Label-free imaging of human cells: algorithms for image reconstruction of Raman hyperspectral datasets

Abstract

Raman microspectroscopy-based, label-free imaging methods for human cells at sub-micrometre spatial resolution are presented. Since no dyes or labels are used in this imaging modality, the pixel-to-pixel spectral variations are small and multivariate methods of analysis need to be employed to convert the hyperspectral datasets to spectral images. Thus, the main emphasis of this paper is the introduction and comparison of a number of multivariate image reconstruction methods. The resulting Raman spectral imaging methodology directly utilizes the spectral contrast provided by small (bio)chemical compositional changes over the spatial dimension of the sample to construct images that can rival fluorescence images in terms of spatial information, yet without the use of any external dye or label.

Molecular pathology via IR and Raman spectral imaging

“…One constraint in VCA is that the concentrations, or abundances, of the endmembers are non-negative. Further details have been given elsewhere [61,62].…”

Cellular discrimination using in vitro Raman micro spectroscopy: the role of the nucleolus

“…[11][12][13] As an optical microscopic technique, Raman micro spectroscopy also has the potential to probe the molecular structure on a cellular and subcellular level. 14,15 In comparison to Infrared absorption spectroscopy; Raman micro spectroscopy offers the possibility to study biological matrices in an aqueous environment due to the weak contribution from water. 16,17 Thus, the potential applications extend beyond disease diagnostics to the label free in vitro screening of cytological processes, such as drug or nanoparticle uptake and mechanisms of interaction, and toxicology.…”

Spectral pre and post processing for infrared and Raman spectroscopy of biological tissues and cells

“…A good example of KMCA in Raman spectroscopy is shown in the study by Dorney et al [12], in which it was used to identify regions in the Raman dataset which correspond to polystyrene nanoparticles, and differentiate them from neighbouring cytoplasm, as well as the nucleus and nucleolus ( Figure 5). Many other examples of KMCA as a spectroscopic imaging reconstruction technique can be found in the investigation of a wide range of samples including tissue sections [78], cells [12,79,80] and in the analysis of human skin [26,81]. While this method has been shown to be useful in partitioning spectra into clusters, it is important to highlight that the method is not without certain pitfalls.…”

“…Therefore, by analysing the C centroid spectrum it is possible to extract chemical information which describes each reconstructed image. FCM has seen some usage in Raman spectroscopy although primarily as an imaging method [79,80].…”

“…diseased and non-diseased [69]. It has also been used to reconstruct images [79,80] i.e. a variance plot based on the loadings plot.…”