Using AI to predict pancreatic cancer risk from CT scans
Official title: Predicting Pancreatic Ductal Adenocarcinoma (PDAC) Through Artificial Intelligence Analysis of Pre-Diagnostic CT Images
Funded at Cedars-Sinai Medical Center · NIH-10911178 · Data updated 2026-11-12
This study is looking to use artificial intelligence to help spot people who might be at high risk for pancreatic cancer by analyzing CT scans and other information, so that doctors can catch the disease early and improve chances of survival.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cedars-Sinai Medical Center NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | September 1, 2021 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $631,999 |
| NIH project number | 5R01CA260955-04 |
| Project ID | NIH-10911178 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals who have undergone abdominal CT scans and are at risk for developing pancreatic ductal adenocarcinoma.
✕Less likely to help
Patients who have already been diagnosed with pancreatic cancer or those without any risk factors for PDAC may not benefit from this research.
What this research studies
This research aims to develop a model that uses artificial intelligence to analyze pre-diagnostic CT images and other factors to identify individuals at high risk for pancreatic ductal adenocarcinoma (PDAC) within the next three years. Given that PDAC is a leading cause of cancer-related deaths, early identification is crucial for improving survival rates. The study focuses on extracting critical information from CT scans that may not be visible to radiologists, potentially leading to earlier interventions. By identifying high-risk patients, follow-up imaging or biopsies can be conducted to facilitate early detection and treatment.
Why it matters
Potential benefit: If successful, this research could significantly improve early detection of pancreatic cancer, leading to better treatment outcomes and increased survival rates.
How similar studies have gone: Other research has shown promise in using AI for cancer prediction, indicating that this approach could be effective in identifying high-risk individuals for pancreatic cancer.
Where this research is happening
-
Cedars-Sinai Medical Center
Los Angeles, United States Active
Researchers
- Principal investigator: Li, Debiao — Cedars-Sinai Medical Center
- Study coordinator: Li, Debiao
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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.