Improving Quantification of Cardiac Glucose Metabolism by 18F-FDG PET Using the Iterative Two-stage Algorithm

Background: The metabolism of [18F]-FDG, an analogue of glucose molecule, is often evaluated by kinetic analysis. Methods: In this study, we compare the performance of the Iterative Two-stage (ITS) algorithm against the standard Weighted Nonlinear Least Squares (WNLS) and the Patlak analysis for PET imaging quantification in control and diseased rats. A full kinetic modelling and graphical analyses were performed on [18F]-FDG PET data (7 controls and 7 Myocardial Infarct (MI) rats). The evaluation of the identifiability of parameters and the goodness of the fit in nonlinear regression wereconducted by statistic measures i.e. the Coefficient of Variation (COV), Akaike Information Criterion (AIC) and the Model Selection Criterion (MSC). Bland-Altman analysis was used to assess the reproducibility of the net influx rate (Ki) constants in the mid-inferoseptal region. The Patlak Ki outcome values were compared to ITS Ki by calculating the percentage changes between their outcomes estimated values. Results: The WNLS and ITS show an excellent identifiability of the parameters (resp. 5.15≤COV≤8.92; 4.12≤COV≤ 10.20) and showed a good reproducibility of the Ki constants in controls. In contrast, in the MI group, WNLS revealed a poor identifiability in the mid-inferoseptal region (17.62≤COV≤38.15) whereas ITS revealed a good identifiability (10.84 ≤COV≤23.54). The Bland Altman analysis showed a large bias in the estimation of the Ki constants in the region of interest e.g. mid-inferoseptal, 0.053 ± 0.017 mL/ min/mL. The Patlak Ki values were underestimated by 6.8% and 7.4% compared to ITS Ki in controls and MI respectively.