Parametric imaging of a two-injection, single scan, rest-stress myocardial blood flow method

149 Objectives We previously published a non-stationary kinetic model for quantitative measurement of absolute myocardial blood flow (MBF) during a two-injection single scan rest/stress imaging session (1). More recently, accurate rest and stress blood flow measurements were obtained in a porcine model in less than 15 min of PET acquisition using [18F]Flurpiridaz (2). In this work, we present a solution of the non-stationary kinetic model for fast computation of parametric images of rest (K1r) and stress (K1s) MBF using a table lookup method. Methods The non-stationary rest-stress kinetic model previously developed by our group considers rest-stress imaging to be a single acquisition characterized by time-varying parameters (1). In this work, the model was solved using a two-dimensional lookup table of the rest and stress egress rate constants (k2r, k2s). For each value of k2r and k2s all voxels are simultaneously fitted with linear least squares and the solution providing the lowest residual sum of square (RSS) is retained. Simulations were performed to compare the performance of the table lookup model (LM) with the original non-linear method (NLM). Realistic noisy time activity curves (TACs) were generated at 8 different noise levels (1000 noise realizations for each noise level) and fitted with both methods. 16 Single scan rest/stress [18F]Flurpiridaz measurements were made in 12 pigs: 9 were imaged in control state and 7 after infarction of the left anterior descending artery (LAD) territory. Dynamic images were reconstructed with filtered back projection (FBP) and transformed into a three-dimensionnal pig atlas. Parametric maps of rest and stress MBF as well as maps of left (fLV) and right (fRV) ventricular spill-over fractions were generated. Regions of interest (ROIs) for 17 myocardial segments were defined in bull9s eye fashion (3) on the parametric maps. The mean of each ROI was then compared to the K1r and K1s estimates obtained from fitting the 17 regional TACs with the NLM. Results A novel model formulation was derived using a matrix representation and a two-dimensional table lookup. In simulation, the LM performed as well as the NLM in terms of precision and accuracy. The simulation did not show that bias was introduced by the use of our predefined two-dimensional lookup table (k2r,k2s). In experimental data, parametric maps demonstrated good statistical quality and the LM was computationally much more efficient than the original NLM: a set of parametric maps K1r, K1s, fLV, fRV (Figure 1) was obtained in 16 min on a conventional Macbook Pro (2.3 GHz Intel Core i5); whereas, several hours were required with the NLM. fLV and fRV maps showed higher spill-over fractions around the blood pools which is consistent with expectation and illustrates the identifiability of the model parameters at the voxel level. Excellent agreement was obtained between the mean MBF calculated on the parametric maps for each of the 17 ROIs and the regional MBF values estimated by the NLM (K1map=0.969 x K1ROI + 0.018, R2=0.994; mean difference= 0.036 ± 0.050 mL/min/cc) suggesting that reasonable MBF estimates are obtained at the voxel level. Conclusions We developed a table lookup method for fast computation of parametric imaging of rest and stress MBF. Our results show the feasibility of obtaining good quality MBF maps in a timely manner, thus demonstrating that the method can be applied in a clinical environment to obtain voxel-wise rest-stress MBF information. $$graphic_C321FD1E-9BC3-49EC-A031-D30A52791BAB$$