PT - JOURNAL ARTICLE AU - Jing Tang AU - Frank Bengel AU - Yun Zhou AU - Paco Bravo AU - Arman Rahmim TI - Direct 4D parametric image reconstruction for dynamic cardiac PET imaging DP - 2011 May 01 TA - Journal of Nuclear Medicine PG - 1996--1996 VI - 52 IP - supplement 1 4099 - http://jnm.snmjournals.org/content/52/supplement_1/1996.short 4100 - http://jnm.snmjournals.org/content/52/supplement_1/1996.full SO - J Nucl Med2011 May 01; 52 AB - 1996 Objectives Conventional dynamic myocardial perfusion PET imaging consists of reconstructing data frames individually followed by compartmental analysis to estimate kinetic parameters. The goal of this study is to develop and evaluate (through simulation) a direct parametric image reconstruction method for dynamic cardiac PET studies. Methods We developed a preconditioned steepest ascent (PSA) method that incorporates the one-tissue compartmental model to directly reconstruct parametric images from dynamic sinogram frames. The log-likelihood function for the direct 4D reconstruction has the myocardial activity represented as the contribution from plasma and myocardial tissue. It was maximized with respect to each of the involved kinetic parameters. Rb-82 PET patient organ time activity curves including blood pool and myocardium were acquired and fitted to generate a set of K1, k2, and vB values. The corresponding parametric images created from the XCAT phantom served as the truth for simulation. Image frames created from the parametric images (and the input function) were projected to generate the sinogram frames. Noise comparable to the clinical data level was added. To evaluate the results, polar maps were created from estimated K1 values on the left ventricular myocardium. We compared the resulted K1 polar maps from the PSA direct reconstruction and that from fitting the individually reconstructed 3D image frames. Results The K1 values on the whole polar map and its segments estimated from the PSA direct reconstruction showed significantly improved bias versus noise performance compared to those from fitting the compartmental model to individually reconstructed image frames. Conclusions A direct parametric image reconstruction method was developed to incorporate kinetic modeling in the reconstruction of dynamic cardiac PET data. With realistic simulation, we have demonstrated improved performance of the proposed technique over the conventional method on estimation of the myocardial rate constants