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<\/p>\nOver the past two decades, coherent Raman imaging has been widely applied to live-cell imaging. This allows to probe the intracellular lipid, protein, nucleic acid, and water content with high-acquisition rate and sensitivity. Multiplex coherent anti-Stokes Raman scattering (MCARS) microspectroscopy using sub-nanosecond laser pulses is now recognized as a mature and straightforward technology for label-free bioimaging, offering the high spectral resolution of conventional Raman spectroscopy with reduced acquisition time.<\/p>\n
In the framework of the challenge \u00ab\u00a0Biomaterials, biophotonics and imaging for diagnosis\u00a0\u00bb of the flagship \u00ab\u00a0Improving health through advanced diagnostics and therapies\u00a0\u00bb of the LABEX \u2211-LIM and through the thesis work of Damien Boildieu, a team of researchers developed a new methodology for hyperspectral cell imaging and segmentation using MCARS microspectroscopy, described in a publication entitled \u00ab\u00a0Coherent anti-Stokes Raman scattering cell imaging and segmentation with unsupervised data analysis\u00a0\u00bb in the journal Frontiers in Cell and Developmental Biology.<\/p>\n
The term \u00ab\u00a0hyperspectral\u00a0\u00bb means that the collected datasets contain a high number of spectral channels (one thousand, typically), unlike other imaging approaches that focus on speed rather than spectral quality.<\/p>\n
This new method combines the MCARS imaging technique with unsupervised data analysis based on multivariate curve resolution (MCR). The MCR process is implemented under the classical constraint of signal non-negativity and, in a more original way, under a new spatial constraint based on cell segmentation. The approach allows to save time, to improve the analysis of intra\/extra-cellular content and to reduce sample preparation costs.<\/p>\n
This work was carried out in collaboration with LASIRE – Laboratory of Spectroscopy for Interactions, Reactivity and Environment and the Department of Chemistry of the Faculty of Sciences of Kyushu University, Fukuoka (Japan) and is being pursued through a New-Aquitaine Region project entitled BELENOS for which this new method will be used to characterize a new bioceramic material. Another project is submitted on the development of artificial intelligence algorithms for hyperspectral MCARS data processing.<\/p>\n
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