Pulmonary lesions affect a large population globally, posing huge challenges in clinical management and public healthcare. Functional imaging-based diagnosis facilitates the classification and treatment planning for pulmonary lesions. [¹⁸F]FDG PET/CT is a valuable tool for evaluating pulmonary lesions, but it is limited by false-positive uptake in inflammatory processes. Although quantitative kinetic analysis can improve diagnostic specificity, long dynamic acquisitions pose practical challenges in clinical settings and compromise patient comfort. This study evaluated an efficient and clinically practical protocol combining a 10-min dynamic scan with two-phase static scanning to improve diagnostic accuracy.

Forty patients with pulmonary lesions confirmed by histopathology (28 malignant, 12 non-malignant) were included in the analysis. Kinetic parameters were derived from time-activity curves generated by integrating dynamic and static data points using different compartment models with image-derived input functions. Semi-quantitative parameters, including maximum standardized uptake value (SUV_max), tumor-to-blood standard uptake ratio (SUR) from the early static scan, and delayed SUV_max and delayed SUR from the delayed static scan, were also calculated and assessed. Malignant lesions showed significantly higher net influx rates (K_i) calculated from Patlak model compared with non-malignant lesions (P = 0.023). The receiver operating characteristic (ROC) curve analysis for K_i yielded an area under the curve (AUC) of 0.729. Both SUR from the standard static scan (P = 0.045, AUC = 0.702) and delayed SUR from the 2.5-h static scan (P = 0.029, AUC = 0.720) were significantly higher in malignant lesions and demonstrated significant diagnostic accuracy. Standard SUV_max, and delayed SUV_max did not show significant differences between groups.

The combined 10-min dynamic and two-phase static [¹⁸F]FDG PET/CT protocol may be feasible in selected centers with optimized scheduling. When applicable, this method allows derivation of the net influx rate K_i from Patlak graphical analysis as well as the easily calculated semi-quantitative parameters SUR and delayed SUR, all of which demonstrate significant diagnostic value for differentiating malignant from non-malignant pulmonary lesions, outperforming conventional SUV_max.