AI-powered radiotherapy planning for cervical and head-and-neck cancer
Official title: ARCHERY: Artificial Intelligence based Radiotherapy treatment planning for Cervical and Head and Neck cancer
Funded at University College London · NIH-11415643 · Data updated 2026-11-12
A new AI-based system helps doctors plan cervical and head-and-neck cancer radiotherapy faster and with less labor, aiming to reach more patients, especially in low- and middle-income countries.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University College London NIH-funded |
| Lab location | 1 site (London, United Kingdom) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $163,987 |
| NIH project number | 5U01CA269143-04 |
| Project ID | NIH-11415643 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults with cervical cancer or head-and-neck cancer who are candidates for radiotherapy and treated at participating LMIC-priority centers.
✕Less likely to help
Patients whose tumors are outside the targeted sites or who require alternative treatment modalities may experience no direct benefit.
What this research studies
This project from University College London develops AI software to automatically outline critical anatomy and to define radiation beam positions for cervical and head-and-neck cancers. It will be tested in a non-randomized, prospective study involving about 706 patients to measure how well the AI plans match expert standards and how the technology impacts costs. If successful, the approach could shorten planning time from weeks to under a day and reduce the need for specialized staff, potentially increasing access to radiotherapy in LMICs. The study will focus on improving treatment accuracy while lowering resource requirements in high-need settings.
Why it matters
Potential benefit: If successful, patients could receive timely, accurate radiotherapy with less dependence on scarce workforce resources.
How similar studies have gone: Preliminary AI planning tools have shown promise in improving planning efficiency, but this exact approach in LMIC settings is still being evaluated.
Where this research is happening
-
University College London
London, United Kingdom Active
Researchers
- Principal investigator: Aggarwal, Ajay — University College London
- Study coordinator: Aggarwal, Ajay
Related research
Other NIH-funded projects on the same topics.
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AI-powered radiotherapy planning for cervical and head-and-neck cancer
A computer program helps plan radiation therapy for cervical and head-and-neck cancer patients to make treatments faster and more accurate.
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AI-powered radiotherapy planning for cervical and head-and-neck cancer
A United Kingdom study is testing AI software that helps plan radiotherapy for cervical and head-and-neck cancer patients to save time and reduce the workload for clinicians in low-resource settings.
-
AI-powered radiotherapy planning for cervical and head-and-neck cancer
A UK research team is testing an AI-based software to automatically outline cancer areas and plan radiation beams to speed up treatment for cervical and head-and-neck cancers in LMICs.
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AI-Powered Radiotherapy Planning for Cervical and Head & Neck Cancer
A new AI tool helps plan radiation therapy for cervical and head-and-neck cancers to save time and reduce the need for specialized staff.
-
AI-powered radiotherapy planning for cervical and head-and-neck cancer
A UK study from University College London uses AI to plan radiotherapy for cervical and head-and-neck cancers to save time and reduce the need for specialized staff, aiming to help patients in LMICs.
-
AI-powered radiotherapy planning for cervical and head & neck cancer
A non-randomized study will test an AI system that helps plan radiotherapy for cervical and head & neck cancers to save time and resources in LMICs.
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.