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-11535418 · Data updated 2026-11-12
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.
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) | $10,654 |
| NIH project number | 3U01CA269143-04S6 |
| Project ID | NIH-11535418 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cervical cancer or head-and-neck cancer who are candidates for radiotherapy and treated at participating centers.
✕Less likely to help
Patients not receiving radiotherapy or treated outside participating sites may not benefit.
What this research studies
This project uses artificial intelligence to automatically outline risky anatomy and shape radiation beams for cervical and head-and-neck cancers. It is a non-randomized, prospective study conducted at University College London to see how well the AI-based planning matches expert plans and what it costs in real-world use. The goal is to speed up treatment planning from weeks to potentially under a day while preserving accuracy and safety. If successful, the approach could expand access to radiotherapy in low- and middle-income countries by reducing the need for specialized staff and resources.
Why it matters
Potential benefit: If successful, patients could receive faster and potentially more consistent radiotherapy planning, increasing access to curative treatment in resource-limited settings.
How similar studies have gone: Previous AI-assisted radiotherapy planning work has shown promise in improving efficiency and planning quality, though the LMIC context and non-randomized design are important factors here.
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 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.
-
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.
-
AI-powered radiotherapy planning for cervical and head-and-neck cancer
A UK-led study is testing an AI system that helps plan and optimize radiotherapy for cervical and head-and-neck cancer to reduce wait times and required staff.
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.