基于动态混沌引力搜索算法的 F-FDG PET/CT 肝癌动力学参数估计
Dynamic chaotic gravitational search algorithm-based kinetic parameter estimation of hepatocellular carcinoma on F-FDG PET/CT.
机构信息
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Yunnan Key Laboratory of Artificial Intelligence, Kunming, 650500, Yunnan, China.
PET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China.
出版信息
BMC Med Imaging. 2022 Feb 6;22(1):20. doi: 10.1186/s12880-022-00742-4.
BACKGROUND
Kinetic parameters estimated with dynamic F-FDG PET/CT can help to characterize hepatocellular carcinoma (HCC). We aim to evaluate the feasibility of the gravitational search algorithm (GSA) for kinetic parameter estimation and to propose a dynamic chaotic gravitational search algorithm (DCGSA) to enhance parameter estimation.
METHODS
Five-minute dynamic PET/CT data of 20 HCCs were prospectively enrolled, and the kinetic parameters k ~ k and the hepatic arterial perfusion index (HPI) were estimated with a dual-input three-compartment model based on nonlinear least squares (NLLS), GSA and DCGSA.
RESULTS
The results showed that there were significant differences between the HCCs and background liver tissues for k, k and the HPI of NLLS; k, k, k and the HPI of GSA; and k, k, k, k and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k than NLLS and GSA.
CONCLUSIONS
GSA enables accurate estimation of the kinetic parameters of dynamic PET/CT in the diagnosis of HCC, and DCGSA can enhance the diagnostic performance.
背景
利用动态 F-FDG PET/CT 估算的动力学参数有助于对肝细胞癌（HCC）进行特征描述。本研究旨在评估引力搜索算法（GSA）进行动力学参数估计的可行性，并提出一种动态混沌引力搜索算法（DCGSA）以增强参数估计。
方法
前瞻性纳入 20 例 HCC 患者的 5 分钟动态 PET/CT 数据，使用双输入三房室模型基于非线性最小二乘法（NLLS）、GSA 和 DCGSA 估算动力学参数 k~k 和肝动脉灌注指数（HPI）。
结果
结果显示，与背景肝组织相比，NLLS 的 k、k 和 HPI，GSA 的 k、k、k 和 HPI，以及 DCGSA 的 k、k、k、k 和 HPI 之间存在显著差异。与 NLLS 和 GSA 相比，DCGSA 对 k 的诊断性能更高。
结论
GSA 可准确估计动态 PET/CT 的动力学参数，有助于 HCC 的诊断，而 DCGSA 则可增强诊断性能。
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