Modeling of high-energy contamination in SPECT imaging using Monte Carlo simulation

¹²³I is a commonly used radioisotope employed in neurotransmitter SPECT studies. In addition to an intense line at 159 keV, the decay scheme of this radioisotope includes a low yield (∼3%) of higher energy photons which make a non-negligible contribution to the final image when low-energy high-resolution (LEHR) collimators are used. This contribution of high-energy photons may reach ∼28% of the total counts in the projections. The aim of this work is to model each energy component of the high-energy Point Spread Function (hPSF) for fan-beam LEHR collimators in order to develop fast Monte Carlo (MC) simulations of high-energy ray contamination. The modeling of hPSF was based on the results of simulating photons through the collimator-detector system using the MC code PENELOPE. Since low-energy PSFs models for fan-beam collimators tend to a Gaussian distribution, we use the same function for the hPSF modeling for high-energy photons. The parameters of these Gaussian functions (g(x,y)) were obtained by minimizing the root mean square error (RMS) using the sensitivity of the simulated hPSFs as a constraint. The hPSFs were parameterized for a range of energies between 350 keV and 538 keV. The RMS attained after fitting of g(x,y) to the simulated hPSFs was always smaller than ∼2% of the mean sensitivity per pixel of the image. A strong dependence of the sensitivity on the type and thickness of the backscatter material behind the crystal was found. Our results indicate that Gaussian distributions approximate the hPSF responses for fan-beam collimators. This model will be an important tool to accelerate MC simulations of radiolabeled compounds which emit medium- or high-energy rays.