动态（11）C-乙酸盐PET/CT成像的动力学分析作为鉴别肝细胞癌和肝脏良性病变的潜在方法

Kinetic analysis of dynamic (11)C-acetate PET/CT imaging as a potential method for differentiation of hepatocellular carcinoma and benign liver lesions.

作者信息

Huo Li, Guo Jinxia, Dang Yonghong, Lv Jinqiao, Zheng Youjing, Li Fang, Xie Qingguo, Chen Xiaoyuan

机构信息

1. Department of Nuclear Medicine, Peking Union Medical College Hospital.

2. Laboratory of Molecular Imaging and Nanomedicine (LOMIN), National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (NIBIB), Bethesda, Maryland, USA ; 3. Department of Biomedical Engineering, and Wuhan National Laboratory for Optoelectronics(WNLO), Huazhong University of Science and Technology, Wuhan, Hubei, China.

出版信息

Theranostics. 2015 Jan 21;5(4):371-7. doi: 10.7150/thno.10760. eCollection 2015.

DOI:10.7150/thno.10760

PMID:25699097

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4329501/

Abstract

OBJECTIVE

The 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.

METHODS

Twenty-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.

RESULTS

K1 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.

摘要

目的

与常规的一次性静态成像相比，¹¹C-乙酸盐PET的动力学分析能提供更多信息。本研究旨在通过使用房室动力学建模和判别分析，探讨动态¹¹C-乙酸盐肝脏PET成像在改善肝细胞癌（HCC）和肝脏良性病变诊断方面的潜力。

方法

本研究纳入了22例患者，其中6例为高分化HCC，7例为低分化HCC，9例为良性病变。在CT扫描后，所有患者均接受了¹¹C-乙酸盐动态PET成像。将三室不可逆双输入模型应用于病变时间-活性曲线（TAC），以估计动力学速率常数K1 - k3、血管分数（VB）以及代表肝动脉（HA）对病变和非病变肝组织肝血供相对贡献的系数α。计算参数Ki（=K1×k3/(k2 + k3)）以评估局部肝脏乙酸代谢率（LHMAct）。使用上述所有参数通过判别分析对病变进行进一步分类。

结果

在逐步判别分析中，发现K1和病变与非病变标准化摄取值（SUV）比值（T/L）是最能表征高分化HCC、低分化HCC和良性病变之间差异的参数。利用由这两个参数组成的判别函数，高分化HCC的病变预测准确率为87.5%，低分化HCC为50%，良性病变为66.7%。该分类比使用SUV和T/L时要好得多，三种病变对应的分类准确率分别为57.1%、33.3%和44.4%。