Shortwave-infrared meso-patterned imaging enables label-free mapping of tissue water and lipid content

Water and lipids are key participants in many biological processes, but there are few non-invasive methods that provide quantification of these components in vivo, and none that can isolate and quantify lipids in the blood. Here we develop a new imaging modality termed shortwave infrared meso-patter...

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Veröffentlicht in:Nature communications 2020-10, Vol.11 (1), p.5355-5355, Article 5355
Hauptverfasser: Zhao, Yanyu, Pilvar, Anahita, Tank, Anup, Peterson, Hannah, Jiang, John, Aster, Jon C., Dumas, John Paul, Pierce, Mark C., Roblyer, Darren
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Sprache:eng
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Zusammenfassung:Water and lipids are key participants in many biological processes, but there are few non-invasive methods that provide quantification of these components in vivo, and none that can isolate and quantify lipids in the blood. Here we develop a new imaging modality termed shortwave infrared meso-patterned imaging (SWIR-MPI) to provide label-free, non-contact, spatial mapping of water and lipid concentrations in tissue. The method utilizes patterned hyperspectral illumination to target chromophore absorption bands in the 900–1,300 nm wavelength range. We use SWIR-MPI to monitor clinically important physiological processes including edema, inflammation, and tumor lipid heterogeneity in preclinical models. We also show that SWIR-MPI can spatially map blood-lipids in humans, representing an example of non-invasive and contact-free measurements of in vivo blood lipids. Together, these results highlight the potential of SWIR-MPI to enable new capabilities in fundamental studies and clinical monitoring of major conditions including obesity, cancer, and cardiovascular disease. Quantifying lipid and water content in tissues non-invasively is difficult, and no method exists to quantify lipids in blood non-invasively. Here the authors develop an imaging approach called shortwave infrared meso-patterned imaging (SWIR-MPI) to detect and spatially map tissue water and lipids in preclinical models.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-19128-7