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

Marco Antonio Zepeda-Zepeda, Michel Picquart, María Esther Irigoyen-Camacho and Adriana Marcela Mejía-Gózalez
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Marco Antonio Zepeda-Zepeda: Physics Department, Universidad Autónoma Metropolitana (UAM) Unidad Iztapalapa, Mexico City 09340, Mexico
Michel Picquart: Health Care Department, Universidad Autónoma Metropolitana (UAM) Unidad Xochimilco, Mexico City 04960, Mexico
María Esther Irigoyen-Camacho: Health Care Department, Universidad Autónoma Metropolitana (UAM) Unidad Xochimilco, Mexico City 04960, Mexico
Adriana Marcela Mejía-Gózalez: Oral Health Sub-Direction, Centro Nacional de Programas Preventivos y Control de Enfermedades, Secretaría de Salud, Mexico City 11800, Mexico

IJERPH, 2021, vol. 18, issue 20, 1-12

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 ? 1 , ? 2 , ? 3 , and ? 4 (PO 4 3? ). 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.

Keywords: dental fluorosis; Raman spectroscopy; principal component analysis; discriminant analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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