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 k1 ~ k4 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 k1, k4 and the HPI of NLLS; k1, k3, k4 and the HPI of GSA; and k1, k2, k3, k4 and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k3 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.