SAM #75N98026Q00779

NIH Procurement of Clinical Cohort and Imaging Data for AI-Based Liver Cancer Risk Research

The National Institutes of Health (NIH), through the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), is seeking specialized research data and imaging resources to advance liver cancer risk prediction: - Government Buyer: - National Institutes of Health (NIH) - National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) - Vendor: - University of Pennsylvania (sole source provider) - Products/Services Requested: - Clinical patient cohort data for individuals who underwent liver transplantation due to hepatocellular carcinoma - Associated magnetic resonance imaging (MRI) datasets - De-identified radiology reports - Related clinical data to support research and model development - Unique/Notable Requirements: - Focus on translational research using artificial intelligence (AI) and radiomics - Data and imaging must be suitable for advanced AI-driven analysis to predict liver cancer risk in cirrhosis patients - No specific OEMs, part numbers, or commercial hardware/software products are referenced; the procurement centers on unique clinical and imaging datasets from a single academic source

Description

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.

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