View clinical trials related to Post-hepatectomy Liver Failure.
Filter by:The goal of this in-silico clinical trial is to learn about the usability and clinical effectiveness of an interpretable deep learning framework (VAE-MLP) using counterfactual explanations and layerwise relevance propagation for prediction of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). The main questions it aims to answer are: - To investigate the usability of the VAE-MLP framework for explanation of the deep learning model. - To investigate the clinical effectiveness of VAE-MLP framework for prediction of post-hepatectomy liver failure in patients with hepatocellular carcinoma. In the usability trial the clinicians and radiologists will be shown the counterfactual explanations and layerwise relevance propagation (LRP) plots to evaluate the usability of the framework. In the clinical trial the clinicians and radiologists will make the prediction under two different conditions: with model explanation and without model explanation with a washout period of at least 14 days to evaluate the clinical effectiveness of the explanation framework.
Hepatectomy is an essential treatment for various benign and malignant diseases of the liver. However, post-hepatectomy liver failure (PHLF) is still a life-threatening complication after hepatectomy. The pathophysiological mechanism of PHLF has not yet been fully elucidated, and there is still a lack of effective strategies for either prevention or therapy of PHLF. Sphingolipids include ceramides (CER), sphingomyelins (SM), glycosphingolipids (GSL), sphingosine (SPH), and sphingosine-1-phosphate (S1P) are multi-functional lipids that regulates cell proliferation, cell survival, cell death, inflammation, tissue fibrosis, cancer cell metastasis, and invasion. Liver is a main organ for metabolizing sphingolipids, dysregulation of specific sphingolipids is associated with several liver diseases, therefore sphingolipids have been proposed to be biomarkers of liver diseases, including hepatitis, liver cancer, fatty liver diseases, and liver fibrosis. Moreover, several studies have shown CER, SPH and S1P are critical in regulating pathophysiology of liver diseases, including liver regeneration, necrosis, and inflammation. Given that PHLF causes dramatic dysregulation in biochemical metabolism in liver, the investigators hypothesize that dysregulation of sphingolipid metabolism may also occur in PHLF, and the dysregulation of specific sphingolipids may serve as a biomarker or regulator during progression and recovery of PHLF. This project will examine the association between sphingolipid metabolism and PHLF. Levels of sphingolipid metabolites and their related enzymes in plasma and liver tissue of patients with hepatic resection will be measured by using liquid chromatograph/electrospray ionization/mass spectrometry (LC-ESI-MS/MS) and high-throughput real-time quantitative PCR. This project will facilitate us to identify specific sphingolipid metabolites as biomarker and regulator of PHLF.