Early detection and risk stratification of liver cancer using AI in cirrhosis patients
Official title: Risk Stratification for and Early Detection of Liver Cancer
Funded at Baylor College of Medicine · NIH-11398195 · Data updated 2026-11-12
This project uses an AI system on data from thousands of people with cirrhosis to identify who is at high risk for liver cancer and to catch it early.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Baylor College of Medicine NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | September 13, 2018 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $766,080 |
| NIH project number | 5U01CA230997-09 |
| Project ID | NIH-11398195 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with cirrhosis enrolled in the TRC cohort or in the indeterminate liver nodules cohort, and individuals at risk of hepatocellular cancer through their liver disease.
✕Less likely to help
Patients not fitting the cirrhosis or indeterminate nodule cohorts or whose data may have limited applicability to their specific condition may not directly benefit.
What this research studies
The Translational Research Center at Baylor College of Medicine is building an AI-based approach to predict hepatocellular cancer risk and enable earlier detection among patients with cirrhosis. It leverages a large, multi-site cohort with extensive clinical data, imaging, and biospecimens, along with a separate nodular lesion cohort, to refine risk models and surveillance strategies. The effort emphasizes collaboration among clinicians, data scientists, and researchers to translate findings into more precise, timely care for patients at risk for liver cancer. Participants would contribute routine clinical data, imaging, and biospecimens as part of ongoing surveillance programs.
Why it matters
Potential benefit: If successful, patients with cirrhosis could receive more personalized surveillance and earlier cancer detection, potentially improving outcomes.
How similar studies have gone: Prior work shows promise in risk stratification and AI-guided surveillance for liver cancer, but this project aims to advance through a larger, multi-site dataset and prospective nodules cohort.
Where this research is happening
-
Baylor College of Medicine
Houston, United States Active
Researchers
- Principal investigator: Kanwal, Fasiha — Baylor College of Medicine
- Study coordinator: Kanwal, Fasiha
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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.