AI-assisted radiotherapy planning for cervical and head and neck cancer
ARCHERY: Artificial Intelligence based Radiotherapy treatment planning for Cervical and Head and Neck cancer
This project uses artificial intelligence to make radiotherapy planning faster and more accurate for people with cervical or head and neck cancer, 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 ID | NIH-11399432 on NIH RePORTER |
What this research studies
You would have your CT scans processed by AI that automatically outlines tumors and nearby organs at risk and suggests radiation beam positions and shapes, with clinicians reviewing the results. The team plans a non-randomized prospective study enrolling about 706 patients (roughly 353 with cervical cancer and 353 with head and neck cancer) to compare AI-generated plans to current practice. Researchers will measure plan quality, time saved, and economic impact with the goal of reducing planning time from weeks to less than a day and lowering workforce needs. The work is led by University College London in collaboration with partner treatment centers, focusing on sites where radiotherapy access is limited.
Who could benefit from this research
Good fit: People diagnosed with cervical or head and neck cancer who are planned to receive radiotherapy at a participating center, particularly in low- and middle-income countries, are ideal candidates.
Not a fit: Patients who are not receiving radiotherapy, those with cancers outside the targeted sites, or those needing highly individualized or experimental radiation approaches may not benefit from this project.
Why it matters
Potential benefit: If successful, this could shorten radiotherapy wait times, improve treatment accuracy, and expand access to curative radiotherapy in resource-limited settings.
How similar studies have performed: Previous pilot studies of AI auto-contouring and automated planning have shown promising accuracy and time savings, but large prospective clinical evaluations in LMIC settings remain limited.
Where this research is happening
London, United Kingdom
- University College London — London, United Kingdom (Active)
Researchers
- Principal investigator: Aggarwal, Ajay — University College London
- Study coordinator: Aggarwal, Ajay
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.