Water, Collagen, and Lipid Content in the Human Skin and Muscles Assessed with Near‐Infrared Diffuse Reflectance Spectroscopy and Multi‐Spectral Optoacoustic Tomography

• Published in: Advanced science p. e05619
• Main Authors: Davydov, Denis, Kurnikov, Alexey, Subochev, Pavel, Budylin, Gleb, Fadeev, Nikolay, Filippov, Ivan, Mokrysheva, Natalia, Urusova, Liliya, Razansky, Daniel, Shirshin, Evgeny
• Format: Journal Article
• Language: English
• Published: Germany 13.08.2025
• Subjects: collagen; lipids; diffuse reflectance spectroscopy; muscles; multi‐spectral optoacoustic tomography
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202505619

Infrared spectroscopy can quantify individual body components such as lipids, water, and proteins, but extending it to a comprehensive assessment of overall body composition is hampered by high variability and optical heterogeneity of biological tissues. Here, a theoretical and experimental strategy merging multi‐spectral optoacoustic tomography (MSOT) and diffuse reflectance spectroscopy (DRS) is introduced to characterize skin and subcutaneous tissue composition in the near‐infrared range. Water, lipids, and collagen exhibit distinct absorption peaks, with lipids demonstrating significantly higher absorption than collagen at comparable mass concentrations. Diminished lipid absorption in subjects with thin hypodermis allows the DRS method to detect distinct collagen band at 910 nm, whose magnitude correlates with the muscle mass, as confirmed by bioimpedance analysis. Conversely, strong lipid peak at 930 nm in subjects with pronounced hypodermis overshadows collagen signals by an order of magnitude, making DRS characterization insufficient. MSOT overcomes this limitation by offering high‐resolution depth‐resolved 3D imaging to accurately delineate the dermis, hypodermis, and muscle layers in vivo and quantify each chromophore's contribution individually. The findings demonstrate the complementary capabilities of MSOT and DRS for molecularly specific, noninvasive body composition analysis, potentially enhancing diagnostic approaches for a number of conditions, such as obesity and sarcopenia.