Novel methods for estimating 3D distributions of radioactive isotopes in materials

In recent years, various gamma-ray visualization techniques, or gamma cameras, have been proposed. These techniques are extremely effective for identifying “hot spots” or regions where radioactive isotopes are accumulated. Examples of such would be nuclear-disaster-affected areas such as Fukushima or the vicinity of nuclear reactors. However, the images acquired with a gamma camera do not include distance information between radioactive isotopes and the camera, and hence are “degenerated” in the direction of the isotopes. Moreover, depth information in the images is lost when the isotopes are embedded in materials, such as water, sand, and concrete. Here, we propose two methods of obtaining depth information of radioactive isotopes embedded in materials by comparing (1) their spectra and (2) images of incident gamma rays scattered by the materials and direct gamma rays. In the first method, the spectra of radioactive isotopes and the ratios of scattered to direct gamma rays are obtained. We verify experimentally that the ratio increases with increasing depth, as predicted by simulations. Although the method using energy spectra has been studied for a long time, an advantage of our method is the use of low-energy (50–150 keV) photons as scattered gamma rays. In the second method, the spatial extent of images obtained for direct and scattered gamma rays is compared. By performing detailed Monte Carlo simulations using Geant4, we verify that the spatial extent of the position where gamma rays are scattered increases with increasing depth. To demonstrate this, we are developing various gamma cameras to compare low-energy (scattered) gamma-ray images with fully photo-absorbed gamma-ray images. We also demonstrate that the 3D reconstruction of isotopes/hotspots is possible with our proposed methods. These methods have potential applications in the medical fields, and in severe environments such as the nuclear-disaster-affected areas in Fukushima.