Improving lung cancer follow-up care using advanced imaging techniques
OPTimizing surveillance in lung cancer survivors with novel IMAging biomarkers and deep-Learning (OPTIMAL)
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 ID | NIH-11065167 on NIH RePORTER |
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.
Who could benefit from this research
Good fit: 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.
Not a fit: 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.
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 performed: 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
Chapel Hill, United States
- 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
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.