Developing a soft robotic endoscope for early detection of colorectal cancer polyps
Official title: A Novel Framework for Sensitive and Reliable Early Diagnosis, Topographic Mapping, and Stiffness Classification of Colorectal Cancer Polyps
Funded at University of Texas at Austin · NIH-10891721 · Data updated 2026-11-12
This study is testing a new soft robotic tool that helps doctors find and understand colorectal cancer polyps better during exams, making it easier to spot issues early and improve treatment for patients.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas at Austin NIH-funded |
| Lab location | 1 site (Austin, United States) |
| Project start | July 20, 2023 |
| Project end | June 30, 2026 |
| Funding year | 2024 |
| Award (this year) | $211,275 |
| NIH project number | 5R21CA280747-02 |
| Project ID | NIH-10891721 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals undergoing screening or evaluation for colorectal cancer, particularly those with polyps detected during colonoscopy.
✕Less likely to help
Patients who have already been diagnosed with advanced colorectal cancer or those without any gastrointestinal symptoms may not benefit from this research.
What this research studies
This research aims to create a soft robotic endoscope equipped with intelligent tactile sensing and advanced imaging technologies to improve the early detection and classification of colorectal cancer polyps. By utilizing machine learning and computer vision algorithms, the endoscope will provide real-time information about the size, shape, and stiffness of polyps during procedures. This innovative approach seeks to enhance the accuracy of diagnoses and treatment planning for gastrointestinal cancers, ultimately leading to better patient outcomes.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of colorectal cancer, improving treatment options and outcomes for patients.
How similar studies have gone: Previous research has shown promise in using robotic systems and machine learning for cancer detection, indicating that this approach could be a significant advancement in the field.
Where this research is happening
-
University of Texas at Austin
Austin, United States Active
Researchers
- Principal investigator: Alambeigi, Farshid — University of Texas at Austin
- Study coordinator: Alambeigi, Farshid
Related research
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Rewiring Colorectal Cancer to Harness Therapeutic Hyperactivation
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Comparative modeling to guide colorectal cancer screening and care
A researcher team will use computer models to study how access to care, risk, and new screening options affect colorectal cancer outcomes and costs for adults in the US.
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.