Chemoselective imaging of mouse brain tissue via multiplex CARS microscopy

Abstract

The fast and reliable characterization of pathological tissue is a debated topic in the application of vibrational spectroscopy in medicine. In the present work we apply multiplex coherent anti-Stokes Raman scattering (MCARS) to the investigation of fresh mouse brain tissue. The combination of imaginary part extraction followed by principal component analysis led to color contrast between grey and white matter as well as layers of granule and Purkinje cells. Additional quantitative information was obtained by using a decomposition algorithm. The results perfectly agree with HE stained references slides prepared separately making multiplex CARS an ideal approach for chemoselective imaging.

Multiplex coherent anti-Stokes Raman scattering microspectroscopy of brain tissue with higher ranking data classification for biomedical imaging

“…The image contrast was obtained using the two step approach consisting of Raman extraction and PCA. 8 The color coding refers to spectral differences within the scanned area. The scores arising from PCA were associated with different colors, so tumor tissue appears in green and normal tissue in red.…”

“…7 However, in a situation where the Raman spectrum of each component is not known a priori, a different approach must be applied. In this regard, a multistep analysis 8 of CARS data can be implemented by combining Raman reconstruction algorithms, 9 principal component analysis (PCA), and decomposition of the measured data using pure spectra. This approach can reveal quantitative information without any previous information.…”

“…This approach can reveal quantitative information without any previous information. 8 This method is superior to an univariate approach since additional molecular features beyond single spectral intensity are analyzed, visualized, and matched to standard histological assessment of the brain tissues. Nevertheless, a PCA-based type of data analysis is limited to spectral differences within the individual data sets.…”

Fast single‐beam‐CARS imaging scheme based on in silico optimization of excitation phases

“…Additionally, making this technique even more attractive, an intrinsic local oscillator can be created, allowing for the determination of amplitude and phase of molecular susceptibilities, [12,13] without the need of any post-processing to disentangle resonant and nonresonant contributions. [14][15][16][17] SB-CARS with shaped femtosecond laser pulses, however, still requires some sort of scanning of the optical phase to retrieve chemical information of the sample or to obtain image contrast. A scan of the optical phase at a fixed sample position during a measurement not only slows down the data acquisition speed but also increases the photon load, which is often not compatible with imaging of biochemical samples with low damage thresholds.…”

Fiber-optic Raman sensing of cell proliferation probes and molecular vibrations: Brain-imaging perspective

“…9 While most of the recently developed protocols of neurophotonics rely on the fluorescence response from activated brain regions, a wealth of unique chemically specific information on neuronal activity on the molecular level can be obtained with the use of Raman scattering. Coherent Raman microspectroscopy 13,14 has already been shown [15][16][17][18] to offer a tremendous potential for high-resolution chemically selective brain imaging. A serious difficulty encountered when fiber probes are used to detect the Raman response from a biotissue is related to the Raman and fluorescent background from the fiber itself, which dramatically reduces the sensitivity of Raman detection.…”