Assessment of the Contrast to Noise Ratio in PET Scanners with Monte Carlo Methods

Abstract

The aim of the present study was to assess the contrast to noise ratio (CNR) of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction. The PET scanner simulated was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution. Image quality was assessed in terms of the CNR. CNR was estimated from coronal reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL. OSMAPOSL reconstruction was assessed by using various subsets (3, 15 and 21) and various iterations (2 to 20). CNR values were found to decrease when both iterations and subsets increase. Two (2) iterations were found to be optimal. The simulated PET evaluation method, based on the TLC plane source, can be useful in image quality assessment of PET scanners.