(18)F-Deoxyglucose (FDG) kinetics evaluated by a non-compartment model based on a linear regression function using a computer based simulation: correlation with the parameters of the two-tissue compartment model.

Parametric imaging with a linear regression function of the tracer activity curve fit is a non-compartmental method, which can be used for the evaluation of dynamic PET (dPET) studies. However, the dependency of the slope of the regression function fit on the (18)F-Deoxyglucose (FDG) 2-tissue compartment parameters (vb, k1-k4) is not known yet. This study is focused on the impact of the 2-tissue compartment parameters on the slope of the curve. A data base of 1760 dynamic PET FDG studies with the corresponding 2-tissue compartment model parameter solutions were available and used to calculate synthetic time-activity data based on the 2-tissue compartment model. The input curve was calculated from the median values of the input curves of the 1760 dynamic data sets. Then, sequentially each of the five parameters (vb, k1-k4) of the 2-tissue compartment model was varied from 0.1 to 0.9 and tracer activity curves were calculated (60000 curves/parameter). A linear regression function was fitted to these curves. The comparison of the slope values of the regression function with the corresponding compartment data revealed a primary dependency on k3, which is associated with the intracellular phosphorylation of FDG. The squared correlation coefficient was high with r(2)=0.9716, which refers to 97 % explained variance of the data. k2 and vb had only a minor impact, while k1 and k4 had no impact on the slope values. The results demonstrate, that k3 has a major impact on the slope values calculated by the linear regression function.