A comparison of methods using optical coherence tomography to detect demineralized regions in teeth.

Optical coherence tomography (OCT) is a three- dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back-reflected from sound enamel is attenuated stronger than the signal back-reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A-scan intensity), the histogram of the A-scan intensities and three summary parameters derived from the A-scan are defined and their diagnostic potential compared. A total of 754 OCT A-scans were analyzed. The three summary parameters derived from the A-scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A-scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC = 0.98) compared to the parameters derived from the lognormal fit to the histogram of the A-scan. However, direct analysis of the A-scans or the histogram of A-scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A-scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A-scan have high capacity to discriminate between regions of caries and sound enamel.

[1]  J. Schmitt,et al.  Optical-coherence tomography of a dense tissue: statistics of attenuation and backscattering. , 1994, Physics in medicine and biology.

[2]  Mark Hewko,et al.  Precision of Raman depolarization and optical attenuation measurements of sound tooth enamel , 2007, Analytical and bioanalytical chemistry.

[3]  Peter Williams,et al.  Ex vivo detection and characterization of early dental caries by optical coherence tomography and Raman spectroscopy. , 2005, Journal of biomedical optics.

[4]  Theo Lasser,et al.  Multiple scattering in optical coherence tomography. I. Investigation and modeling. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[5]  M. Bashkansky,et al.  Statistics and reduction of speckle in optical coherence tomography. , 2000, Optics letters.

[7]  Lucila Ohno-Machado,et al.  The use of receiver operating characteristic curves in biomedical informatics , 2005, J. Biomed. Informatics.

[8]  G. Stookey,et al.  Emerging methods of caries diagnosis. , 2001, Journal of dental education.

[9]  Daniel Fried,et al.  Imaging caries lesions and lesion progression with polarization-sensitive optical coherence tomography , 2002, SPIE BiOS.

[10]  Xiao-Hua Zhou,et al.  Statistical Methods in Diagnostic Medicine , 2002 .

[11]  Tom Fawcett,et al.  Robust Classification for Imprecise Environments , 2000, Machine Learning.

[12]  Lin-P'ing Choo-Smith,et al.  Assessment of early demineralization in teeth using the signal attenuation in optical coherence tomography images. , 2008, Journal of biomedical optics.

[13]  L. A. Paunescu,et al.  Ultrahigh-resolution optical coherence tomography in glaucoma. , 2005, Ophthalmology.

[14]  Daniel Fried,et al.  Measurement of the severity of natural smooth surface (interproximal) caries lesions with polarization sensitive optical coherence tomography , 2005, Lasers in surgery and medicine.

[15]  A. Fercher,et al.  Polarization–Sensitive Optical Coherence Tomography of Dental Structures , 1999, Caries Research.

[16]  Mark Hewko,et al.  Speckle noise attenuation in optical coherence tomography by compounding images acquired at different positions of the sample , 2007 .

[17]  S R Wood,et al.  The chemistry of enamel caries. , 2000, Critical reviews in oral biology and medicine : an official publication of the American Association of Oral Biologists.

[18]  Victor S. Frost,et al.  A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  J. Girkin,et al.  A Review of Potential New Diagnostic Modalities for Caries Lesions , 2004, Journal of dental research.

[20]  David A. Jackson,et al.  Correlation of quantitative light-induced fluorescence and optical coherence tomography applied for detection and quantification of early dental caries. , 2003, Journal of biomedical optics.

[21]  Christopher D. Brown,et al.  Receiver operating characteristics curves and related decision measures: A tutorial , 2006 .