USE OF SCANNER CHARACTERISTICS IN ITERATIVE IMAGE-RECONSTRUCTION FOR HIGH-RESOLUTION POSITRON EMISSION TOMOGRAPHY STUDIES OF SMALL ANIMALS

The purpose of this work was to improve of the spatial resolution of a whole-body positron emission tomography (PET) system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially va riant line-spread function (LSF), which was determined from 49 activat ed copper-64 line sources positioned over a field of view (FOV) of 21. 0 cm. This information was used to model the image degradation process . During the course of iterative image reconstruction, the forward pro jection of the estimated image was blurred with the LSF at each iterat ion step before the estimated projections were compared with the measu red projections. The imaging characteristics of the high-resolution al gorithm were investigated in phantom experiments. Moreover, imaging st udies of a rat and two nude mice were performed to evaluate the imagin g properties of our approach in vivo. The spatial resolution of the sc anner perpendicular to the direction of projection could be approximat ed by a one-dimensional Gaussian-shaped LSF with a full-width at half- maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial dis tance of 10.5 cm. The incorporation of this blurring kernel into the i teration formula resulted in a significantly improved spatial resoluti on of about 3.9 mm over the examined FOV. As demonstrated by the phant om and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scan s but also improved the accuracy for quantitating activity concentrati ons in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy inco rporates the image restoration step directly into the process of algeb raic image reconstruction and obviates the need for ill-conditioned '' deconvolution'' procedures to be performed on the projections or on th e reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals.