AI-assisted Microendoscopy to Detect Esophageal Cancer Earlier
Official title: AI-Assisted Microendoscopy for the Early Detection of Esophageal Cancer
Funded at Baylor College of Medicine · NIH-11535393 · Data updated 2026-11-12
A technology-based approach uses AI and a tiny endoscopy device to screen for early esophageal cancer, focusing on high-risk regions around the world.</n>
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Baylor College of Medicine NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | September 17, 2014 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $24,000 |
| NIH project number | 3R01CA181275-10S1 |
| Project ID | NIH-11535393 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults undergoing screening or surveillance for esophageal squamous neoplasia, particularly in regions with limited endoscopic screening access.
✕Less likely to help
Patients without signs of esophageal neoplasia or those in settings where AI-assisted screening is not available may not benefit.
What this research studies
This project develops and tests a mobile, high-resolution microendoscope (mHRME) with AI software to identify early esophageal squamous cell neoplasia. It builds on prior work including a large randomized trial and pilot studies in the US, China, and Brazil to improve screening accuracy and reduce unnecessary biopsies. The study integrates deep-learning algorithms to automatically detect neoplastic images during endoscopy and assesses how well experts and non-experts interpret the AI-assisted visuals. The effort aims to make screening more accessible and affordable in underserved regions where endoscopic capacity is limited.
Why it matters
Potential benefit: If successful, patients could receive earlier detection of esophageal cancer with fewer false positives, leading to earlier treatment and better survival chances.
How similar studies have gone: Previous trials showed improved specificity with expert interpretation and promising AI-assisted detection, though performance varied by user experience.
Where this research is happening
-
Baylor College of Medicine
Houston, United States Active
Researchers
- Principal investigator: Mcguire, Amy L — Baylor College of Medicine
- Study coordinator: Mcguire, Amy L
Related research
Other NIH-funded projects on the same topics.
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AI-guided microendoscopy to detect esophageal cancer早期
A doctor-research team is testing an AI-assisted microendoscopy tool to screen people at risk for esophageal cancer, aiming to find cancer early with higher accuracy and fewer unnecessary biopsies.
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Point-of-care esophageal cancer detection in low- and middle-income countries
A researcher-led effort to use a swallowable sponge and a portable chip to detect DNA methylation markers of esophageal cancer right where patients live, helping people in LMICs get quick results.
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AI-assisted Microendoscopy for early esophageal cancer detection
A Baylor College of Medicine team is testing a mobile, AI-driven microscopic imaging tool to help screen for early esophageal cancer in regions with limited screening capacity.
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OmicXScreen: AI-powered blood test to detect liver and esophageal cancers early
A new blood test using AI and DNA methylation patterns aims to detect hepatocellular carcinoma and esophageal cancer early, helping people who are at high risk.
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AI-assisted microendoscopy to find esophageal cancer early
This project uses a small, high-resolution endoscope plus AI to help doctors spot early esophageal cancer in people at risk, especially where screening is limited.
-
AI-assisted microendoscope to find esophageal cancer early
This project uses a small, high-resolution endoscope plus artificial intelligence to help doctors spot early esophageal squamous cell cancer in people at risk, especially where screening is scarce.
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.