Improving lung cancer follow-up care using advanced imaging techniques
Official title: OPTimizing surveillance in lung cancer survivors with novel IMAging biomarkers and deep-Learning (OPTIMAL)
Funded at Univ of North Carolina Chapel Hill · NIH-11065167 · Data updated 2026-11-12
This study is looking to improve the follow-up care for people who have survived lung cancer by using special imaging techniques to better understand their health, helping doctors predict if cancer might come back or if new cancers could develop, so that survivors get the right care they need without extra tests they don’t.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $968,999 |
| NIH project number | 1R01CA298002-01 |
| Project ID | NIH-11065167 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have undergone treatment for early-stage non-small cell lung cancer and are in the post-operative phase of their care.
✕Less likely to help
Patients who have not been diagnosed with lung cancer or those who are not survivors of early-stage non-small cell lung cancer may not benefit from this research.
What this research studies
This research aims to enhance the follow-up care for lung cancer survivors by utilizing advanced imaging biomarkers and deep learning technology. It focuses on analyzing chest CT scans to identify specific body composition and cardiopulmonary health indicators that can predict the risk of cancer recurrence or the development of new lung cancers. By tailoring surveillance strategies based on individual risk factors, the study seeks to optimize the monitoring process for lung cancer survivors, ensuring they receive the most appropriate care without unnecessary procedures.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective follow-up care for lung cancer survivors, potentially reducing the risk of recurrence and improving long-term health outcomes.
How similar studies have gone: Previous studies have shown promise in using imaging biomarkers from CT scans to predict outcomes in lung cancer patients, indicating that this approach has potential for success.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Henderson, Louise — Univ of North Carolina Chapel Hill
- Study coordinator: Henderson, Louise
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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.