Characterizing breast cancer tissues through the spectral correlation properties of polarized fluorescence

Abstract

We study the spectral correlation properties of the polarized fluorescence spectra of normal and cancerous human breast tissues, corresponding to patients belonging to diverse age groups and socioeconomic backgrounds. The emission range in the visible wavelength regime of 500 to 700 nm is analyzed, with the excitation wavelength at 488 nm, where flavin is one of the active fluorophores. The correlation matrices for parallel and perpendicularly polarized fluorescence spectra reveal correlated domains, differing significantly in normal and cancerous tissues. These domains can be ascribed to different fluorophores and absorbers in the tissue medium. The spectral fluctuations in the perpendicular component of the cancerous tissue clearly reveal randomization not present in the normal channel. Random matrix-based predictions for the spectral correlations match quite well with the observed behavior. The eigenvectors of the correlation matrices corresponding to large eigenvalues clearly separate out different tissue types and identify the dominant wavelengths, which are active in cancerous tissues.

Autofluorescence and diffuse reflectance spectroscopy and spectral imaging for breast surgical margin analysis

“…Autofluorescence and diffuse reflectance spectroscopy have been researched extensively as a diagnostic tool for discriminating among normal, malignant, and/or benign breast tissues [10][11][12][13][14][15][16][17][18][19][20][21][22]. Some of the most extensive recent work has been performed by Ramanujam and coworkers, who have used numerous approaches to discriminate breast tissues with autofluorescence and/or diffuse reflectance, including the use of multiple excitation wavelengths [23,24], multiple source-detector fiber separations [25], and Monte Carlo-based extraction algorithms [26][27][28].…”

Comparative study of laser and lamp fluorescence of cancer and normal tissue through wavelet transform and singular value decomposition

“…Previously the correlation properties of the polarized fluorescence using laser as excitation source has been studied by us. 12,13 The spectral fluctuations in the perpendicular channel showed the randomization effect of the tissue medium for the cancerous samples, earlier indicated through wavelet domain analysis 14,15 .In both parallel and perpendicular channels strong spectral correlated domains reveal information about wavelength ranges showing significant differences between cancer and normal tissues.…”

EEG Epilepsy Seizure Signal Characterization through theories of Random Matrix Analysis

“…This formed our initial 100 x 4096 data matrix for correlation matrix study. We had taken those obtained matrixes of each data set A, B and E to study the multifractal properties for EEG signal characterization using Random matrix theory (RMT) [20][21][22][23][24] for analysis purpose which could be described as below:…”

“…It is witnessed that random matrix theory approach for statistical analysis of cross-correlation matrix has brought attention of researcher to analyze natural time series data especially from financial and biological systems [20][21][22][23][24][25][26]. The purpose of this paper is to propose a real time analysis technique to characterize epilepsy patients with seizure from healthy human or patients who achieved complete seizure control using EEG signals that are measured for different recordings simultaneously making a high dimensional data for analysis using the random matrix theory.…”