PET Reconstruction with a Spatially Varying Point Spread Function for a Brain Dedicated PET Insert for PET/MR

Abstract

Including accurate modeling of the point spread function (PSF) in positron emission tomography (PET) reconstruction algorithms results in improvements in image spatial resolution and contrast. In this work, we sampled the PSF in our first-generation radio-frequency brain dedicated PET insert for simultaneous PET/MR imaging using a 100 µCi NEMA standard 250 µm diameter Na-22 point source at 13 different positions within a subsection of the system field of view (FoV). The acquired list mode data was converted into the canonical sinogram format from which the spatial positioning of the source and standard deviations were calculated. The subset was then used to extrapolate the PSF for the full system FoV. This model was then fed as an input parameter into a graphical processing unit based ordered subset expectation maximization (OSEM) reconstruction algorithm and used to generate reconstructed images with and without spatially varying PSF modeling for the Na-22 point source and a Hoffman brain phantom. Results indicate that for point source reconstruction, the FWHM of the horizontal profile of the point source is smaller with spatially variant PSF especially closer to the edges. Effect of spatially varying PSF modeling is also presented with Hoffman phantom reconstruction and CNR value has increased with spatially varying PSF.