AI-powered liver cancer screening using arterial blood flow patterns
Official title: Assessment of sound waves from liver vessels via artificial intelligence to detect liver cancer
Funded at University of Minnesota · NIH-11241817 · Data updated 2026-11-12
A new AI-based method analyzes liver blood flow to help detect liver cancer early in people with liver disease, aiming to be low-cost and easy to use.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Minnesota NIH-funded |
| Lab location | 1 site (Minneapolis, United States) |
| Project start | September 18, 2026 |
| Project end | August 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $441,138 |
| NIH project number | 1R01CA305903-01 |
| Project ID | NIH-11241817 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with liver disease who are at risk for hepatocellular carcinoma and could benefit from enhanced screening.
✕Less likely to help
People without liver disease or those not at risk for HCC are unlikely to benefit.
What this research studies
This project will develop an AI system that looks at how blood moves through the liver to identify signs of hepatocellular carcinoma early on. By focusing on the arterial blood supply unique to liver tumors, the approach aims to distinguish cancer from normal liver tissue without requiring highly trained operators. The study combines medical imaging data with machine learning to create a scalable screening tool that could be used in settings with limited resources. The goal is to provide a practical, accessible option that complements current ultrasound screening to improve early detection. Results will inform whether this arterial-flow based AI method can be deployed in real-world clinics.
Why it matters
Potential benefit: If successful, patients with liver disease could receive earlier and easier screening for liver cancer, potentially improving survival.
How similar studies have gone: Prior AI approaches show promise in cancer detection, but this method specifically leverages arterial blood flow patterns for HCC, representing a novel application.
Where this research is happening
-
University of Minnesota
Minneapolis, United States Active
Researchers
- Principal investigator: Debes, Jose Daniel — University of Minnesota
- Study coordinator: Debes, Jose Daniel
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.