Quantitative hepatitis B surface antigen in predicting recurrence of hepatitis B-related hepatocellular carcinoma after liver transplantation

Aim: Recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) for chronic hepatitis B (CHB) can be associated with reappearance of hepatitis B surface antigen (HBsAg). The current study determined the significance of HBsAg qualitatively and quantitatively using a highly sensitive assay in recurrent HCC after transplantation.Methods: Consecutive patients with HBV-related HCC with LT were included. Oral nucleos(t)ide analogues without hepatitis B immune globulin were used as hepatitis B virus (HBV) prophylaxis. Quantitative HBsAg levels were performed at time of transplant, at 1 month, 3 and 6 months post transplant using a highly sensitive (hs)-HBsAg assay.Results: One hundred and fourteen patients were included, with a median follow-up of 80 months, with 24 cases of HCC recurrence, and a cumulative rate of 20.7% at 5 years. There was significant correlation between time of tumor recurrence and time of HBsAg reappearance (r = 0.551, P = 0.027). Early HCC recurrence was associated with higher median level of hs-HBsAg at the time of transplant (72.85 vs. 69.70 IU/mL, P = 0.018). Using a hs-HBsAg cut-off level of 0.0005 IU/mL, patients with levels above this threshold at 3 and 6 months were associated with higher rate of early HCC recurrence (28.6% vs. 3.0% and 26.9% vs. 2.9% respectively, both P = 0.0006). There was no significant difference in HCC recurrence between positive and negative HBsAg using the conventional qualitative HBsAg assay.Conclusion: Serum hs-HBsAg levels of ≥ 0.0005 IU/mL at 3 to 6 months after LT is associated with higher rates of early HCC recurrence, and may be useful as an early tumor marker

Primary Tumor Radiomic Model for Identifying Extrahepatic Metastasis of Hepatocellular Carcinoma Based on Contrast Enhanced Computed Tomography

This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic (CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software