RESUMO
The iterative image reconstruction (IIR) is a promising approach to achieve a better image quality in PET. However, limitations exist with respect to the required computation time and the influence of reconstruction parameters on quantitative PET data. We implemented different reconstruction algorithms in a PC based reconstruction program and evaluated the effect of the reconstruction algorithms as well as reconstruction parameters on the quantitative PET results. The following IIR algorithms were implemented: maximum likelihood expectation maximization (LMEM), weighted least squares (WLS), image space reconstruction algorithm (ISRA), space alternating generalized expectation maximization (SAGE). The ordered subsets (OS) method and the median root prior (MRP) correction were provided and can be used in combination with each reconstruction algorithm. A dynamic PET study, showing small liver metastases, was used for the evaluation of the properties of the reconstruction parameters. Regions-of-Interest (ROI) were placed in a small high uptake area as well as in a larger low uptake region for quantification purpose using standardized uptake values (SUV). The 128x128 image matrix was generally not suffient to detect the metastases as separate lesions and a 256x256 matrix was required for the delineation of the lesions. Furthermore, the use of the iterative attenuation correction improved the image quality significantly...