A new imaging system to identify tumors in the pancreas and digestive system.
Geles: A Novel Imaging Informatics System for Generalizable Lesion Identification in Neuroendocrine Tumors
['FUNDING_R21'] · UNIVERSITY OF COLORADO DENVER · NIH-10740578
This study is working on a new computer system that uses advanced imaging technology to help doctors find and measure gastroenteropancreatic neuroendocrine tumors more accurately, so patients can get better treatment options and care.
Quick facts
| Phase | ['FUNDING_R21'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF COLORADO DENVER (nih funded) |
| Locations | 1 site (Aurora, UNITED STATES) |
| Trial ID | NIH-10740578 on ClinicalTrials.gov |
What this research studies
This research focuses on improving the detection of gastroenteropancreatic neuroendocrine tumors (GEP-NETs), which are often diagnosed at advanced stages. The project aims to develop an automated imaging informatics system that utilizes deep learning to enhance the identification and quantification of these tumors using advanced PET/CT imaging techniques. By addressing the challenges of dataset shifts, the research seeks to create a more reliable tool for assessing tumor burden, which is crucial for developing effective treatment strategies. Patients may benefit from more accurate monitoring of their disease, leading to better-informed treatment decisions.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals diagnosed with gastroenteropancreatic neuroendocrine tumors who require accurate assessment of their disease.
Not a fit: Patients with neuroendocrine tumors that do not express somatostatin receptor subtype 2 may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved detection and monitoring of neuroendocrine tumors, enhancing treatment outcomes for patients.
How similar studies have performed: Other research has shown promise in using deep learning for automated lesion detection, but this specific approach addressing dataset shifts is relatively novel.
Where this research is happening
Aurora, UNITED STATES
- UNIVERSITY OF COLORADO DENVER — Aurora, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: XING, FUYONG — UNIVERSITY OF COLORADO DENVER
- Study coordinator: XING, FUYONG
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.