Dynamic chaotic gravitational search algorithm-based kinetic parameter estimation of hepatocellular carcinoma on 18F-FDG PET/CT

Abstract

Abstract Background Kinetic parameters estimated with dynamic 18F-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 1 ~ k 4 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 1, k 4 and the HPI of NLLS; k 1, k 3, k 4 and the HPI of GSA; and k 1, k 2, k 3, k 4 and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k 3 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.

Keywords

• Kinetic models
• PET/CT
• Hepatocellular carcinoma
• Gravitational search algorithm