Optimization of the k(2)' Parameter Estimation for the Pharmacokinetic Modeling of Dynamic PIB PET Scans Using SRTM2

Background: This study explores different approaches to estimate the clearance rate of the reference tissue (k2 ') parameter used for pharmacokinetic modeling, using the simplified reference tissue model 2 (SRMT2) and further explores the effect on the binding potential (BPND) of C-11-labeled Pittsburgh Compound B (PIB) PET scans. Methods: Thirty subjects underwent a dynamic PIB PET scan and were classified as PIB positive (+) or negative (-). Thirteen regions were defined from where to estimate k2 ': the whole brain, eight anatomical region based on the Hammer's atlas, one region based on a SPM comparison between groups on a voxel level, and three regions using different BPNDSRTM thresholds. Results: The different approaches resulted in distinct k2 ' estimations per subject. The median value of the estimated k2 ' across all subjects in the whole brain was 0.057. In general, PIB+ subjects presented smaller k2 ' estimates than this median, and PIB-, larger. Furthermore, only threshold and white matter methods resulted in non-significant differences between groups. Moreover, threshold approaches yielded the best correlation between BPNDSRTM and BPNDSRTM2 for both groups (R-2 = 0.85 for PIB+, and R-2 = 0.88 for PIB-). Lastly, a sensitivity analysis showed that overestimating k2 ' values resulted in less biased BPNDSRTM2 estimates. Conclusion: Setting a threshold on BPNDSRTM might be the best method to estimate k2 ' in voxel-based modeling approaches, while the use of a white matter region might be a better option for a volume of interest based analysis.