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

BMC Med Imaging. 2022 Feb 6;22(1):20. doi: 10.1186/s12880-022-00742-4.

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.

Keywords: Gravitational search algorithm; Hepatocellular carcinoma; Kinetic models; PET/CT.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Carcinoma, Hepatocellular / diagnostic imaging*
  • Female
  • Fluorodeoxyglucose F18
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Liver Neoplasms / diagnostic imaging*
  • Male
  • Positron Emission Tomography Computed Tomography / methods*
  • Radiopharmaceuticals

Substances

  • Radiopharmaceuticals
  • Fluorodeoxyglucose F18