Abstract
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 K1 ~ k3, HPI and $${{\varvec{V}}}_{{\varvec{b}}}$$
V
b
in the short-term and fully dynamic protocols. With the three-compartment model, HCCs were found to have higher k2, HPI and k3 values than background liver tissues, while K1, k4 and $${{\varvec{V}}}_{{\varvec{b}}}$$
V
b
values were not significantly different between HCCs and background liver tissues. With the combined model, HCCs were found to have higher HPI, K1 and k2, k3 and $${{\varvec{V}}}_{{\varvec{b}}}$$
V
b
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
Funder
the National Natural Science Foundation of China
Yunnan Key Laboratory of Smart City in Cyberspace Security
the Basic Research on Application of Joint Special Funding of Science and Technology Department of Yunnan Province-Kunming Medical University
the High-level Talent Project of Health in Yunnan Province,
the Ten Thousand People Plan in Yunnan Province
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging
Cited by
1 articles.
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