View clinical trials related to Liver Cancer.
Filter by:Liver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer death worldwide. It is the 3rd most common cause of cancer death in Hong Kong. The five-year survival rates of liver cancer differ greatly with disease staging, ranging from 91.5% in early-stage to 11% in late-stage. The early and accurate diagnosis of liver cancer is paramount in improving cancer survival. Liver cancer is diagnosed radiologically via cross sectional imaging, e.g. computed tomography (CT), without the routine use of liver biopsy. However, with current internationally-recommended radiological reporting methods, up to 49% of liver lesions may be inconclusive, resulting in repeated scans and a delay in diagnosis and treatment. An artificial intelligence (AI) algorithm that that can accurately diagnosed liver cancer has been developed. Based on an interim analysis, the algorithm achieved a high diagnostic accuracy. The AI algorithm is now ready for implementation. This study aims to prospective validate this AI algorithm in comparison with the current standard of radiological reporting in a randomized manner in the at-risk population undergoing triphasic contrast CT. This research project is totally independent and separated from the actual clinical reporting of the CT scan by the duty radiologist. The primary study outcome is the diagnostic accuracy of liver cancer, which will be unbiasedly based on a composite clinical reference standard.
Tumor infiltration lymphocytes (TILs) have been harvested from advanced cancer patients and constructed to knockout PD1 gene and express scFvs against both PD1 and CTALA4 and CARs against various antigens, followed by transfusion into the patients. The safety, tolerance, and preliminary clinical efficacy of the TILs will be evaluated.
The primary objective of this study, DELFI-L101, is to train and test classifiers for lung cancer detection using the DELFI assay and other biomarker and clinical features.
Liver Transplantation for Unresectable GIST Liver Metastases
This study is aimed at assessing the effectiveness of a novel liver specific nerve block in improving pain control during painful liver interventional radiology procedures including liver tumoral ablation and trans arterial chemoembolization, two procedures aimed at controlling liver tumors, but that can be associated with significant pain. This novel hepatic specific nerve block was designed by us and initial retrospective results suggests it might help in controlling such liver procedural derived pain. The study was designed to compare the liver block to a sham procedure in a blinded context and to follow the participants over three days post-procedure to asses for pain levels.
Radiological response after trans arterial chemoembolization (TACE) is classified according to Modified Response Evaluation Criteria in Solid Tumors (mRECIST) to: complete response (CR) (disappearance of arterial enhancement), partial response (PR) ( at least a 30% decrease in the sum of diameters of viable enhancement), progressive disease (PD) (an increase of at least 20% in the sum of the diameters of viable enhancement, or appearance of new lesions), and stable disease (any cases that do not qualify for either partial response or progressive disease
Thromboprophylaxis for liver surgery can be commenced either preoperatively or postoperatively. Despite a clear trade-off between thrombosis and bleeding in liver surgery patients, there is no international consensus when thrombosis prophylaxis should be commenced in patients undergoing liver surgery. As far as we know, there are no prospective randomized trials in this field, and current guidelines are unfortunately based on very low quality evidence, that is, a few retrospective studies and expert opinion. Both American and European thromboprophylaxis guidelines for abdominal cancer surgery support the preoperative initiation of thromboprophylaxis, but these guidelines do not specifically address the increased bleeding risk associated with liver surgery. On the contrary, Dutch guidelines recommend postoperative thromboprophylaxis only, because of lack of evidence for preoperative thromboprophylaxis. Traditionally, many liver surgery units have been reluctant in using preoperative thromboprophylaxis due to the potentially increased risk of bleeding complications. Enhanced Recovery After Surgery (ERAS) Society Guidelines recommend preoperative thromboprophylaxis in liver surgery, but the guidelines provide no supporting evidence for this recommendation. Overall, the amount of evidence is scarce and somewhat contradictory in this clinically relevant field of thromboprophylaxis in liver surgery. The aim of this study is to compare pre- and postoperatively initiated thromboprophylaxis regimens in liver surgery in a randomized controlled trial.
Patients may be considered if the cancer has come back, has not gone away after standard treatment or the patient cannot receive standard treatment. This research study uses special immune system cells called CARE T cells, a new experimental treatment. The body has different ways of fighting infection and disease. No single way seems perfect for fighting cancers. This research study combines two different ways of fighting cancer: antibodies and T cells. Antibodies are types of proteins that protect the body from infectious diseases and possibly cancer. T cells, also called T lymphocytes, are special infection-fighting blood cells that can kill other cells, including cells infected with viruses and tumor cells. Both antibodies and T cells have been used to treat patients with cancers. They have shown promise, but have not been strong enough to cure most patients. Investigators have found from previous research that they can put a new gene (a tiny part of what makes-up DNA and carries a person's traits) into T cells that will make them recognize cancer cells and kill them. In the lab, investigators made several genes called a chimeric antigen receptor (CAR), from an antibody called GPC3. The antibody GPC3 recognizes a protein found solid tumors including pediatric liver cancers. This CAR is called GPC3-CAR. To make this CAR more effective, investigators also added two genes that includes IL15 and IL21, which are protein that helps CAR T cells grow better and stay in the blood longer so that they may kill tumors better. The mixture of GPC3-CAR and IL15 plus IL21 killed tumor cells better in the laboratory when compared with CAR T cells that did not have IL15 plus IL21 .This study will test T cells that investigators made (called genetic engineering) with GPC3-CAR and the IL15 plus IL21 (CARE T cells) in patients with GPC3-positive solid tumors. T cells made to carry a gene called iCasp9 can be killed when they encounter a specific drug called AP1903. The investigators will insert the iCasp9 and IL15 plus IL21 together into the T cells using a virus that has been made for this study. The drug (AP1903) is an experimental drug that has been tested in humans with no bad side-effects. The investigators will use this drug to kill the T cells if necessary due to side effects. This study will test T cells genetically engineered with a GPC3-CAR and IL15 plus IL21 (CARE T cells) in patients with GPC3-positive solid tumors. The CARE T cells are an investigational product not approved by the Food and Drug Administration. The purpose of this study is to find the biggest dose of CARE T cells that is safe, to see how long they last in the body, to learn what the side effects are and to see if the CARE T cells will help people with GPC3-positive solid tumors.
Clearing potential intrahepatic metastasis to prevent early recurrence after liver cancer treatment, there are no effective interventions so far. For secondary metastatic cancer, only the lesions visible under ultrasound can be used, one by one for local ablation and chemotherapy, but people may develop new tumor lesions. Therefore, the treatment of potential tumors and recurrent tumors after ablation is a very important clinical issue.
Liver resection remains the only curative option for primary or metastatic liver cancer, but a more accurate prediction of post-hepatectomy liver failure (PHLF) is needed to further reduce morbidity and mortality and to extend the indication to a wider patient population. Magnetic resonance Imaging (MRI) is a promising new source of liver function tests as it can provide segmental function alongside measurements of perfusion, tissue structure and standard morphological assessment. The primary aim of HEPARIM is to determine if quantitative MRI biomarkers of liver function and perfusion can improve predictions of post-hepatectomy liver function, as measured by an indocyanine green (ICG) liver function test. Secondary aims is to validate the MRI measurements of liver function against ICG. HEPARIM is an observational cohort study recruiting patients referred locally for a one- or two-stage liver resection of 2 segments or more. Before surgery, all participants will undergo an ICG liver function test and a Dynamic Gadoxetate-enhanced (DGE) MRI scan of the liver. The ICG test will be repeated at one day after surgery. The Gadoxetate Clearance (GC) of the future liver remnant (FLR-GC) will be determined from the DGE-MRI data and correlated to the post-operative ICG R15 as primary outcome measure. Preoperative ICG R15 will be correlated against GC of the whole liver (WL-GC) to address the secondary objective. In patients that undergo a staged hepatectomy, an additional MRI and ICG test will be performed before the first stage to assess its effect on volumetric and functional growth of the FLR. Additional pre- and postoperative data will be collected from medical records including demographics and medical histories, biochemistry, pathology and radiology reports, and any long-term outcome data collected in the 90-day follow-up visit. These data will be used in a multi-variate analysis to determine which preoperative biomarkers are most predictive of immediate and long-term outcomes, to identify the added value of functional MRI over routine clinical markers, and to derive a multi-variate prediction model that can be validated in future studies.