Intelligent and Personalized Online Adaptive Proton Therapy
Funded at University of Chicago · NIH-11601037 · Data updated 2026-11-12
A new, AI-powered online system aims to tailor proton therapy in real time for patients with cancers near vital organs, to reduce side effects and improve outcomes.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | August 1, 2026 |
| Project end | April 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $654,200 |
| NIH project number | 7R01DE033512-03 |
| Project ID | NIH-11601037 on NIH RePORTER |
Who could benefit from this research
✓Could help
Children and adults with cancers located near critical organs who receive proton therapy and are at risk from anatomical changes during treatment.
✕Less likely to help
Patients whose tumors do not require adaptive proton therapy or who cannot tolerate the treatment protocol.
What this research studies
This project uses smart imaging and AI to adapt proton therapy while a patient is on the treatment table, accounting for everyday changes in anatomy. It seeks to streamline the process so new treatment plans are available quickly, minimizing treatment interruptions. By focusing on pediatric and other sensitive anatomies, the goal is to keep the Bragg peak aligned with the tumor and spare healthy tissue. If successful, it could make adaptive proton therapy faster, more accurate, and more accessible in clinical practice.
Why it matters
Potential benefit: If successful, patients could receive more precise radiation with fewer side effects and shorter overall treatment times.
How similar studies have gone: Adaptive proton therapy approaches have shown promise in reducing dosing errors, but online, real-time methods are still being developed and validated.
Where this research is happening
-
University of Chicago
Chicago, United States Active
Researchers
- Principal investigator: Yang, Xiaofeng — University of Chicago
- Study coordinator: Yang, Xiaofeng
Related research
Other NIH-funded projects on the same topics.
-
Efficient AI-Driven Image Guidance for Upright Lung Proton Therapy
A patient-focused AI-powered system helps guide upright proton therapy for lung cancer to improve accuracy and accessibility.
-
3D in vivo dosimetry for FLASH proton therapy
A new protoacoustic dosimeter will help doctors precisely measure dose delivery in proton FLASH therapy for adults with cancer.
-
Dose-LET Volume Histogram to Improve Safe Proton Therapy in Head and Neck Cancer
A Mayo Clinic study will develop a new tool to map dose and LET in spot-scanning proton therapy to reduce severe side effects for head and neck patients.
-
AI-guided proton therapy that adapts during treatment for head and neck cancer
Using AI to build 3D images from routine X-rays so proton therapy can be updated during treatment for people with head and neck cancer.
-
Real-time guided proton radiation for more precise liver tumor treatment
Trying a proton radiation approach that tracks liver tumors in real time to treat people with liver cancer more precisely while protecting healthy liver tissue.
-
Compact upright proton therapy for much faster treatments
This project builds a smaller proton therapy beam-delivery system so people with cancer—especially children and those with moving tumors—can get treatments in seconds instead of minutes.
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.