Objective: The objectives of the study were to develop a population pharmacokinetic model for (11)C-flumazenil at tracer concentrations, to assess the effects of patient-related covariates and to derive an optimal sampling protocol for clinical use.
Methods: A population pharmacokinetic model was developed using nonlinear mixed effects modelling (NONMEM) with data obtained from 51 patients with either depression or epilepsy. Each patient received approximately 370 MBq (1-4 microg) of (11)C-flumazenil. The effects of selected covariates (gender, weight, type of disease and age) were investigated. The model was validated using a bootstrap method. Finally, an optimal sampling design was established.
Results: The population pharmacokinetics of tracer quantities of (11)C-flumazenil were best described by a two compartment model. Type of disease and weight were identified as significant covariates (P < 0.002). Mean population pharmacokinetic parameters (percent coefficient of variation) were: CL 1530 mL min(-1) (6.6%), V(1) 24.8 x 10(3) mL (3.8%), V(2) 27.3 x 10(3) mL (5.4%), and Q 2510 mL min(-1) (6.5%). CL was 20% lower in patients with epilepsy, and the influence of weight on V(1) was 0.55% kg(-1). For the prediction of the AUC, a combination of two time points at t = 30 and 60 min post injection was considered optimal (bias -0.7% (95% CI -2.2 to 0.8%), precision 5.7% (95% CI 4.5-6.9%)). The optimal sampling strategy was cross-validated (observed AUC = 296 MBql(-1) min(-1) (95% CI 102-490), predicted AUC = 288 MBql(-1) min(-1) (95% CI 70-506)).
Conclusions: The population pharmacokinetics of tracer quantities of (11)C-flumazenil are well described by a two-compartment model. Inclusion of weight and type of disease as covariates significantly improved the model. Furthermore, an optimal sampling procedure may increase the feasibility and applicability of (11)C-flumazenil PET.