Using AI to improve treatment for craniosynostosis
Official title: Development of deep learning methods to optimize patient personalized treatment for craniosynostosis
Funded at University of Colorado Denver · NIH-10994923 · Data updated 2026-11-12
This study is looking at how to use advanced computer technology to better understand and track the results of surgeries for kids with craniosynostosis, helping doctors improve treatment and ensure healthier head shapes as they grow.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Colorado Denver NIH-funded |
| Lab location | 1 site (Aurora, UNITED STATES) |
| Project start | August 1, 2024 |
| Project end | July 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $37,721 |
| NIH project number | 1F31DE033614-01A1 |
| Project ID | NIH-10994923 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children diagnosed with craniosynostosis who are undergoing or have undergone surgical treatment.
✕Less likely to help
Patients with craniosynostosis who are not candidates for surgery or those who have not received a diagnosis may not benefit from this research.
What this research studies
This research focuses on craniosynostosis, a condition where the skull bones fuse too early, leading to head shape abnormalities and potential complications. The project aims to develop advanced deep learning techniques to analyze 3D images of patients' heads, allowing for a more accurate and objective assessment of surgical outcomes. By automating the evaluation process, the research seeks to provide healthcare professionals with better tools to monitor and optimize treatment for affected children. This innovative approach could enhance the understanding of how different surgical methods impact head shape normalization over time.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatment plans for children with craniosynostosis.
How similar studies have gone: Previous research has shown promise in using 3D imaging and AI for analyzing craniofacial conditions, indicating that this approach could be effective.
Where this research is happening
-
University of Colorado Denver
Aurora, United States Active
Researchers
- Principal investigator: Elkhill, Connor — University of Colorado Denver
- Study coordinator: Elkhill, Connor
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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.