Short-term PET-derived kinetic estimation for the diagnosis of hepatocellular carcinoma: a combination of the maximum-slope method and dual-input three-compartment model

Abstract

Background: Kinetic estimation provides fitted parameters related to blood flow perfusion and fluorine-18-fluorodeoxyglucose (18F-FDG) transport and intracellular metabolism to characterize hepatocellular carcinoma (HCC) but usually requires 60 min or more for dynamic PET, which is time-consuming and impractical in a busy clinical setting and has poor patient tolerance. Methods: This study preliminarily evaluated the equivalence of liver kinetic estimation between short-term (5-min dynamic data supplemented with 1-min static data at 60 min postinjection) and fully 60-min dynamic protocols and whether short-term 18F-FDG PET-derived kinetic parameters using a three-compartment model can be used to discriminate HCC from the background liver tissue. Then, we proposed a combined model, a combination of the maximum-slope method and a three-compartment model, to improve kinetic estimation. Results: There is a strong correlation between the kinetic parameters K 1 ~ k 3, HPI and Vb in the short-term and fully dynamic protocols. With the three-compartment model, HCCs were found to have higher k 2, HPI and k 3 values than background liver tissues, while K 1, k 4 and Vb values were not significantly different between HCCs and background liver tissues. With the combined model, HCCs were found to have higher HPI, K 1 and k 2, k 3 and Vb values than background liver tissues; however, the k4 value was not significantly different between HCCs and the background liver tissues. Conclusions: Short-term PET is closely equivalent to fully dynamic PET for liver kinetic estimation. Short-term PET-derived kinetic parameters can be used to distinguish HCC from background liver tissue, and the combined model improves the kinetic estimation. Clinical relevance statement: Short-term PET could be used for hepatic kinetic parameter estimation. The combined model could improve the estimation of liver kinetic parameters. Graphical Abstract: [Figure not available: see fulltext.]