Fingerprint spectroscopic SRS imaging of single living cells and whole brain by ultrafast tuning and spatial-spectral learning

作     者：Lin, Haonan Lee, Hyeon Jeong Tague, Nathan Lugagne, Jean-Baptiste Zong, Cheng Deng, Fengyuan Wong, Wilson Dunlop, Mary J. Cheng, Ji-Xin 

作者机构：Department of Biomedical Engineering Department of Electrical & Computer Engineering Photonics Center Biological Design Center Boston University BostonMA02215 United States College of Biomedical Engineering and Instrument Sciences Zhejiang University Hangzhou China 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2020年

核心收录：

主　　题：Stimulated Raman scattering 

摘      要：Label-free vibrational imaging by stimulated Raman scattering (SRS) provides unprecedented insight into real-time chemical distributions in living systems. Specifically, SRS in the fingerprint region (400-1800 cm−1) can resolve multiple chemicals in a complex bio-environment using specific and well-separated Raman signatures. Yet, fingerprint SRS imaging with microsecond spectral acquisition has not been achieved due to the small fingerprint Raman cross-sections and the lack of ultrafast acquisition scheme with high spectral resolution and high fidelity. Here, we report a fingerprint spectroscopic SRS platform that acquires a distortion-free SRS spectrum with 10 cm-1 spectral resolution in 20 µs using a lab-built ultrafast delay-line tuning system. Meanwhile, we significantly improve the signal-to-noise ratio by employing a spatial-spectral residual learning network, reaching comparable quality to images taken with two orders of magnitude longer pixel dwell times. Collectively, our system achieves reliable fingerprint spectroscopic SRS with microsecond spectral acquisition speed, enabling imaging and tracking of multiple biomolecules in samples ranging from a live single microbe to a tissue slice, which was not previously possible with SRS imaging in the highly congested carbon-hydrogen region. To show the broad utility of the approach, we have demonstrated high-speed compositional imaging of lipid metabolism in living pancreatic cancer Mia PaCa-2 cells. We then performed high-resolution mapping of cholesterol, fatty acid, and protein in the mouse whole brain. Finally, we mapped the production of two biofuels in microbial samples by harnessing the superior spectral and temporal resolutions of our system. Copyright © 2020, The Authors. All rights reserved.