Differing self-similarity in light scattering spectra: A potential tool for pre-cancer detection

TL;DR

This study investigates the self-similar properties of light scattering spectra in normal and dysplastic cervical tissues, revealing differences that could aid in non-invasive pre-cancer detection using wavelet-based analysis.

Contribution

It demonstrates the potential of wavelet transform techniques to distinguish tissue states based on spectral self-similarity and multi-fractality, offering a novel optical diagnostic approach.

Findings

Significant differences in spectral scaling exponents between tissue types

Higher degree of multi-fractality in dysplastic tissues

Angular variation of the scaling exponent related to scatterer size distribution

Abstract

The fluctuations in the elastic light scattering spectra of normal and dysplastic human cervical tissues analyzed through wavelet transform based techniques reveal clear signatures of self-similar behavior in the spectral fluctuations. Significant differences in the power law behavior ascertained through the scaling exponent was observed in these tissues. The strong dependence of the elastic light scattering on the size distribution of the scatterers manifests in the angular variation of the scaling exponent. Interestingly, the spectral fluctuations in both these tissues showed multi-fractality (non-stationarity in fluctuations), the degree of multi-fractality being marginally higher in the case of dysplastic tissues. These findings using the multi-resolution analysis capability of the discrete wavelet transform can contribute to the recent surge in the exploration for non-invasive optical tools for pre-cancer detection.