Using advanced imaging techniques to diagnose skin cancers without biopsies
Official title: Machine Learning and Reflectance Confocal Microscopy for Biopsy-free Virtual Histology of Squamous Skin Neoplasms
Funded at VA Greater Los Angeles Healthcare System · NIH-11046554 · Data updated 2026-11-12
This study is working on a new way to help doctors spot skin cancers, especially in veterans who are more likely to get them, by using special imaging technology that can give quick and accurate results without needing a biopsy.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | VA Greater Los Angeles Healthcare System NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | January 1, 2022 |
| Project end | December 31, 2025 |
| Funding year | 2025 |
| NIH project number | 5I01CX002194-04 |
| Project ID | NIH-11046554 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include veterans and individuals with suspicious skin lesions that may be indicative of keratinocyte carcinomas.
✕Less likely to help
Patients with confirmed skin cancer who require immediate surgical intervention may not benefit from this non-invasive diagnostic approach.
What this research studies
This research focuses on improving the diagnosis of skin cancers, particularly keratinocyte carcinomas, using advanced imaging technologies like reflectance confocal microscopy (RCM) combined with machine learning. The goal is to develop a non-invasive method that allows dermatologists to accurately identify skin lesions without the need for biopsies, which can lead to scarring and additional procedures. By enhancing the imaging capabilities, the research aims to provide immediate diagnosis and treatment during the same clinic visit, improving patient access to care. This approach is particularly beneficial for veterans who are at higher risk for skin cancers due to sun exposure.
Why it matters
Potential benefit: If successful, this research could significantly reduce the need for biopsies, leading to less scarring and quicker diagnosis and treatment for skin cancers.
How similar studies have gone: Other research has shown promise in using advanced imaging techniques for skin cancer diagnosis, but this specific combination of RCM and machine learning is relatively novel.
Where this research is happening
-
VA Greater Los Angeles Healthcare System
Los Angeles, United States Active
Researchers
- Principal investigator: Scumpia, Philip — VA Greater Los Angeles Healthcare System
- Study coordinator: Scumpia, Philip
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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.