Relative Equilibrium Plot Improves Graphical Analysis and Allows Bias Correction of Standardized Uptake Value Ratio in Quantitative 11C-PiB PET Studies

Abstract

Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVRs) in ligand-receptor dynamic PET studies. The objective of this study was to use a recently developed relative equilibrium-based graphical (RE) plot method to improve and simplify the 2 commonly used methods for quantification of (11)C-Pittsburgh compound B ((11)C-PiB) PET. The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight (11)C-PiB dynamic PET scans (66 from controls and 12 from participants with mild cognitive impaired [MCI] from the Baltimore Longitudinal Study of Aging) were acquired over 90 min. Regions of interest (ROIs) were defined on coregistered MR images. Both the ROI and the pixelwise time-activity curves were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI time-activity curves were used as a reference for comparison of DVR estimates. Results from the theoretic analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI time-activity curves. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, and cingulate regions and the striatum were underestimated by the Logan plot (controls, 4%-12%; MCI, 9%-16%) and overestimated by the SUVR (controls, 8%-16%; MCI, 16%-24%). This bias was higher in the MCI group than in controls (P < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR. The RE plot improves pixelwise quantification of (11)C-PiB dynamic PET, compared with the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates than of SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of (11)C-PiB studies.