Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function

Abstract

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET is less promising. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. This paper aims to identify the optimal dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen patients with nonalcoholic fatty liver disease were included. Each patient underwent 1-hour dynamic FDG- PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: the traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), a model with population-based dual-blood input function (DBIF), and a new model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation score. Results showed that the optimization-derived DBIF model improved liver time activity curve fitting and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for dynamic liver FDG-PET kinetic analysis in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population- based DBIF for dynamic FDG-PET of liver inflammation.

In vivo confirmation of altered hepatic glucose metabolism in patients with liver fibrosis/cirrhosis by 18F-FDG PET/CT

“…Therefore, the modeling of the 18 F-FDG kinetics usually contains three rate constants k1, k2, and k3, whereas hepatocytes contain glucose-6-phosphatase capable of dephosphorylating 18 FDG-6-phosphate resulting in reversible kinetics with non-negligible k4 [ 23 ]. Kinetics of 18 F-FDG in liver parenchyma is mainly determined by k1 and k2, with a minor impact of k3 and k4 in short-term studies lasting about 60 to 90 min post-FDG injection [ 31 , 64 ]. In line with the glucose kinetics, SUV Liver in normal liver parenchyma varies little between 60 and 120 min post-injection [ 65 , 66 ], while the blood activity slowly decreases with time in a hyperbolic manner, i.e., proportional to 1/T^0.313) [ 20 ].…”

“…For assessing liver inflammation in non-alcoholic steatohepatitis (NASH), a recent study showed that the dynamic 18 F-FDG-PET with kinetic modeling has the potential to assess liver inflammation in patients with NASH, while hepatic glucose metabolism assessed by means of SUV-analyzes gave no promising results [ 31 ].…”

Dynamic 18F-FDG PET imaging of liver lesions: evaluation of a two-tissue compartment model with dual blood input function

“…Since the hepatic tissue has blood supply from both the PV and the HA, a dual-blood input function (DBIF) that takes into consideration the tracer concentration in both vessels is believed to produce more reasonable results [ 10 , 11 ]. The arterial input function can either be directly obtained by arterial blood sampling [ 5 ] or be derived from the left ventricle or aortic regions in dynamic PET images [ 12 – 14 ].Whereas the portal vein input function was usually estimated by using the convolution models of arterial input function with population-based parameters, or with individuation-based parameters determined together with kinetic modeling [ 10 , 15 – 17 ]…”

PET Parametric Imaging: Past, Present, and Future

“…The hallmark of NASH is liver inflammation (lobular inflammation plus ballooning degeneration) in the setting of hepatic steatosis. Recent studies have demonstrated the potential of using the widely accessible radiotracer 18 F-FDG via dynamic PET imaging coupled with tracer kinetic modeling [80], [81]. While SUV or K i of 18 F-FDG did not show promise, the blood-to-tissue transport rate FDG K 1 of the liver demonstrated a strong correlation with histopathological liver inflammation grades [81].…”

“…In combination with the ability of CT for evaluating hepatic steatosis, a liver parametric PET/CT method may have the potential to provide a valuable clinical imaging tool for differentiating NASH from simple fatty liver. One interesting technical aspect of PET liver parametric imaging is that the liver receives dual blood supplies from the hepatic artery and the portal vein [75], which should be taken into account in tracer kinetic modeling [75], [80].…”