Generalized whole-body Patlak parametric imaging for enhanced quantification in clinical PET

摘要: We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis domain routine clinical whole-body (WB) imaging. The standard (sPatlak) linear graphical assumes irreversible tracer uptake, ignoring effect FDG dephosphorylation, which has been suggested by number studies. In this work: (i) non-linear generalized (gPatlak) model is utilized, including net efflux rate constant kloss, and (ii) hybrid (s/g)Patlak (hPatlak) imaging technique introduced enhance contrast noise ratios (CNRs) uptake Ki images. Representative set kinetic parameter values XCAT phantom were employed generate realistic 4D simulation data, proposed methods additionally evaluated on 11 WB patient Quantitative simulated images over 2 groups regions-of-interest (ROIs), with low (ROI A) or high B) true kloss relative Ki, superior accuracy for gPatlak. Bias sPatlak was found be 16-18% 20-40% poorer than gPatlak ROIs A B, respectively. By contrast, exhibited, average, 10% higher sPatlak. Meanwhile, bias levels hPatlak always ranged between other two methods. general, seen outperform all in terms target-to-background ratio (TBR) CNR ROIs. Validation datasets demonstrated feasibility methods, while TBR evaluations confirmed our findings, presence non-negligible reversibility data. As such, we recommend highly tasks, while, tasks emphasizing lesion detectability (e.g. TBR, CNR) quantification, noise, instead preferred. Finally, systematically compared SUV values.