Using AI to predict treatment response in rectal cancer patients
Official title: Pathologically Interpretable Computational Imaging Predictor for Response to Total Neoadjuvant Treatment in Rectal Cancers
Funded at Case Western Reserve University · NIH-11067227 · Data updated 2026-11-12
This study is looking at how advanced computer technology can help doctors better understand MRI scans for people with locally advanced rectal cancer, so they can find out who might not need surgery after treatment and can safely wait and see instead.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Case Western Reserve University NIH-funded |
| Lab location | 1 site (Cleveland, United States) |
| Project start | June 1, 2025 |
| Project end | May 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $48,974 |
| NIH project number | 1F31CA291057-01A1 |
| Project ID | NIH-11067227 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with locally advanced rectal cancer who are undergoing total neoadjuvant therapy.
✕Less likely to help
Patients with rectal cancer who do not undergo total neoadjuvant therapy or those with early-stage disease may not benefit from this research.
What this research studies
This research focuses on improving the treatment of locally advanced rectal cancer by using advanced artificial intelligence techniques to analyze MRI scans. The goal is to identify patients who have a near complete response to total neoadjuvant therapy, allowing them to avoid unnecessary surgery and instead follow a 'watch-and-wait' approach. By leveraging deep learning algorithms, the study aims to enhance the accuracy of MRI evaluations, which can be challenging due to subtle tissue changes. This could lead to better patient outcomes and quality of life for those diagnosed with rectal cancer.
Why it matters
Potential benefit: If successful, this research could allow rectal cancer patients to avoid unnecessary surgeries, improving their quality of life while maintaining effective disease management.
How similar studies have gone: Other research has shown promise in using artificial intelligence for medical imaging analysis, indicating potential success for this novel approach.
Where this research is happening
-
Case Western Reserve University
Cleveland, United States Active
Researchers
- Principal investigator: Desilvio, Thomas — Case Western Reserve University
- Study coordinator: Desilvio, Thomas
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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.