Multi-graphical analysis of dynamic PET

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2010-02, Vol.49 (4), p.2947-2957
• Main Authors: Zhou, Yun, Ye, Weiguo, Brašić, James R., Wong, Dean F.
• Format: Article
• Language: English
• Subjects: Algorithms; Brain - diagnostic imaging; Brain - metabolism; Computer Simulation; Economic models; Equilibrium; Estimates; Gjedde–Patlak plot; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Logan plot; Metabolic Clearance Rate; Methods; Models, Biological; Noise; PET; Plasma; Positron-Emission Tomography - methods; Radiopharmaceuticals - pharmacokinetics; RE plot; Relative equilibrium; Reproducibility of Results; Sensitivity and Specificity; Studies; Tissue Distribution
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2009.11.028

In quantitative dynamic PET studies, graphical analysis methods including the Gjedde–Patlak plot, the Logan plot, and the relative equilibrium-based graphical plot (RE plot) (Zhou Y., Ye W., Brašić J.R., Crabb A.H., Hilton J., Wong D.F. 2009b. A consistent and efficient graphical analysis method to improve the quantification of reversible tracer binding in radioligand receptor dynamic PET studies. Neuroimage 44(3):661–670) are based on the theory of a compartmental model with assumptions on tissue tracer kinetics. If those assumptions are violated, then the resulting estimates may be biased. In this study, a multi-graphical analysis method was developed to characterize the non-relative equilibrium effects on the estimates of total distribution volume (DVT) from the RE plot. A novel bi-graphical analysis method using the RE plot with the Gjedde–Patlak plot (RE-GP plots) was proposed to estimate DVT for the quantification of reversible tracer kinetics that may not be at relative equilibrium states during PET study period. The RE-GP plots and the Logan plot were evaluated by 19 [11C]WIN35,428 and 10 [11C]MDL100,907 normal human dynamic PET studies with brain tissue tracer kinetics measured at both region of interest (ROI) and pixel levels. A 2-tissue compartment model (2TCM) was used to fit ROI time activity curves (TACs). By applying multi-graphical plots to the 2TCM fitted ROI TACs which were considered as the noise-free tracer kinetics, the estimates of DVT from the RE-GP plots, the Logan plot, and the 2TCM fitting were equal to each other. For the measured ROI TACs, there was no significant difference between the estimates of the DVT from the RE-GP plots and those from 2TCM fitting (p=0.77), but the estimates of the DVT from the Logan plot were significantly (p