Congratulations to Profs Aneta Stefanovska and Marco Rossi and their teams at Lancaster and Pisa Universities who generated much interest here recently with their work “Dynamic Markers Based on Blood Perfusion Fluctuations for Selecting Skin Melanocytic Lesions for Biopsy” published in Nature Scientific Reports. The work is available to view here. The authors have presented a non-invasive and accurate identification of malignant melanoma. The technique involves monitoring flow over a period of time to allow study and comparison of the strength of rhythmical fluctuations over different bandwidths using wavelet analysis. They have processed the results of the wavelet analysis to diagnose melanoma lesions on skin with 100% sensitivity and 90.9% specificity. It’s quite a breakthrough as subjective inspection is much less reliable with some reports indicating that up to 80% of skin biopsies returned indicate a non-cancerous melanoma so with refinement this could become a screening technique for the future. Just a reminder then that wavelet analysis is available as standard with moorVMS-PC software.