The complex biological process of skin aging can now be studied more extensively and efficiently, thanks to a new low-cost laser-based technique. A laser-speckle imaging technique using low-power red lasers can assess skin aging better than traditional imaging methods, a team at De Montfort University has discovered. As a possible alternative to high-cost confocal microscopy, it could lead to better understanding of skin growth, damage and diseases, and could also lead to better and more personalized skin treatment. A laser-speckle imaging technique using red laser illumination can better assess skin aging and changes. Images courtesy of De Montfort University. Aging affects skin beyond the surface layer, namely in the basal layer (stratum basale) that sits about 0.1 mm below the surface, where changes including cell size, as well as blood flow and content can occur. The researchers collected skin data from study participants ranging in age from 19 to 60, divided into two groups: under 30 and over. The team used two different techniques to compare textural response, laser-speckle imaging and conventional RGB/IR light back-scatter reading technique. To generate the speckle effect, a 3840 × 2880-resolution modified CCD camera with red laser illumination was used at a 23° angle to visualize skin layers and cells beyond the surface. The RGB/IR light source used provided only a single reflection reading; its resolution was shown to be insufficient for cell-level analysis. The optical components of the laser-speckle imaging technique. Ultimately, the noninvasive laser-speckle technique was a “substantial improvement” over the RGB/IR light, and can detect multilayer cellular textural changes caused by aging, the researchers wrote in their paper. The researchers had previously used these imaging methods to study optical skin modeling: They introduced a hybrid method for development of a parametric optical skin model that used various techniques such as light back-scatter analysis, image-texture analysis, laser speckle imaging and Bayesian inference methods. In that study, they identified subtle skin changes and were able to detect early signs of various abnormalities and diseases. The current study is to be presented in June at the IEEE-EMBS International Conferences on Biomedical and Health Informatics in Valencia, Spain. For more information, visit: www.dmu.ac.uk