AI-powered liver cancer screening using ultrasound 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-11638603 · Data updated 2026-11-12
A new AI-based method analyzes liver blood flow signals to help detect liver cancer early in people with liver disease, especially in settings with limited resources.
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) | $18,735 |
| NIH project number | 3R01CA305903-01S1 |
| Project ID | NIH-11638603 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with chronic liver disease or risk factors for hepatocellular carcinoma, particularly in resource-limited settings.
✕Less likely to help
Individuals without liver disease or liver cancer risk factors are unlikely to benefit.
What this research studies
This project aims to develop an AI tool that uses ultrasound-based signals of how blood moves through liver vessels to identify early signs of hepatocellular carcinoma (HCC). It focuses on making screening affordable, scalable, and easy to use without requiring highly specialized expertise. Researchers will work with existing ultrasound images and related blood-flow data to train and validate the AI model, with attention to real-world clinical settings. If successful, the approach could complement or improve current screening methods by catching cancer earlier when curative options are possible.
Why it matters
Potential benefit: If successful, this AI tool could enable earlier and more accurate liver cancer screening, potentially saving lives through earlier treatment.
How similar studies have gone: AI-based imaging analysis has shown promise in cancer detection, but applying vascular-flow patterns to HCC screening is a novel approach that warrants validation.
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.