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

Insights into Imaging

Original Article

Dongdong Xv¹  Pengfei Li¹  Qiao Luo¹  Yinglei Deng¹  Siyu Wang¹  Shaobo Wang²  Boqiao Li³  Tao Wang³  Jianfeng He³  Hong Shi⁴ 

[1] PET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People’s Hospital of Yunnan, 650031, Kunming, China;PET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People’s Hospital of Yunnan, 650031, Kunming, China;Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China;Yunnan Key Laboratory of Artificial Intelligence, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China;Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China;

关键词: Hepatocellular carcinomas;    Positron-emission tomography;    Compartmental model;   

DOI  :  10.1186/s13244-023-01442-5

 received in 2022-12-28, accepted in 2023-04-24,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundKinetic 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.MethodsThis 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.ResultsThere is a strong correlation between the kinetic parameters K1 ~ k3, HPI and Vb\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${{\varvec{V}}}_{{\varvec{b}}}$$\end{document} 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 Vb\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${{\varvec{V}}}_{{\varvec{b}}}$$\end{document} 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 Vb\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${{\varvec{V}}}_{{\varvec{b}}}$$\end{document} values than background liver tissues; however, the k4 value was not significantly different between HCCs and the background liver tissues.ConclusionsShort-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 statementShort-term PET could be used for hepatic kinetic parameter estimation. The combined model could improve the estimation of liver kinetic parameters.Graphical Abstract

【 授权许可】

CC BY   
© The Author(s) 2023

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