Improving quality assurance in radiation therapy using AI tools
Official title: Development of AI-Augmented quality assurance tools for radiation therapy
Funded at Stanford University · NIH-11014970 · Data updated 2026-11-12
This study is working on using smart computer tools to make sure that radiation therapy for cancer is done safely and accurately, so patients can feel confident they are getting the best treatment possible.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | February 1, 2023 |
| Project end | January 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $514,576 |
| NIH project number | 5R01CA275772-03 |
| Project ID | NIH-11014970 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients undergoing radiation therapy for cancer treatment.
✕Less likely to help
Patients who are not receiving radiation therapy or those with conditions that do not require such treatment may not benefit from this research.
What this research studies
This research focuses on enhancing the quality assurance (QA) processes in radiation therapy by developing advanced AI-augmented tools. It aims to address current limitations in QA methods, which can be labor-intensive and costly, by leveraging deep learning techniques. The project will create a framework to verify treatment machine parameters and dose delivery, ensuring that patients receive accurate and effective radiation treatment. By integrating AI into the QA workflow, the research seeks to improve the reliability and efficiency of radiation therapy.
Why it matters
Potential benefit: If successful, this research could lead to safer and more effective radiation therapy treatments for patients.
How similar studies have gone: Other research has shown promising results in using AI for medical applications, indicating potential success for this innovative approach.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Xing, Lei — Stanford University
- Study coordinator: Xing, Lei
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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.