DALLAS – An investigational device that couples laser spectroscopy with a machine-learning algorithm demonstrated a high sensitivity and specificity for discriminating skin cancers from benign lesions in real time, results from a single-center study showed.
“More than 5.4 million cases of nonmelanoma skin cancer were treated in 2012, but the accuracy of skin cancer screening prior to biopsy is pretty low, about 70%, and is individual dependent,” lead study author, said at the annual conference of the American Society for Laser Medicine and Surgery. “There have been several in vivo skin cancer screening devices based on noninvasive techniques such as multispectral imaging, Raman spectroscopy, and electrical impedance spectroscopy, but their diagnostic accuracies were not sufficient for clinical use and could not be applied in real time.”
For the single-site study, carried out in Australia, the researchers collected 502 emission spectra from skin cancers confirmed with biopsy results. They also collected 1,429 emission spectra from benign lesions. They achieved a sensitivity of 92% and a specificity of 90% out of 1,931 spectral data sets. No adverse events occurred and no microscopic damage of the irradiated skin was observed.
“Pathologic diagnosis-based cancer detection is considered to be time- and labor-consuming, and can sometimes be individual dependent,” Dr. Pyun said. “Our real-time, noninvasive, in vivo skin cancer detection device demonstrated a high sensitivity and specificity for discriminating skin cancers from benign lesions.” He added that the device could be helpful in office-based cancer screening and real-time, on-site cancer detection during skin cancer surgeries.
Larger, multicenter studies of the device are being planned. Dr. Pyun holds ownership interests with Speclipse, and is an employee of the company.