Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Skin problems are often overlooked due to a lack ofrobust and patient-friendly monitoring tools. Herein, we report arapid, noninvasive, and high-throughput analytical chemical method-ology, aiming at real-time monitoring of skin conditions and earlydetection of skin disorders. Within this methodology, adhesivesampling and laser desorption ionization mass spectrometry arecoordinated to record skin surface molecular mass in minutes.Automated result interpretation is achieved by data learning, usingsimilarity scoring and machine learning algorithms. Feasibility of themethodology has been demonstrated after testing a total of 117 healthy, benign-disordered, or malignant-disordered skins. Remark-ably, skin malignancy, using melanoma as a proof of concept, wasdetected with 100% accuracy already at early stages when the lesionswere submillimeter-sized, far beyond the detection limit of most existing noninvasive diagnosis tools. Moreover, the malignancydevelopment over time has also been monitored successfully, showing the potential to predict skin disorder progression. Capable ofdetecting skin alterations at the molecular level in a nonsurgical and time-saving manner, this analytical chemistry platform ispromising to build personalized skin care