Quantitative chemical imaging and unsupervised analysis using hyperspectral coherent anti-Stokes Raman scattering microscopy

Masia, Francesco ORCID: https://orcid.org/0000-0003-4958-410X, Glen, Adam, Stephens, Philip ORCID: https://orcid.org/0000-0002-0840-4996, Borri, Paola ORCID: https://orcid.org/0000-0002-7873-3314 and Langbein, Wolfgang Werner ORCID: https://orcid.org/0000-0001-9786-1023 2013. Quantitative chemical imaging and unsupervised analysis using hyperspectral coherent anti-Stokes Raman scattering microscopy. Analytical Chemistry 85 (22) , pp. 10820-10828. 10.1021/ac402303g

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview

Abstract

In this work, we report a method to acquire and analyze hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy images of organic materials and biological samples resulting in an unbiased quantitative chemical analysis. The method employs singular value decomposition on the square root of the CARS intensity, providing an automatic determination of the components above noise which are retained. Complex CARS susceptibility spectra, which are linear in the chemical composition, are retrieved from the CARS intensity spectra using the causality of the susceptibility by two methods and their performance is evaluated by comparison with Raman spectra. We use non-negative matrix factorization applied to the imaginary part and the non-resonant real part of the susceptibility with an additional concentration constraint to obtain absolute susceptibility spectra of independently varying chemical components and their absolute concentration. We demonstrate the ability of the method to provide quantitative chemical analysis on known lipid mixtures. We then show the relevance of the method by imaging lipid-rich stem-cell derived mouse adipocytes as well as differentiated embryonic stem cells with a low density of lipids. We retrieve and visualize the most significant chemical components with spectra given by water, lipid, and proteins segmenting the image into cell surrounding, lipid droplets, cytosol, and the nucleus, and reveal the chemical structure of the cells, with details visualized by the projection of the chemical contrast into a few relevant channels.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Biosciences Dentistry Physics and Astronomy
Subjects:	Q Science > Q Science (General) R Medicine > RK Dentistry
Publisher:	American Chemical Society
ISSN:	0003-2700
Funders:	BBSRC, EPSRC
Date of First Compliant Deposit:	30 March 2016
Last Modified:	06 Nov 2024 22:26
URI:	https://orca.cardiff.ac.uk/id/eprint/52367

Citation Data

Cited 81 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item