Diagnosis of Dental Fluorosis Using Micro-Raman Spectroscopy Applying a Principal Component-Linear Discriminant Analysis

Marco Antonio Zepeda-Zepeda,Adriana Marcela Mejía-Gózalez,María Esther Irigoyen-Camacho,Michel Picquart

doi:10.3390/ijerph182010572

Abstract

Dental fluorosis is an irreversible condition caused by excessive fluoride consumption during tooth formation and is considered a public health problem in several world regions. The objective of this study was to evaluate the capability of micro-Raman spectroscopy to classify teeth of different fluorosis severities, applying principal component analysis and linear discriminant analysis (PCA-LDA), and estimate the model cross-validation accuracy. Forty teeth of different fluorosis severities and a control group were analyzed. Ten spectra were captured from each tooth and a total of 400 micro-Raman spectra were acquired in the wavenumber range of 250 to 1200 cm−1, including the bands corresponding to stretching and bending internal vibrational modes ν1, ν2, ν3, and ν4 (PO43−). From the analysis of the micro-Raman spectra an increase in B-type carbonate ion substitution into the phosphate site of the hydroxyapatite as fluorosis severity increases was identified. The PCA-LDA model showed a sensitivity and specificity higher than 94% and 93% for the different fluorosis severity groups, respectively. The cross-validation accuracy was higher than 90%. Micro-Raman spectroscopy combined with PCA-LDA provides an adequate tool for the diagnosis of fluorosis severity. This is a non-invasive and non-destructive technique with promising applications in clinical and epidemiological fields.

Highlights

Dental fluorosis is an irreversible condition characterized by the hypomineralization of the dental structure that occurs during tooth formation
The findings of this study reveal that dental fluorosis severity can be assessed using micro-Raman spectroscopy and principal component analysis and linear discriminant analysis (PCA-Linear discriminant analysis (LDA)) models
The Principal component analysis (PCA) model fitted in this study showed that the points in 3D PCA space formed clusters according to the level of dental fluorosis, implying that the samples in each category have similar chemical compositions and structures [13]

Summary

Introduction

Dental fluorosis is an irreversible condition characterized by the hypomineralization of the dental structure that occurs during tooth formation. Children chronically exposed to high levels of fluoride in the first six years of life will develop dental fluorosis in the permanent dentition [1]. This condition affects millions of people worldwide. The mild form of fluorosis is the most prevalent [2]. The main source of fluoride is groundwater, which is frequently of geological origin. Several fluoride belts have been identified: one running through Turkey, Iraq, Iran, Afghanistan, India, Northern China, and Thailand, and another one stretching from Syria through Jordan, Egypt, Libya, Algeria, Sudan, and

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