Quantitative 3D mapping of the integrated sweat duct-microvasculature unit via fingerprint-guided photoacoustic/ultrasound microscopy.
Authors
Affiliations (4)
Affiliations (4)
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fujian Provincial Key Lab of Photonic Technology, Information Photonics Research Center, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian 350007, China.
- Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua University, Huaihua, Hunan, China.
- Affiliated Hospital of Putian University, Putian, Fujian, China.
- PROYA COSMETICS CO., LTD, China.
Abstract
Cutaneous thermoregulation relies on coordinated interactions between sweat ducts and the dermal microvasculature. However, single-modality imaging cannot simultaneously visualize and characterize this functional coupling. Here, we present a fingerprint-guided dual-modal photoacoustic/ultrasound (PA/US) microscopy framework for three-dimensional mapping of the integrated sweat duct-microvasculature unit (SDMU). This strategy combines high-frequency ultrasound with deep learning (U-Net) to extract sweat duct and fingerprint features; simultaneously, the distribution of microvasculature in PA imaging is accurately localized via structural similarity index metrix (SSIM) analysis of depth-dependent melanin. Crucially, fingerprint-guided non-rigid registration eliminates motion artifacts, enabling dynamic tracking of the identical SDMUs during physiological processes. Quantitative analysis indicated that the functional coupling of microvasculature is highly concentrated within a 75-micrometer radius around sweat ducts, and that the expansion of US-visible sweat ductal structures exhibits a strong positive correlation with microvascular recruitment. Furthermore, a physiology-informed operational dual-response criterion further revealed significant spatial heterogeneity in functional activation, thereby facilitating robust discrimination between activated and unactivated SDMUs. This study not only established the SDMU as a quantifiable functional unit for studying cutaneous thermoregulation, but also highlighted its potential as a candidate biomarker for assessing diabetes-associated neurovascular dysfunction.