The standard approach for evaluating FDG-PET kinetic studies is based upon an assumption that tissue within a representative region of interest (ROI) is relatively homogeneous in terms of FDG kinetics. In neoplasms and other disease states, tissue within an ROI may be grossly heterogeneous, due to adjacent infarcted tissue and other causes. We have developed a method employing two ROIs (one over the tumor and another over a "reference region") to deal with this level of heterogeneity.
Methods: The method is based on the regular FDG model but consists of six variable parameters (6P model) which uses the kinetics in the reference region to account for the normal tissue within the tumor ROI, so that the kinetic data only associated with the tumor can be estimated. Monte Carlo simulations and human PET FDG studies were used to analyze the performance of the 6P model.
Results: The narrower 95% confidence intervals of parameter estimates, which centered at the true tumor rate constants, and the smaller correlation matrix of the 6P model showed the better performance of the 6P model compared to the standard "homogeneous" four-parameter FDG model. Computer simulations further showed that the 6P model can accurately estimate the microparameters (rate constants: K1* (ml/min/g), k2* (min-1), k3* (min-1), k4* (min-1)) and the macroparameter (K (ml/min/g)) of tumor cells regardless of the percent weight of tumor cells in the lesions.
Conclusions: The new method can produce more reliable and accurate estimates of tumor glucose metabolic rates with dynamic PET FDG studies.