Evaluation of compartment models to quantify plasma parent fraction data in PET studies.

501 Objectives: Metabolite analysis during PET studies is usually performed for a few selected blood samples only, and these samples’ parent fraction data are then fitted by an empirical function to provide a continuous function of time. These empirical functions are usually selected only for their ability to smooth and interpolate the parent fraction data. Alternatively, compartmental models, using the total plasma radioactivity curve as input, have been proposed to analyze parent fraction data for F-DOPA [1] and raclopride [2]. Possible advantages of these compartment models are that they would be independent of the type of injection protocol (e.g., bolus vs. infusion), and might provide a basis for developing population metabolite corrections. However, these compartment models have not been evaluated for a large range of tracers. The goal of the study was to evaluate the suitability of these compartment models for 11 tracers (18F-AS2471907, 11C-LY3172176, 11C-TASP0410699, 11C-EKAP, 11C-FEKAP, 11C-UCB-J, 11C-Flumazenil, 18F-NCFHEB, 18F-PF-05270430, 18F-FPEB and 18F-FPDTBZ). Methods: For each tracer, data from 5 scans following a bolus injection were used. First, to verify that compartment models can describe the relationship between the metabolite-corrected arterial input function (MC-AIF) and the total plasma time-activity curve (pTAC), the pTACs were fitted with various compartment models (CM-TP) using the MC-AIF (using the best empirical function) as input. CM-TP models incorporating 2 to 11 compartments were tested. The optimal number of compartment was evaluated using the F-test. Then, compartment models for metabolite correction (CM-MC) were evaluated. These models were based on a generalization of the model proposed in [2]: the metabolite concentration in plasma (MiP) were modeled using the pTAC convoluted by a sum of exponentials, and then the parent fraction was computed as 1-MiP/pTAC. These models used 2 to 6 compartments, and 2 to 9 parameters. For comparison, 2 conventional empirical functions (EF) were used: 1) a sum of exponentials (SE; using 2 to 6 parameters) and 2) a sigmoid function (SF; using 1 to 5 parameters) based on the gamma function. For the empirical functions, the number of parameters was automatically selected by minimizing the residual sum of squares. These models were compared using the mean absolute percent residuals from the fits of the parent fraction data, and visual grading of the quality of fit and of the interpolation between sample points. Finally, the volumes of distribution VT were quantified with MA1 using each CM-MC, and then compared to the VT values computed using the best empirical function. Results: For all tracers, the best empirical function was the SF, using ~ 4 parameters (for 18F-AS2471907) to 5 parameters (for 18F-FPEB, 11C-EKAP and 18F-PF-05270430) (See Table 1 for details). For all tracers, the CM-TP models adequately fitted the pTAC, using 2 (for 18F-FPDTBZ and 18F-NCFHEB) to 8 (for 11C-FEKAP) compartments (median values across scans). With CM-MC models, good fits and interpolation were obtained for 18F-AS2471907, 11C-LY3172176, 11C-TASP0410699, 11C-EKAP, 11C-FEKAP, 18F-NCFHEB, 18F-FPEB and 18F-FPDTBZ, but not for 11C-UCB-J, 11C-Flumazenil and to a lower extent 18F-PF-05270430. Errors on VT were < 3% on average for all tracers with good CM-MC fits. Conclusions: For 8 out of 11 tracers, CM-MC models could be successfully developed. In the other cases, the parent fraction data could not be fit with the corresponding models, perhaps due noise in the total plasma curve, requiring a more robust fitting approach, such as a Bayesian method. For tracers for which CM-MC is applicable, further investigations are needed to assess the utility of MC-CM for improved test-retest variability and to produce population metabolite corrections. References: [1] Huang et al., 1991; [2] Carson et al., J Cereb Blood Flow Metab, 1997 [asterisk]Scoring scale: 1 (good) to 3 (unacceptable); #Selected using a procedure based on the F-test