AI-assisted 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-11399431 · Data updated 2026-11-12
This project uses artificial intelligence to speed up and improve radiotherapy planning for people with cervical or head and neck cancer, especially in areas with limited specialist staff.
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 | 2025 |
| Award (this year) | $24,653 |
| NIH project number | 3U01CA269143-03S4 |
| Project ID | NIH-11399431 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people diagnosed with cervical or head and neck cancers who are scheduled to receive radiotherapy at a participating center, especially in low- and middle-income countries.
✕Less likely to help
People with other types of cancer, those not receiving radiotherapy, or patients treated outside participating sites are unlikely to receive direct benefit from this project.
What this research studies
This project will use software that automatically outlines tumor and nearby organs on CT scans and creates radiation beam plans so doctors can treat cervical and head and neck cancers faster. It is a non-randomized prospective study enrolling about 706 patients (353 per cancer type) to compare the quality and economic impact of AI-generated plans with current clinical practice. The team aims to reduce planning time from weeks to less than a day and lower the need for specialized workforce. Data will be collected at participating cancer centers, particularly in low- and middle-income countries, to evaluate real-world performance and feasibility.
Why it matters
Potential benefit: If successful, this could make radiotherapy faster, more accurate, and much more available in areas with few specialist staff.
How similar studies have gone: Previous AI tools for automatic contouring and treatment planning have shown promising accuracy and speed in pilot and single-center studies, but larger multi-center real-world evaluations are still needed.
Where this research is happening
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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.
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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.
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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.