Using advanced imaging techniques to assess the risk of precancerous oral lesions
Official title: Decoding FTIR-based multimodal imaging for risk assessment of precancerous oral lesions
Funded at University of Missouri Kansas City · NIH-11116278 · Data updated 2026-11-12
This study is working on a new way to better diagnose and manage mouth lesions that could turn into cancer, using advanced imaging and technology to help doctors more accurately determine the risk for each patient.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Missouri Kansas City NIH-funded |
| Lab location | 1 site (Kansas City, United States) |
| Project start | September 19, 2024 |
| Project end | September 18, 2025 |
| Funding year | 2024 |
| Award (this year) | $550,296 |
| NIH project number | 1R56DE034052-01 |
| Project ID | NIH-11116278 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with oral potentially malignant disorders (OPMDs) who are at risk of developing oral squamous cell carcinoma.
✕Less likely to help
Patients with confirmed oral squamous cell carcinoma or those without any oral lesions may not benefit from this research.
What this research studies
This research focuses on improving the diagnosis and management of oral mucosal lesions, particularly those that may lead to oral squamous cell carcinoma (OSCC). It aims to develop a novel diagnostic platform that combines Fourier Transform Infrared (FTIR) imaging, histological imaging, and spatial transcriptomics to provide a more accurate risk assessment for precancerous oral lesions. By utilizing machine learning and deep learning techniques, the study seeks to create predictive models that can objectively evaluate the risk of malignant transformation in individual cases. This approach addresses the limitations of current subjective histopathological methods, potentially leading to better patient outcomes.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and timely diagnoses of precancerous oral lesions, improving treatment options and outcomes for patients.
How similar studies have gone: Other research has shown promise in using multimodal imaging and machine learning techniques for cancer diagnosis, indicating that this approach could be effective.
Where this research is happening
-
University of Missouri Kansas City
Kansas City, United States Active
Researchers
- Principal investigator: Wang, Rong — University of Missouri Kansas City
- Study coordinator: Wang, Rong
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.