Quantitative accuracy considerations in dynamic state-of-the-art PET imaging (when average counts-per-LOR are (much) less than unity)

Abstract

State-of-the-art high resolution PET is now more than ever in need of scrutiny into the nature and limitations of the imaging modality itself as well as image reconstruction techniques. Particularly, we have discussed and addressed the following two considerations in the context of dynamic PET imaging: (i) The typical average numbers of counts-per-LOR are now (much) less than unity; (ii) The wide range of statistics (due to physical/biological decay of the activity) coupled with the aforementioned low count-rates-per-LOR further challenge the quantitative accuracy of dynamic reconstructions. In this context, we have argued theoretically and demonstrated experimentally, that the sinogram non-negativity constraint (when using the delayed coincidence and/or scatter subtraction techniques) will result in considerable overestimation biases. Two alternate schemes have been considered, and have been shown to remove the aforementioned bias. We have also investigated applicabilities of ordinary and convergent subsetized image reconstruction methods.