Brain Tumour Detection and Grading Using Raman Scattering: Analogy from Semiconductors for Solving Biological Problem

Abstract

Subtle changes in Raman spectral line shape have been observed from malignant human brain cells and its possibility for being used in detection and grading of Glioma has been explored here. The latter has been developed as a result of the fact that the width of the Raman spectra is more sensitive, as compared to the peak position, to the brain tumours. The perturbations induced by the cell modification, as a consequence of the cancerous growth, may be responsible for the width's variation in the Raman spectrum due to vibrational lifetime alteration enforced at the molecular levels. A consistent cancer-induced effect on the spectral width has been observed for three different brain cells' Raman modes. Raman spectral analysis reveals that for cancerous cells, the FWHM varies up to 35% in comparison with the healthy cells. It has been established how a careful analysis of Raman spectra can help in easy detection of brain tumours. The methodology has been appropriately validated. The proposed model for malignancy detection is based on analogous behaviour of Raman spectral width variation in biological samples with semiconductor nanoparticles.

Fano-Type Wavelength-Dependent Asymmetric Raman Line Shapes from MoS2 Nanoflakes

“…It is important here to mention that the Raman line shape, and associated symmetry, is sensitive to any perturbation in the system. 47 , 48 To dig out any possible interaction present at the microscopic level, Raman spectra have been recorded using 633 nm, and Raman line shape parameters have been extracted. Figure 2 shows the spectrum (red curve), recorded using 633 nm excitation, with E 1 2g (378 cm –1 ) and A 1g (404 cm –1 ) modes having an asymmetry ratio (α R ) of 1.4 and 0.7, respectively, estimated using the formula defined above.…”

Mescoporous Nickel Titanate–Titanium Oxide Complex Material for Enhanced Energy Storage Application

“…Overall, the presence of characteristic peaks of NiO, TiO 2 and NiTiO 3 confirms the synthesis of TiO 2 and the NiTiO 3 complex. To further confirm the chemical compositional characteristics, Raman spectroscopy − is done (Figure d). The Raman spectra of m-NTTO reveal the presence of peaks at 154 and 206 cm –1 (marked by #), 310, 609, 708, and 758 cm –1 (marked by *), and 1060 cm –1 (marked by $).…”

Discovering Glioma Tissue through Its Biomarkers’ Detection in Blood by Raman Spectroscopy and Machine Learning

“…Different physical conditions [ 84 ] and concentrations of substances, such as salt, can lead to changes in the position of Raman shifts [ 85 ]. It has also been shown that, depending on the glioma grade, the tissue microenvironment affects the shift of Raman bands by up to 38% [ 86 ].…”