Model-based compensation for quantitative 123I brain SPECT imaging

Previously we have developed a model-based method that can accurately estimate downscatter contamination from high-energy photons in 123I imaging. In this work we combined the model-based method with iterative reconstruction-based compensations for other image-degrading factors such as attenuation, scatter, the collimator-detector response function (CDRF) and partial volume effects to form a comprehensive method for performing quantitative 123I SPECT image reconstruction. In the model-based downscatter estimation method, photon scatter inside the object was modelled using the effective source scatter estimation (ESSE) technique, including contributions from all the photon emissions. The CDRFs, including the penetration and scatter components due to the high-energy 123I photons, were estimated using Monte Carlo (MC) simulations of point sources in air at various distances from the face of the collimator. The downscatter contamination was then compensated for during the iterative reconstruction by adding the estimated results to the projection steps. The model-based downscatter compensation (MBDC) was evaluated using MC simulated and experimentally acquired projection data. From the MC simulation, we found about 39% of the total counts in the energy window of 123I were attributed to the downscatter contamination, which reduced image contrast and caused a 1.5% to 10% overestimation of activities in various brain structures. Model-based estimates of the downscatter contamination were in good agreement with the simulated data. Compensation using MBDC removed the contamination and improved the image contrast and quantitative accuracy to that of the images obtained from 159 keV photons. The errors in absolute quantitation were reduced to within +/-3.5%. The striatal specific binding potential calculated based on the activity ratio to the background was also improved after MBDC. The errors were reduced from -4.5% to -10.93% without compensation to -0.55% to 4.87% after compensation. The model-based method provided accurate downscatter estimation and, when combined with iterative reconstruction-based compensations, accurate quantitation was obtained with minimal loss of precision.