Georgios N Stamatas
SGS, France
Abstract Title: Advances in non-invasive optical biopsy techniques for in vivo skin analysis: New perspectives on skin aging
Biography:
Dr. Georgios Stamatas brings over 25 years of international experience in the Health Care industry, with a deep passion for translating scientific discovery into actionable insights. His research focuses on skin physiology and the effects of topical skin care products, driving innovation across multiple domains including the microbiome, metabolome, computational biology, and non-invasive clinical methods. Dr. Stamatas holds a PhD in Chemical/Biomedical Engineering and has authored over 110 peer-reviewed publications and 14 patents.
Research Interest:
Non-invasive high-resolution imaging has emerged as a powerful approach to objectively characterize structural and functional hallmarks of skin aging in vivo. Reflectance confocal microscopy (RCM) now offers faster acquisition, larger mosaics, and improved contrast, enabling near-histologic visualization of the epidermis and dermal–epidermal junction over extended skin sites. These technical improvements allow quantitative assessment of epidermal thickness, keratinocyte and melanocyte morphology, papillary and reticular dermal architecture, microvascular morphology, and the presence of elastotic material, supporting differentiation between intrinsic and photoinduced aging. Line-field confocal optical coherence tomography (LC-OCT) combines vertical and horizontal sectioning at quasi-cellular resolution with increased penetration depth, making it possible to extract continuous depth profiles of epidermal and dermal thickness, dermal–epidermal junction undulation, appendage density, and early microstructural alterations in collagen and elastin. Multiphoton microscopy (MPM), using two-photon excited fluorescence and second-harmonic generation, has benefited from more compact lasers, higher acquisition speed, and automated 3D mapping, enabling label-free imaging of endogenous fluorophores and fibrillar collagen. From MPM images, quantitative parameters such as collagen fiber orientation, density, and fragmentation, elastin-to-collagen ratios, and metabolic state (NAD(P)H) can be derived, capturing both structural and functional aspects of aging. Across all three modalities, advanced image analysis and machine-learning pipelines now allow automated segmentation and extraction of multiparametric biomarkers. Together, RCM, LC-OCT, and MPM provide complementary, biopsy-sparing readouts that support early detection of deleterious aging patterns and sensitive evaluation of preventive and corrective interventions in both clinical and cosmetic research setting.