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Fissionable materials can be distinguished from normal materials by their emission of fast neutrons and neutrons moderated by surrounding materials. Radioisotopes can often be identified by their gamma-ray spectra. In this work, we use the nuclear physics Monte Carlo package MCNP6.2 to compare the detection efficiencies of different detector designs for the triple-mode detection of fast and moderated neutrons, and gamma-ray spectroscopy. For each design, we tabulate the detection efficiencies for neutrons from 0.1 eV to 5 MeV and for the full absorption of gamma rays from 0.1 to 5 MeV. All designs use 100 scintillators 1 cm × 1 cm × 5 cm. Of these, 36 are Cs2 LiLaBr6:Ce (90% 6Li) (CLLB) and 64 are polyvinyl toluene (PVT). The first design uses separate arrays of 6 × 6 CLLB and 8 × 8 PVT scintillators. Three other designs are 10 ×10 composite arrays using all 100 scintillators combined in different ways. PVT is a fast scintillator that can be used to detect fast neutrons by time-separated multiple proton recoils and discriminate against gammas. PVT in the three composite designs serves to moderate neutrons of all energies for capture by the 6Li in the CLLB. Gamma rays interact in the PVT and CLLB by Compton scattering and pair production; full energy absorption requires photoelectric absorption in the CLLB. The energy deposited by each gamma ray can be determined from a weighted sum of the CLLB and PVT signals from separate photodetectors. We find that for a fixed number of neutrons/cm2, one of the composite arrays has much higher 6Li detection efficiencies than the design that uses separate CLLB and PVT arrays, and has similar detection efficiencies for fast neutrons and gammas. We also find that in all cases, the average energy of the neutrons at capture by 6Li is well above the 25-meV thermal energy. [ABSTRACT FROM AUTHOR]

Automatic and fast identification of gamma-ray-emitting radionuclides is a challenge in the field of nuclear safety, especially in case of emergency, since it requires complex calculations and often the knowledge of experts to interpret the data. We present a development of an automatic identification method based on convolutional neural networks (CNNs) as a new tool to analyze gamma-ray spectra in real time, which uses not only photoelectric peaks but also extracts all discriminant features in the spectrum, such as Compton structures, for instance. The original approach relies on the training of the CNN with a fully synthetic database, built by means of a Monte Carlo simulation with Geant4 combined with a detailed analytical detector response model. The algorithm and training method are evaluated to identify radionuclides in measurements of the mixtures of sources acquired with Caliste, a fine-pitch CdTe imaging spectrometer. The neural network is able to discriminate each element in an arbitrary mixture very quickly with high accuracy. [ABSTRACT FROM AUTHOR]

Scatter correction is very important in 3-D PET reconstruction due to a large scatter contribution in measurements. Currently, one of the most popular methods is the so-called single scatter simulation (SSS), which considers single Compton scattering contributions from many randomly distributed scatter points. The SSS enables a fast calculation of scattering with a relatively high accuracy; however, the accuracy of SSS is dependent on the accuracy of tail fitting to find a correct scaling factor, which is often difficult in low photon count measurements. To overcome this drawback as well as to improve accuracy of scatter estimation by incorporating multiple scattering contribution, we propose a multiple scatter simulation (MSS) based on a simplified Monte Carlo (MC) simulation that considers photon migration and interactions due to photoelectric absorption and Compton scattering. Unlike the SSS, the MSS calculates a scaling factor by comparing simulated prompt data with the measured data in the whole volume, which enables a more robust estimation of a scaling factor. Even though the proposed MSS is based on MC, a significant acceleration of the computational time is possible by using a virtual detector array with a larger pitch by exploiting that the scatter distribution varies slowly in spatial domain. Furthermore, our MSS implementation is nicely fit to a parallel implementation using graphic processor unit (GPU). In particular, we exploit a hybrid CPU–GPU technique using the open multiprocessing and the compute unified device architecture, which results in 128.3 times faster than using a single CPU. Overall, the computational time of MSS is 9.4 s for a high-resolution research tomograph (HRRT) system. The performance of the proposed MSS is validated through actual experiments using an HRRT. [ABSTRACT FROM AUTHOR]

Modern radiotherapy (RT) techniques provide increasingly higher conformality, a potential invaluable clinical benefit to the patient. Consequently, in both single and multi-fractionated RT, patient misalignments and changing internal anatomy are also becoming more critical since higher conformality may equally represent a higher risk of target underdosage or organ-at-risk overdosage. Even with rigid fixation devices, maximum positioning errors higher than 1 cm are observable. In addition, anatomical morphological variations induced by cardiorespiratory or bowel motion, or RT-related biological responses, have been reported. The latter include tissue swelling, edema, inflammation, tumor shrinkage/growth, or filling of body cavities with unaccounted mucus or edematous tissue. State-of-the-art image-guided radiotherapy (IGRT) aims at providing feedback to the radiation oncologist in regard to these matters, some times at the cost of increased dosage (e.g. kilo and megavoltage IGRT), other times providing insufficient clinical information. We investigate a novel imaging system specially designed for monitoring both conventional and intensity/volumetric modulated photon radiotherapy (IMRT/VMRT, static and dynamic). The proof-of-principle and feasibility of such system indicate its potential for monitoring each field (and segment, for IMRT/VMRT) during all treatment fractions without whatsoever additional dose. We present a clear 2D correlation between the dose delivered in a heterogeneous phantom and the number of scattered photons detected perpendicular to the photon beam. Simulations of high-energy, multi-hole collimators show real-time, high-detectability of abnormal (though possible) irradiation scenarios with pertinent target morphological alterations, such as tumor dislocation or formation of edematous tissue. [ABSTRACT FROM PUBLISHER]

The detection of radioactive contraband is a critical problem in maintaining national security for any country. Gamma-ray emissions from threat materials challenge both detection and measurement technologies significantly. The development of a sequential, model-based Bayesian processor that captures both the underlying transport physics of gamma-ray emissions including Compton scattering and the measurement of photon energies offers a physics-based approach to attack this challenging problem. The inclusion of a basic radionuclide representation of absorbed/scattered photons at a given energy along with interarrival times is used to extract the physics information available from noisy measurements. It is shown that this representation leads to an “extended” physics-based structure that can be used to develop an effective sequential detection technique. The resulting model-based processor is applied to data obtained from a controlled experiment in order to assess its feasibility. [ABSTRACT FROM AUTHOR]

Hadron therapy for, e.g., cancer treatment requires an accurate dose deposition (total amount and location). As a consequence, monitoring is crucial for the success of the treatment. Currently employed PET imaging systems are not able to provide information about the deposed dose fast enough to allow stopping the therapy in case of a discordance with the treatment plan. We are currently investigating an imaging system based on a combined Compton scattering and pair creation camera capable of imaging gamma rays up to 50 MeV. The camera would be able to measure the complete spectrum of emitted gamma rays during the therapy session. We have performed Monte Carlo simulations for three different proton beam energies in a typical hadron therapy scenario. They show that the location of the gamma-ray distribution decay and the falloff region of the deposed dose are related. The reconstructed images prove that the proposed system could provide the required imaging and dose location capabilities. [ABSTRACT FROM AUTHOR]

Detectors and dosimeters are used all over the world for monitoring and detection of radiation. As an estimate device for worker's exposure, a dosimeter must go through a well determined calibration process in a radiation calibration facility, according to international standards. The most common way of calibration is to expose the dosimeter to several mono energy sources, like 241Am or 137Cs, while changing the source to detector distance. In this work, a single mono energy 137Cs source is used to create a wide energy spectrum calibration beam produced by Compton scattering from a copper target. The detector is shifted in a constant radius around the copper target and therefore exposed to energy determined by the angle of the Compton scattered photons. Target geometry optimization was done using the well known MCNP Monte Carlo simulation program and confirmed by experimental measurements. The work done so far, provides a starting point for a commercial dose calibration device based on Compton scattering. [ABSTRACT FROM AUTHOR]

A hybrid approach was developed to compute the dose deposited in cancerous and healthy tissues during stereotactic synchrotron radiation therapy treatment. The proposed approach divides the computation into two parts: (1) the dose deposited by primary radiation (coming directly from the incident X-ray beam) is calculated using a deterministic algorithm based on ray casting, optimized for transport in voxelized geometries; (2) the dose deposited by secondary radiation (Rayleigh and Compton scattering, fluorescence) is computed using a hybrid algorithm combining Monte Carlo and deterministic calculations. In the Monte Carlo part, a set of scattering and fluorescence events occurring in the patient is determined. These events are further processed in a deterministic way, which considerably improves the statistics of the final dose map. The results obtained in test cases are compared to those obtained with the Monte Carlo method alone (Geant4 and MCNPX codes) and found to be in excellent agreement. The proposed simulation scheme makes it possible to simulate dose maps with a single PC, featuring computation time and statistical fluctuations substantially reduced in comparison with full Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]