Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA

Evaluation of aspartate aminotransferase to platelet ratio index and fibrosis 4 scores for hepatic fibrosis assessment compared with transient elastography in chronic hepatitis C patients

Background and Aim: Fibrotic stage (FS) assessment is essential in chronic hepatitis C treatment cascade. Liver stiffness measurement (LSM) using transient elastography (TE) is reliable and correlated with liver biopsy. However, TE may not be widely available. This study aimed to evaluate the diagnostic performances of aspartate aminotransferase to platelet ratio index (APRI) and fibrosis 4 (FIB‐4) scores compared with TE. Methods: We conducted a multicenter, cross‐sectional study, including all chronic hepatitis C virus (HCV) monoinfection patients with successful and reliable LSM, at 10 centers in Thailand from 2012 to 2017. Characteristics and laboratory data within 3 months of TE were retrospectively reviewed. Using TE as a reference standard, the diagnostic performances of APRI and FIB‐4 were evaluated. TE cut‐off levels of 7.1 and 12.5 kPa represented significant fibrosis (SF) and cirrhosis, respectively. Results: The distribution of FS by TE in 2000 eligible patients was as follows: no SF 28.3%, SF 31.4%, and cirrhosis 40.3%. APRI ≥ 1 provided 70.1% sensitivity and 80.6% specificity, with an area under the receiver operator characteristics curve (AUROC) of 0.834 for cirrhosis. The specificity increased to 96.3% when using a cut‐off level of APRI ≥ 2. FIB‐4 ≥ 1.45 provided a sensitivity, specificity, and AUROC of 52.4%, 91.0%, and 0.829 for cirrhosis, respectively. For SF, APRI performed better than FIB‐4, with an AUROC of 0.84 versus 0.80 (P   1.45 yielded sensitivities of 82.3% and 74.4% and specificities of 65.4% and 69.8%, respectively. Conclusions: APRI and FIB‐4 scores had good diagnostic performances for FS assessment compared with TE, especially for cirrhosis. APRI may be used as the noninvasive assessment in resource‐limited settings for HCV patients’ management.</br