Skin electrical scanning to tell if a spot is basal or squamous cell skin cancer
Official title: Electrical impedance dermography as a biomarker for basal and squamous cell carcinoma
Funded at Utah State Higher Education System--University of Utah · NIH-11328116 · Data updated 2026-11-12
This project uses a handheld skin electrical scanner with smart computer analysis to help doctors tell whether common skin spots are harmless, precancerous, or invasive basal or squamous cell cancers.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Utah State Higher Education System--University of Utah NIH-funded |
| Lab location | 1 site (Salt Lake City, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2026 |
| Funding year | 2026 |
| Award (this year) | $210,684 |
| NIH project number | 5R21CA289101-02 |
| Project ID | NIH-11328116 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with new, changing, or suspicious non‑melanoma skin lesions such as possible basal cell carcinoma, squamous cell carcinoma, actinic keratoses, or inflamed benign keratoses would be the ideal candidates.
✕Less likely to help
This would not apply to people without skin lesions or to suspected melanomas, and it may not help cases that are already clearly invasive and require surgical treatment.
What this research studies
From your perspective, a quick, non‑invasive device will be placed on a suspicious skin spot to measure how electricity moves through the lesion. The device sends those measurements to machine‑learning software that aims to tell superficial lesions from deeper, invasive tumors and to separate squamous cell carcinoma‑in‑situ from actinic keratosis or inflamed benign keratoses. The researchers will compare the scanner results to standard clinical exams and biopsy findings to see how well the tool matches real diagnoses. If accurate, the scan could help guide whether a biopsy is needed and which biopsy method to use, potentially reducing unnecessary surgery.
Why it matters
Potential benefit: If successful, this could help doctors spot invasive cancers earlier, avoid unneeded biopsies, and choose less damaging biopsy or treatment approaches.
How similar studies have gone: Previous work shows electrical skin measurements can differ between cancerous and benign lesions, but using machine learning to reliably distinguish superficial from invasive subtypes is a newer, largely unproven approach.
Where this research is happening
-
Utah State Higher Education System--University of Utah
Salt Lake City, United States Active
Researchers
- Principal investigator: Grossman, Douglas — Utah State Higher Education System--University of Utah
- Study coordinator: Grossman, Douglas
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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.