Spectral region optimization for Raman-based optical diagnosis of inflammatory lesions

TL;DR

This study uses FT-Raman Spectroscopy and statistical analysis to distinguish inflammatory fibrous hyperplasia from normal tissue, identifying an optimal spectral region that improves diagnostic accuracy for inflammatory lesions.

Contribution

The paper identifies the spectral region 530-580 cm$^{-1}$ as optimal for differentiating inflammatory tissue from normal tissue using Raman spectroscopy, enhancing diagnostic precision.

Findings

High discrimination sensitivity (95%) and specificity (100%) achieved.

Spectral region 530-580 cm$^{-1}$ is optimal for classification.

Vibrational modes of collagen amino acids are key biomarkers.

Abstract

FT-Raman Spectroscopy was applied to identify biochemical alterations existing between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa. One important implication of this study is related to the cancer lesion border. In fact, the cancerous normal border line is characterized by the presence of inflammation and its correct discrimination would increase the accuracy in delimiting the lesion frontier. Seventy spectra of IFH from 14 patients were compared to 30 spectra of normal tissue from 6 patients. The statistical analysis was performed with Principal Components Analysis and Soft Independent Modeling Class Analogy methodologies. After studying several spectral ranges it was concluded that the best discrimination capability (sensibility of 95% and specificity of 100%) was found using the 530 to 580 cm$^{-1}$ wavenumbers. The bands in this region are related to vibrational modes of Collagen aminoacids Cistine, Cysteine, and Proline and their relevant contribution to the classification probably relies on the extracellular matrix degeneration process occurring in the inflammatory tissues.