Characterization of regional lymph nodes in cases with hepatocellular carcinoma before surgical resection: new approach utilizing FDG PET/CT

Abstract Background Hepatocellular carcinoma (HCC) is a tumor with a high mortality rate. So, early detection and precise assessment of the disease’s stage are critical. Individuals with HCC often have cirrhosis and/or hepatitis, which are frequently associated with reactive lymphadenopathy that may mimic metastatic lymph nodes. Most studies accept lymph node short axis diameter of 1 cm or greater as a criterion of malignancy. However, a large false negative ratio of metastatic lymph nodes with normal size weakens the diagnostic sensitivity of these studies. Using post-contrast enhancement parameters from computed tomography (CT) and adding metabolic data from Positron emission tomography (PET) can help to detect malignancy in lymph nodes even if normal sized, resulting in changing the treatment plan. The aim of this study is to evaluate new indices for predicting metastatic lymph nodes in HCC patients using 18 fluoro-2-deoxy-D-glucose (18F-FDG) PET/CT. Methods An observational study of 90 patients with HCC underwent 18F-FDG PET/CT for tumor staging prior to surgery. Morphologic, contrast dynamic, and metabolic criteria for the identified lymph nodes were compared to histopathology and/or follow-up data to characterize and differentiate benign from metastatic nodes. Results We found a significant difference between non-metastatic and metastatic lymph nodes in terms of long axis diameter, short axis diameter, long/short axis ratio, non-contrast computed tomography (NCCT) Hounsfield unit (HU), contrast-enhanced computed tomography (CECT) HU in the arterial phase, nodal maximum standardized uptake value (SUVmax), and nodal SUVmax/liver SUVmax ratio ( p value < 0.0001). Metastatic nodes had the best cutoff values of > 15 mm for short axis. We combined data from CECT and PET images, including SUV ratio × diameter ratio, non-contrast HU/(diameter ratio/SUV ratio), and arterial enhancement percent/(SUV ratio × diameter ratio), and found a significant difference ( p value < 0.0001) between metastatic and non-metastatic lymph nodes. The best cutoff values for metastatic lymph nodes were > 2, > 25, and less than 29.87%, respectively. Conclusions PET/CT imaging with co-registration of different anatomical and functional imaging data enhances lymph node metastasis prediction and enables more accurate staging and management of HCC patients.