Artificial Intelligence and Radiomics to Predict Hepatocellular Carcinoma Risk in Cirrhosis Patients
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The National Institutes of Health, through the National Institute of Diabetes and Digestive and Kidney Diseases, is advancing research into liver cancer prediction among patients with advanced liver disease or cirrhosis using radiographic imaging and artificial intelligence. This initiative is supported by funding from the Bench-to-Bedside and Back Award Program and aims to enhance risk assessment, evaluate recurrence after curative therapy, and drive translational research in liver disease. The University of Pennsylvania will provide a clinical cohort of patients who underwent liver transplantation for hepatocellular carcinoma, along with associated magnetic resonance imaging studies, de-identified radiology reports, and related clinical data to enable the development and validation of predictive models. The solicitation titled Artificial Intelligence and Radiomics to Predict Hepatocellular Carcinoma Risk in Cirrhosis Patients was posted on July 13, 2026, with a response deadline of July 23, 2026, and falls under NAICS code 611310. The opportunity is managed by the Office of the Director at the NIH in Bethesda, Maryland, with James B. Law serving as the primary point of contact. No set-aside provisions apply, and the performance location is in Bethesda, Maryland, aligning with the agency’s primary research infrastructure and clinical collaboration networks.
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Bethesda, MD, 20892, USASet-Aside
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The mission of the National Institute of Diabetes and Digestive and Kidney Diseases is to conduct and support medical research and research training and to disseminate science-based information on diabetes and other endocrine and metabolic diseases; digestive diseases, nutritional disorders, and obesity; and kidney, urologic, and hematologic diseases to improve people’s health and quality of life.
The Liver Diseases Branch is conducting research using radiographic imaging and artificial intelligence to evaluate liver cancer risk in patients with advanced liver disease or cirrhosis. Funding for this effort was awarded through the Bench-to-Bedside and Back Award Program (Award Number 1517448). A portion of the awarded funding will be used to acquire a clinical patient cohort, associated radiographic imaging datasets, and de-identified radiology reports from the University of Pennsylvania.
The research focuses on the use of imaging data and artificial intelligence to improve prediction of liver cancer risk, evaluate liver cancer recurrence following curative therapy, and support translational research related to liver disease and liver cancer. To support these research objectives, the University of Pennsylvania will provide a clinical cohort of patients who underwent liver transplantation for hepatocellular carcinoma, together with associated magnetic resonance imaging studies, radiology reports, and related clinical data necessary for research analysis and model development.
