count rate of the proposed model showed that for a given thickness of mudcake and the formation density, both detectors show approximately the same percentage of change in counting rate. However, these counts for the proposed model deviate from those of the mixture model between 5.1% and 28%. It can be concluded that defining a model for describing heterogeneities of a natural porous medium can effectively account for the prediction of density measurement in logging tools.

On the importance of modeling gold nanoparticles distribution in dose-enhanced radiotherapy.

Purpose: To investigate the effect of precise modeling for Monte Carlo simulations of gold nanoparticles (GNPs) dose-enhanced radiotherapy, two models characterized by their distribution of GNPs in a simulated macroscopic cubic tumor were introduced. The motivation was the widely documented tendency of GNPs to localize around the cell nucleus. Methods: The introduced models composed of 2.7×107 ellipsoid cells, each of them containing a centrally located nucleus as the target for dose evaluation. In the first model, the spheres of GNP are homogeneously distributed in the whole tumor volume, and in the latter, GNPs are localized in the cytoplasms surrounded the nuclei. Results: The results achieved through applying Monte Carlo radiation transports using the Mont Carlo N-Particle eXtended code (MCNPX) show an underestimation of nuclear dose enhancement caused by homogeneous model compared with that of heterogeneous distribution. By investigating various quantities, it was found that subcellular location of GNPs strongly governs the sensitivity of dose enhancement to the number and concentration of GNPs targeted in the tumor. Other obvious differences are revealed by studying the dose enhancement curves in depth of the tumor. While the heterogeneous model predicts an approximately constant dose enhancement in depth for primary photon energies of 50 keV and more, the homogeneous model estimates an energy-dependent increase of about 11 to 30%. Conclusion: It can be concluded that defining a model in accordance with the experimental observations can effectively account for accurate prediction of macroscopic dose enhancement in the target of interest.

BNCT of skin tumors using the high-energy D-T neutrons.

Owing to the continuing need for providing improved and universally accepted facilities to be used in radiation therapies, a number of recently published BNCT-related studies have focused on investigating appropriate neutron sources as alternatives for nuclear reactors. Of special interest are D-T neutron generators, which theoretically have shown the potential to be utilized as neutron sources for BNCT of deep-seated tumors. This work is devoted to investigate the feasibility of using the high-energy neutrons emitted from these generators for treatment of surface tumors, especially skin. Using a set of MCNPX simulations, the D-T neutrons are passed through an optimized arrangement of materials to slow-down toward the desired energy range, and to remove the neutron and gamma contamination considering the IAEA recommended criteria, especially determined for pre-clinical survey for treatment of surface tumors. By assessment with these parameters, it is shown that the designed beam, corresponding to a configuration composed of natural uranium as neutron multiplier, D2O as moderator, Pb as reflector, Bi as gamma filter, and polyethylene and BeO as collimators provides high-intensity of desired neutrons, and low-background doses as well. It was found that an appropriate material for collimator, if accompanied with an optimized geometry, is an important parameter for keeping the undesired components to the recommended level. A typical simulated phantom, subjected to the irradiation of the designed spectrum, is used to study the performance of the resultant beam in shallow tissue. For an arbitrary chosen 10B concentration, the evaluated depth-dose curves show that the proposed configuration establishes acceptable agreement between the appropriate neutron intensity and penetration to desired depth in tissue in a reasonable treatment time of about 25-38min. Considering the simulations carried out, the total dose delivered to the tumor is expected to be of about 4.2 times higher than that delivered to the first depths in healthy tissue, and of about 2.4 times higher than that delivered to the normal skin. These results in essence endorse the ability of D-T neutron generators to be used for BNCT of surface tumors, even with the yield of ∼1012n/s.

Water or realistic compositions in proton radiotherapy? An analytical study.

PURPOSE: Pre-clinical tests and simulation studies for radiotherapy are generally carried out using water or simplified materials. Investigating the effects of defining compositionally realistic media in proton transport studies was the objective of this work. Accurate modeling of the Bragg curve is a fundamental requirement for such a study. METHODS AND MATERIALS: An equation previously validated by experiments provides an appropriate analytical method for proton dose calculation in depth of the target. Owing to the dependency on protons ranges and the probability of undergoing non-elastic nuclear interactions (NNI), this formula comprises three parameters with values specified for initial proton energy and for the target material. As a result, knowledge of the depth-dose distribution using this analytical model is limited to the materials for which the data has been provided in nuclear data tables. In this study, we used our general formulas for calculating the protons ranges and the probability of undergoing NNI in desired compounds and mixtures with an arbitrary number of constituent elements. Furthermore, the protons dose distribution in the depth of these targets was leading off with determining the parameters appeared in the employed model using our mathematically easy to handle relations. For a number of tissues which may be of interest in proton radiotherapy studies but are missing in reference data tables, the mentioned parameters were calculated. Moreover, the resultant values for the protons ranges and the probability of undergoing NNIs were compared with those in water. RESULTS: The results showed that the differences between the position of Bragg peaks in water and realistic media considered in this study were energy dependent, and ranged between a few millimeters. For proton beams of arbitrary chosen initial energies, the maximum dose delivered to the realistic media varied between about -0.02-4.42% in comparison with that to water. CONCLUSIONS: The effects observed (both in penetration and in the magnitude of the Bragg peaks) may be overshadowed by the different dose prescriptions depending on the quality of the treatment planning system, and dosimetry protocols used at the various therapy centers.

Ocular brachytherapy dosimetry for 103Pd and 125I in the presence of gold nanoparticles: a Monte Carlo study.

The aim of the present Monte Carlo study is to evaluate the variation of energy deposition in healthy tissues in the human eye which is irradiated by brachytherapy sources in comparison with the resultant dose increase in the gold nanoparticle (GNP)-loaded choroidal melanoma. The effects of these nanoparticles on normal tissues are compared between 103Pd and 125I as two ophthalmic brachytherapy sources. Dose distribution in the tumor and healthy tissues has been taken into account for both brachytherapy sources. Also, in certain points of the eye, the ratio of the absorbed dose by the normal tissue in the presence of GNPs to the absorbed dose by the same point in the absence of GNPs has been calculated. In addition, differences of the absorbed dose in the tumor observed in the comparison of simple water phantom and actual simulated human eye in presence of GNPs are also a matter of interest that have been considered in the present work. The difference between the eye globe and the water phantom is more obvious for 125I than that of the 103Pd when the ophthalmic dosimetry is done in the presence of GNPs. Whenever these nanoparticles are utilized in enhancing the absorbed dose by the tumor, the use of 125I brachytherapy source will greatly amplify the amount of dose enhancement factor (DEF) in the tumor site without inflicting much dam-age to healthy organs, when compared to the 103Pd source. For instance, in the concentration of 30 mg GNPs, the difference amongst the calculated DEF for 125I between these phantoms is 5.3%, while it is 2.45% for 103Pd. Furthermore, in Monte Carlo studies of eye brachytherapy, more precise definition of the eye phantom instead of a water phantom will become increasingly important when we use 125I as opposed to 103Pd.

Technical Note: On the analytical proton dose evaluation in compounds and mixtures.

PURPOSE: By combining the physical processes occurring due to the interaction of protons with matter, analytical theories published so far have provided acceptable models for calculating depth-dose distributions in homogeneous media. As a well-defined and comprehensive theory, the formula derived by Bortfeld models the dose transferred to the target in terms of the parabolic cylinder function. The model also includes three parameters with values specified for an initial proton energy and for the target material. These parameters are obtainable through the data gathered in nuclear data tables. The analytical studies using this interesting model are therefore restricted to those materials for which the data have been provided in these tables. This study aims to find general solutions for calculation of these parameters for a compound or mixture composed of an arbitrary choice of constituent elements. METHODS: Inspired by formulas dedicated for calculating the range and the probability of undergoing nonelastic nuclear interactions for protons in desired compounds, the analytical methods for finding the three mentioned parameters are investigated. The accuracy of the methods suggested is examined through comparison of the results with those which are calculated using the data taken from nuclear data tables. By employing the calculated parameters using the derived formulas in the Bortfeld model, the dose distribution at depth in a chosen target is calculated. RESULTS: For an arbitrary selection of compounds, the predictions of the analytical depth-dose model using these parameters have been found to closely match the results employing the parameters calculated using the data reported in nuclear data tables. CONCLUSIONS: The formulas presented are general, mathematically easy to handle, and valid for almost every compound or mixture including materials of interest for proton radiotherapy purposes, making the Bortfeld model more practical and advantageous.

Gold nanoparticle-based brachytherapy enhancement in choroidal melanoma using a full Monte Carlo model of the human eye.

The effects of gold nanoparticles (GNPs) in 125I brachytherapy dose enhancement on choroidal melanoma are examined using the Monte Carlo simulation technique. Usually, Monte Carlo ophthalmic brachytherapy dosimetry is performed in a water phantom. However, here, the compositions of human eye have been considered instead of water. Both human eye and water phantoms have been simulated with MCNP5 code. These simulations were performed for a fully loaded 16 mm COMS eye plaque containing 13 125I seeds. The dose delivered to the tumor and normal tissues have been calculated in both phantoms with and without GNPs. Normally, the radiation therapy of cancer patients is designed to deliver a required dose to the tumor while sparing the surrounding normal tissues. However, as the normal and cancerous cells absorbed dose in an almost identical fashion, the normal tissue absorbed radiation dose during the treatment time. The use of GNPs in combination with radiotherapy in the treatment of tumor decreases the absorbed dose by normal tissues. The results indicate that the dose to the tumor in an eyeball implanted with COMS plaque increases with increasing GNPs concentration inside the target. Therefore, the required irradiation time for the tumors in the eye is decreased by adding the GNPs prior to treatment. As a result, the dose to normal tissues decreases when the irradiation time is reduced. Furthermore, a comparison between the simulated data in an eye phantom made of water and eye phantom made of human eye composition, in the presence of GNPs, shows the significance of utilizing the composition of eye in ophthalmic brachytherapy dosimetry Also, defining the eye composition instead of water leads to more accurate calculations of GNPs radiation effects in ophthalmic brachytherapy dosimetry.

Technical Note: On the proton range and nuclear interactions in compounds and mixtures.

PURPOSE: Range and probability of nonelastic nuclear interactions (NNIs) for protons can be found only for a limited number of compounds and mixtures in nuclear data tables, and the proton-related analytical studies are therefore restricted to those materials for which the data are provided in these documents. In this paper, the authors present general solutions for calculating the proton range and probability of NNIs for desired compounds and mixtures. METHODS: Benefiting from the Bragg-Kleeman approximation of mass stopping power, the authors derive a concise formula for calculating the proton range in materials with arbitrary number of constituent elements. Additionally, the authors propose another relation for obtaining the probability of undergoing NNIs which is suggested to be additive. RESULTS: The examination of the formula presented shows that the authors' method can be considered as general solutions for analytical evaluation of the range in compounds and mixtures. The formula proposed for probability of NNIs is valid for almost every compound except for those materials containing H. It is shown that this formula can be modified so that it covers these materials. CONCLUSIONS: The authors present a general analytical method for calculating the range and probability of NNIs for protons which are mathematically easy to handle and valid for desired compounds or mixtures composed of an arbitrary number of constituent elements, including materials of interest for proton radiotherapy purposes.

A study on the optimum fast neutron flux for boron neutron capture therapy of deep-seated tumors.

High-energy neutrons, named fast neutrons which have a number of undesirable biological effects on tissue, are a challenging problem in beam designing for Boron Neutron Capture Therapy, BNCT. In spite of this fact, there is not a widely accepted criterion to guide the beam designer to determine the appropriate contribution of fast neutrons in the spectrum. Although a number of researchers have proposed a target value for the ratio of fast neutron flux to epithermal neutron flux, it can be shown that this criterion may not provide the optimum treatment condition. This simulation study deals with the determination of the optimum contribution of fast neutron flux in the beam for BNCT of deep-seated tumors. Since the dose due to these high-energy neutrons damages shallow tissues, delivered dose to skin is considered as a measure for determining the acceptability of the designed beam. To serve this purpose, various beam shaping assemblies that result in different contribution of fast neutron flux are designed. The performances of the neutron beams corresponding to such configurations are assessed in a simulated head phantom. It is shown that the previously used criterion, which suggests a limit value for the contribution of fast neutrons in beam, does not necessarily provide the optimum condition. Accordingly, it is important to specify other complementary limits considering the energy of fast neutrons. By analyzing various neutron spectra, two limits on fast neutron flux are proposed and their validity is investigated. The results show that considering these limits together with the widely accepted IAEA criteria makes it possible to have a more realistic assessment of sufficiency of the designed beam. Satisfying these criteria not only leads to reduction of delivered dose to skin, but also increases the advantage depth in tissue and delivered dose to tumor during the treatment time. The Monte Carlo Code, MCNP-X, is used to perform these simulations.

Design and optimization of a beam shaping assembly for BNCT based on D-T neutron generator and dose evaluation using a simulated head phantom.

A feasibility study was conducted to design a beam shaping assembly for BNCT based on D-T neutron generator. The optimization of this configuration has been realized in different steps. This proposed system consists of metallic uranium as neutron multiplier, TiF(3) and Al(2)O(3) as moderators, Pb as reflector, Ni as shield and Li-Poly as collimator to guide neutrons toward the patient position. The in-air parameters recommended by IAEA were assessed for this proposed configuration without using any filters which enables us to have a high epithermal neutron flux at the beam port. Also a simulated Snyder head phantom was used to evaluate dose profiles due to the irradiation of designed beam. The dose evaluation results and depth-dose curves show that the neutron beam designed in this work is effective for deep-seated brain tumor treatments even with D-T neutron generator with a neutron yield of 2.4×10(12) n/s. The Monte Carlo Code MCNP-4C is used in order to perform these calculations.