A new screening method combines microscopic skin imaging with AI to flag subtle signs of basal cell carcinoma in real time.
Basal cell carcinoma is the most common skin cancer worldwide. It rarely spreads to distant parts of the body, but it can grow into nearby tissue and cause substantial local damage. On the face, that growth can affect structures such as the nose or eyes.
Finding these tumors early can make treatment less invasive. “Detecting basal cell carcinoma early allows for less invasive treatment options,” claims Dr. Moritz Ronicke. “In some cases, all that is required is a cream.”
Researchers are now testing whether advanced imaging combined with artificial intelligence can identify basal cell carcinomas before they are visible during a conventional skin examination.
In a feasibility study involving 150 patients at increased risk of basal cell carcinoma, systematic imaging of facial skin identified histologically confirmed subclinical tumors in 14 patients, or 9.3% of the study group. Of 18 lesions classified as basal cell carcinoma with AI-assisted imaging, 15 were confirmed by biopsy. Two patients declined biopsy, while one lesion proved to be actinic keratosis.
LC-OCT creates detailed images beneath the skin surface
The technique, called line-field confocal optical coherence tomography, or LC-OCT, combines optical coherence tomography (OCT) with confocal microscopy ((LC: Line-field Confocal Microscopy).
OCT helps show the depth and extent of a tumor, while confocal microscopy resolves structures at the cellular level. Together, they produce vertical, horizontal, and three-dimensional images of the skin in real time.
LC-OCT operates at micrometer-scale resolution, allowing physicians to examine structures only thousandths of a millimeter across. A human hair, by comparison, is about 50 micrometers thick (about 0.002 inches).
AI highlights areas that may contain cancer
The AI analyzes LC-OCT images as they are collected and assigns a color-coded probability that basal cell carcinoma is present. This can help physicians identify suspicious areas at a glance, but the software does not make the final diagnosis. That decision remains with the physician.
In the study, the positive predictive value of AI-assisted LC-OCT was 83.3%, meaning that most lesions identified as basal cell carcinoma and subsequently biopsied were confirmed by histology. The researchers did not establish how many tumors the screening method might miss, so its sensitivity remains unknown.
Most detected tumors were superficial basal cell carcinomas. The study also found nodular tumors and one infiltrative basal cell carcinoma.
Researchers are testing systematic facial screening
LC-OCT is already used to detect basal cell carcinoma in the early stages and monitor the success of noninvasive therapies. The newer approach, called SUBSCAN, extends its use by systematically examining facial skin that appears normal to the naked eye in people at elevated risk.
“Our new approach using “SUBSCANS” would allow patients at a high risk of developing skin cancer to receive a diagnosis even earlier on,” explains Moritz Ronicke. “If the SUBSCAN is routinely used in the future, this could lead to more widespread use of creams for treating basal cell carcinoma, even avoiding the need for surgery in such cases.”
SUBSCAN is not yet suitable for routine use. More data are needed to determine its sensitivity, and the method remains too time-consuming.
Reference: “AI-Assisted Line-Field Confocal Optical Coherence Tomography to Detect Subclinical Basal Cell Carcinoma” by Moritz Ronicke, Laura Dürr, Michael W. Höner, Léonie Staats, Michael Erdmann and Carola Berking, 19 August 2026, JAMA Dermatology.
DOI: 10.1001/jamadermatol.2026.2992 **Never miss a breakthrough: Join the SciTechDaily newsletter.**Follow us on Google and Google News.