ArticleTheranostics2015
Kinetic analysis of dynamic (11)C-acetate PET/CT imaging as a potential method for differentiation of hepatocellular carcinoma and benign liver lesions.
Article in Theranostics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Qualitative and quantitative differentiation efficiency of dual-tracer PET/CT with 18F-fluorodeoxyglucose andAbdominal radiology (New York) · 2025Pooled it
- Monitoring Response to Transarterial Chemoembolization in Hepatocellular Carcinoma UsingJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2020Trial
- Comparison among Reconstruction Algorithms for Quantitative Analysis ofContrast media & molecular imaging · 2018Trial
- Dual-phase multiobjective Bayesian optimization method for estimating hepatocellular carcinoma dynamics parameters from PET/CT scans.Quantitative imaging in medicine and surgery · 2025Article
- A prior information-based multi-population multi-objective optimization for estimatingBMC medical imaging · 2025Article
- Dual-tracer PET/CT in the management of hepatocellular carcinoma.JHEP reports : innovation in hepatology · 2024Article
- Advances in PET imaging for meningioma patients.Neuro-oncology advances · 2023Article
- Characterization of myocardial oxidative metabolism and myocardial external efficiency in high-risk alcohol cardiotoxicity and alcoholic cardiomyopathy via dynamicJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022Article
- DynamicBMC medical imaging · 2021Article
- A methodological investigation of healthy tissue, hepatocellular carcinoma, and other lesions with dynamicEJNMMI physics · 2021Article
- Advances in PET Diagnostics for Guiding Targeted Cancer Therapy and Studying In Vivo Cancer Biology.Current pathobiology reports · 2019Article
- Determination of a pharmacokinetic model for [EJNMMI research · 2019Article
- Article
- Imaging Cancer Metabolism: Underlying Biology and Emerging Strategies.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2018Review
- Metformin Promotes 2-Deoxy-2-[Molecular imaging and biology · 2018Article
- PET imaging in patients with meningioma-report of the RANO/PET Group.Neuro-oncology · 2017Review
- [Research and application ofSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2017Review
- Application of Different Imaging Methods in the Early Diagnosis of Primary Hepatic Carcinoma.Gastroenterology research and practice · 2016Review
- Diagnostic and therapeutic management of hepatocellular carcinoma.World journal of gastroenterology · 2015Review
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8 authors.
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Abstract
objectiveThe kinetic analysis of (11)C-acetate PET provides more information than routine one time-point static imaging. This study aims to investigate the potential of dynamic (11)C-acetate hepatic PET imaging to improve the diagnosis of hepatocellular carcinoma (HCC) and benign liver lesions by using compartmental kinetic modeling and discriminant analysis.
methodsTwenty-two patients were enrolled in this study, 6 cases were with well-differentiated HCCs, 7 with poorly-differentiated HCCs and 9 with benign pathologies. Following the CT scan, all patients underwent (11)C-acetate dynamic PET imaging. A three-compartment irreversible dual-input model was applied to the lesion time activity curves (TACs) to estimate the kinetic rate constants K1-k3, vascular fraction (VB) and the coefficient α representing the relative hepatic artery (HA) contribution to the hepatic blood supply on lesions and non-lesion liver tissue. The parameter Ki (=K1×k3/(k2 + k3)) was calculated to evaluate the local hepatic metabolic rate of acetate (LHMAct). The lesions were further classified by discriminant analysis with all the above parameters.
resultsK1 and lesion to non-lesion standardized uptake value (SUV) ratio (T/L) were found to be the parameters best characterizing the differences among well-differentiated HCC, poorly-differentiated HCC and benign lesions in stepwise discriminant analysis. With discriminant functions consisting of these two parameters, the accuracy of lesion prediction was 87.5% for well-differentiated HCC, 50% for poorly-differentiated HCC and 66.7% for benign lesions. The classification was much better than that with SUV and T/L, where the corresponding classification accuracy of the three kinds of lesions was 57.1%, 33.3% and 44.4%.
conclusion(11)C-acetate kinetic parameter K1 could improve the identification of HCC from benign lesions in combination with T/L in discriminant analysis. The discriminant analysis using static and kinetic parameters appears to be a very helpful method for clinical liver masses diagnosis and staging.
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