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Journal of Biomedical Optics

Histological validation of near-infrared reflectance multispectral imaging technique for caries detection and quantification
Author(s): Silvia Salsone; Andrew Taylor; Juliana Gomez; Iain A. Pretty; Roger Ellwood; Christian M. Zakian; Mark R. Dickinson; Giuseppe Lombardo
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Paper Abstract

Near infrared (NIR) multispectral imaging is a novel noninvasive technique that maps and quantifies dental caries. The technique has the ability to reduce the confounding effect of stain present on teeth. The aim of this study was to develop and validate a quantitative NIR multispectral imaging system for caries detection and assessment against a histological reference standard. The proposed technique is based on spectral imaging at specific wavelengths in the range from 1000 to 1700 nm. A total of 112 extracted teeth (molars and premolars) were used and images of occlusal surfaces at different wavelengths were acquired. Three spectral reflectance images were combined to generate a quantitative lesion map of the tooth. The maximum value of the map at the corresponding histological section was used as the NIR caries score. The NIR caries score significantly correlated with the histological reference standard (Spearman's Coefficient = 0.774, p<0.01). Caries detection sensitivities and specificities of 72% and 91% for sound areas, 36% and 79% for lesions on the enamel, and 82% and 69% for lesions in dentin were found. These results suggest that NIR spectral imaging is a novel and promising method for the detection, quantification, and mapping of dental caries.

Paper Details

Date Published: 6 July 2012
PDF: 11 pages
J. Biomed. Opt. 17(7) 076009 doi: 10.1117/1.JBO.17.7.076009
Published in: Journal of Biomedical Optics Volume 17, Issue 7
Show Author Affiliations
Silvia Salsone, Univ. della Calabria (Italy)
Andrew Taylor, The Univ. of Manchester (United Kingdom)
Juliana Gomez, The Univ. of Manchester (United Kingdom)
Iain A. Pretty, The Univ. of Manchester (United Kingdom)
Roger Ellwood, The Univ. of Manchester (United Kingdom)
Christian M. Zakian, The Univ. of Manchester (United Kingdom)
Mark R. Dickinson, The Univ. of Manchester (United Kingdom)
Giuseppe Lombardo, Univ. della Calabria (Italy)


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