A new diagnostic device based on Raman spectroscopy could assist physicians with the early detection of skin cancers.
A new diagnostic device based onRaman spectroscopy could assistphysicians with the early detectionof skin cancers. The system is beingstudied by Harvey Lui, a professorof dermatology and chair of thedepartment of dermatology andskin science at the University ofBritish Columbia (Vancouver, BritishColombia). Lui is the coinventor ofthe device, which he has licensed toVerisante (Vancouver).
In preliminary data published in2008, Lui and colleagues observed289 skin cancers and benign lesions,and found that skin cancers couldbe distinguished from benign skinlesions with a sensitivity of 91%and specificity of 75%. Malignantmelanoma could be distinguishedfrom benign pigmented lesions witha sensitivity of 97% and a specificityof 78%.
Lui says the new device overcomesone of the key limitations of usingRaman spectroscopy in medicine,which is the amount of time neededto acquire data.
“In the past, to collect Raman datafrom the skin, the patient would haveto sit still for 20 minutes, and thatis not practical,” Lui said in a May 1article in Dermatology Times. “Butnow it’s possible to acquire this signalwithin seconds, and that’s been thebreakthrough.”
Another advantage of the system, Luisays, is that it is user-friendly and canbe used easily by technicians, and thisdoes not require the extensive trainingthat confocal microscopy does.
The device, called the VerisanteAura, has been approved for use inCanada and Europe, but US approvalis not expected until next year.
Best of the Week: SciX Award Interviews, Tip-Enhanced Raman Scattering
June 13th 2025Top articles published this week include an interview about aromatic–metal interactions, a tutorial article about the recent advancements in tip-enhanced Raman spectroscopy (TERS), and a news article about using shortwave and near-infrared (SWIR/NIR) spectral imaging in cultural heritage applications.
Hyperspectral Imaging for Walnut Quality Assessment and Shelf-Life Classification
June 12th 2025Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.