Noninvasive quantification of nonhuman primate dynamic F-FDG PET imaging.

F-FDG uptake rate constant K is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate K . The PIF is the F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the K estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the K estimates from pPIF with optimal sampling schemes and those from mPIF were: K (pPIF 1 sample at 40 min) = 1.015 K (mPIF) - 0.000, R  = 0.974; K (pPIF 2 samples at 35 and 50 min) = 1.052 K (mPIF) - 0.001, R  = 0.976; K (pPIF 3 samples at 12, 40, and 50 min) = 1.030 K (mPIF) - 0.000, R  = 0.985; and K (pPIF 4 samples at 10, 20, 40, and 50 min) = 1.016 K (mPIF)- 0.000, R  = 0.993. As the sample size became greater or equal to 4, the K estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic F-FDG PET imaging and is potentially extendable to further translational human studies.