title: Multi-graphical analysis of dynamic PET.
abstract: 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., Brasić 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 (DV(T)) 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 DV(T) 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 [(11)C]WIN35,428 and 10 [(11)C]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 DV(T) 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 DV(T) from the RE-GP plots and those from 2TCM fitting (p=0.77), but the estimates of the DV(T) from the Logan plot were significantly (p<0.001) lower, 2.3% on average, than those from 2TCM fitting. There was a highly linear correlation between the ROI DV(T) from the parametric images (Y) and those from the ROI kinetics (X) by using the RE-GP plots (Y=1.01X+0.23, R(2)=0.99). For the Logan plot, the ROI estimates from the parametric images were 13% to 83% lower than those from ROI kinetics. The computational time for generating parametric images was reduced by 69% on average by the RE-GP plots in contrast to the Logan plot. In conclusion, the bi-graphical analysis method using the RE-GP plots was a reliable, robust and computationally efficient kinetic modeling approach to improve the quantification of dynamic PET.
authors.affiliation: The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287-0807, USA. yunzhou@jhmi.edu
authors.forename: Yun
authors.initials: Y
authors.lastname: Zhou
authors.forename: Weiguo
authors.initials: W
authors.lastname: Ye
authors.forename: James R
authors.initials: JR
authors.lastname: Brasić
authors.forename: Dean F
authors.initials: DF
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism*; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014018:Tissue Distribution
chemical_list: D019275:Radiopharmaceuticals