Usefulness of Imaging and Biological Tools for the Characterization of Portal Vein Thrombosis in Hepatocellular Carcinoma

This study aims to evaluate the performance of contrast-enhanced ultrasound (CEUS) and biological tests to characterize portal vein thrombosis (PVT). We retrospectively analyzed 101 patients with PVT, liver cirrhosis, and hepatocellular carcinoma (HCC). In all patients, demographic, biologic, imaging, and endoscopic data were collected. All patients underwent CEUS and a second line imaging technique (CE-CT/MRI) to characterize PVT. Of the 101 cirrhotic subjects, 77 (76.2%) had HCC. CEUS had 98.6% sensitivity (Se) and 89.3% specificity (Sp) for the characterization of PVT type. A significant correlation was found between alpha-fetoprotein (AFP) levels and the PVT characterization at CEUS (r = 0.28, p = 0.0098) and CT/MRI (r = 0.3, p = 0.0057). Using the AFP rule-out cutoff values for HCC (AFP < 20 ng/dL), 78% of the subjects were correctly classified as having benign PVT, while 100% of the subjects were correctly classified as tumor-in-vein (TIV) when the rule-in cutoff value was used (AFP ≥ 200 ng/dL). Using multiple regression analysis, we obtained a score for classifying PVT. The PVT score performed better than CEUS (AUC—0.99 vs. AUC—0.93, p = 0.025) or AFP serum levels (AUC—0.99 vs. AUC—0.96, p = 0.047) for characterizing PVT. In conclusion, CEUS is a sensitive method for the characterization of PVT. The PVT score had the highest performance for PVT characterization

A Statistical Approach to the Diagnosis and Prediction of HCC Using CK19 and Glypican 3 Biomarkers

Various statistical models predict the probability of developing hepatocellular carcinoma (HCC) in patients with cirrhosis, with GALAD being one of the most extensively studied scores. Biomarkers like alpha-fetoprotein (AFP), AFP-L3, and des-g-carboxyprothrombin (DCP) are widely used alone or in conjunction with ultrasound to screen for HCC. Our study aimed to compare the effectiveness of Cytokeratin 19 (CK19) and Glypican-3 (GPC3) as standalone biomarkers and in a statistical model to predict the likelihood of HCC. We conducted a monocentric prospective study involving 154 participants with previously diagnosed liver cirrhosis, divided into two groups: 95 patients with confirmed HCC based on clinical, biological, and imaging features and 59 patients without HCC. We measured the levels of AFP, AFP-L3, DCP, GPC3, and CK19 in both groups. We used univariate and multivariate statistical analyses to evaluate the ability of GPC3 and CK19 to predict the presence of HCC and incorporated them into a statistical model—the GALKA score—which was then compared to the GALAD score. AFP performed better than AFP-F3, DCP, GPC3, and CK19 in predicting the presence of HCC in our cohort. Additionally, GPC3 outperformed CK19. We used multivariate analysis to compute the GALKA score to predict the presence of HCC. Using these predictors, the following score was formulated: 0.005*AFP-L3 + 0.00069*AFP + 0.000066*GPC3 + 0.01*CK19 + 0.235*Serum Albumin—0.277. The optimal cutoff was >0.32 (AUROC = 0.98, sensitivity: 96.8%, specificity: 93%, positive predictive value—95.8%, negative predictive value—94.8%). The GALKA score had a similar predictive value to the GALAD score for the presence of HCC. In conclusion, AFP, AFP-L3, and DCP were the best biomarkers for predicting the likelihood of HCC. Our score performed well overall and was comparable to the GALAD score