Motion-tolerant 3D volumetric multimodality microscopy imaging of human skin with subcellular resolution and extended field-of-view
Abstract The skin, the body’s largest organ, has a heterogeneous structure with various cell types and tissue layers. In vivo noninvasive 3D volumetric imaging with multi-contrast, high resolution, a large field-of-view (FOV), and no-motion artifacts is crucial for studying skin biology and diagnosi...
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Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
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Series: | Communications Biology |
Online Access: | https://doi.org/10.1038/s42003-025-07614-x |
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Summary: | Abstract The skin, the body’s largest organ, has a heterogeneous structure with various cell types and tissue layers. In vivo noninvasive 3D volumetric imaging with multi-contrast, high resolution, a large field-of-view (FOV), and no-motion artifacts is crucial for studying skin biology and diagnosing/evaluating diseases. Traditionally high-resolution in vivo skin microscopy methods capture images in the en-face (xy) plane parallel to the skin surface but are affected by involuntary motion, particularly during large-area volumetric data acquisition using xy-z mosaicking. In this work, we developed an xz-y imaging method that acquires images in the vertical (xz) plane and extends the FOV by moving the skin laterally along the y-direction. This approach is conceived based on our observation that involuntary skin movements are mostly along the vertical direction. Combined with a unique motion correction method, it enables 3D image reconstruction with subcellular resolution and an extended FOV close to a centimeter (8 mm). A multimodality microscopy system using this method provides simultaneous reflectance confocal, two-photon excited fluorescence, and second harmonic generation imaging, enabling multi-contrast capabilities. Using this system, we captured histology-like features of normal skin, vitiligo, and melanoma, demonstrating its potential for in vivo skin biology studies, clinical diagnosis, treatment planning and monitoring. |
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ISSN: | 2399-3642 |