Using deep learning to improve radiation therapy without invasive markers
Leveraging deep learning for markerless motion management in radiation therapy
This study is exploring a new way to make radiation therapy better for patients with prostate and pancreatic cancers by using advanced computer technology to track tumor movement during treatment, so they can get more precise care without needing any invasive procedures.
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 ID | NIH-11081768 on NIH RePORTER |
What this research studies
This research focuses on enhancing radiation therapy by utilizing deep learning techniques to manage organ motion without the need for invasive fiducial markers. By analyzing images from X-ray and cone beam CT scans, the project aims to develop a system that can accurately localize tumors in real-time, thereby improving treatment precision. The approach seeks to reduce complications associated with traditional methods, such as bleeding and infection, while also increasing the effectiveness of radiation delivery. Patients undergoing treatment for prostate and pancreatic cancers may particularly benefit from this innovative technology.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients undergoing radiation therapy for prostate or pancreatic cancers.
Not a fit: Patients who are not receiving radiation therapy or those with cancers that do not involve organ motion may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to safer and more effective radiation therapy for cancer patients.
How similar studies have performed: Other research has shown promise in using deep learning for medical imaging, suggesting that this approach could be effective, though it is still relatively novel in the context of radiation therapy.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Xing, Lei — Stanford University
- Study coordinator: Xing, Lei
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.