AI safety checks for MRI-guided adaptive radiation therapy
Artificial Intelligence-Based Quality Assurance for Online Adaptive Radiotherapy
This project uses artificial intelligence to run fast safety and quality checks during MRI-guided, same-day radiation treatments for people with advanced cancer.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ut Southwestern Medical Center NIH-funded |
| Lab location | 1 site (Dallas, United States) |
| Project ID | NIH-11285235 on NIH RePORTER |
What this research studies
If you are getting MRI-guided adaptive radiotherapy (MR-LINAC), the team will develop an AI tool that automatically reviews daily MRI scans, organ and tumor outlines, and the adjusted treatment plan to spot mistakes before treatment. The system is trained on prior patient images and plans and tested within the clinical workflow to keep checks quick and reliable. By automating routine quality assurance steps, the tool aims to reduce human errors and shorten the time you spend on the treatment couch. Developers will refine the AI with clinical data and simulated cases before using it alongside clinical teams.
Who could benefit from this research
Good fit: Ideal candidates are people with advanced cancers who are scheduled to receive MRI-guided, online adaptive radiotherapy (MR-LINAC).
Not a fit: Patients who are not treated with MR-LINAC (standard radiotherapy without same-day adaptation) are unlikely to benefit from this specific QA tool.
Why it matters
Potential benefit: If successful, this could make MRI-guided same-day radiation safer and faster by automatically catching planning or delivery errors.
How similar studies have performed: Early pilot work on AI tools for radiotherapy QA and image-guided planning shows promise, but this approach remains an emerging area needing more clinical validation.
Where this research is happening
Dallas, United States
- Ut Southwestern Medical Center — Dallas, United States (Active)
Researchers
- Principal investigator: Jiang, Steve Bin — Ut Southwestern Medical Center
- Study coordinator: Jiang, Steve Bin
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 below.