Multispectral near-IR reflectance imaging of simulated early occlusal lesions: variation of lesion contrast with lesion depth and severity

Abstract

Background and objectives: Early demineralization appears with high contrast at near-IR wavelengths due to a 10- to 20-fold difference in the magnitude of light scattering between sound and demineralized enamel. Water absorption in the near-IR has a significant effect on the lesion contrast and the highest contrast has been measured in spectral regions with higher water absorption. The purpose of this study was to determine how the lesion contrast changes with lesion severity and depth for different spectral regions in the near-IR and compare that range of contrast with visible reflectance and fluorescence.

Materials and methods: Forty-four human molars were used in this in vitro study. Teeth were painted with an acid-resistant varnish, leaving a 4 mm × 4 mm window on the occlusal surface of each tooth exposed for demineralization. Artificial lesions were produced in the unprotected windows after 12-48 hours exposure to a demineralizing solution at pH 4.5. Near-IR reflectance images were acquired over several near-IR spectral distributions, visible light reflectance, and fluorescence with 405-nm excitation and detection at wavelengths >500-nm. Crossed polarizers were used for reflectance measurements to reduce interference from specular reflectance. Cross polarization optical coherence tomography (CP-OCT) was used to non-destructively assess the depth and severity of demineralization in each sample window. Matching two-dimensional CP-OCT images of the lesion depth and integrated reflectivity were compared with the reflectance and fluorescence images to determine how accurately the variation in the lesion contrast represents the variation in the lesion severity.

Results: Artificial lesions appear more uniform on tooth surfaces exposed to an acid challenge at visible wavelengths than they do in the near-IR. Measurements of the lesion depth and severity using CP-OCT show that the lesion severity varies markedly across the sample windows and that the lesion contrast in the visible does not accurately reflect the large variation in the lesion severity. Reflectance measurements at certain near-IR wavelengths more accurately reflect variation in the depth and severity of the lesions.

Conclusion: The results of the study suggest that near-IR reflectance measurements at longer wavelengths coincident with higher water absorption are better suited for imaging early caries lesions.

Keywords: demineralization; dental caries; enamel; near-IR imaging; polarization.

Fig. 1

Near-IR reflectance (BP1460 filter) image of a sample from group 4 (most severe). The 3×3 mm area centered in the 4×4 mm window exposed to demineralization is demarcated in green and labeled 'A'. The polygon region outlined in blue and labeled 'B' represents the sound reference area.

Fig. 2

The mean integrated reflectivity ± the standard deviation (s.d.) for adjusted groups 1–4.

Fig. 3

Set of lesion images for one sample from group 4 (most severe). (A) visible reflectance color image, (B) visible reflectance grayscale, (C) fluorescence (405/500-nm), (D) LP1100, (E) LP1200, (F) LP1300, (G) LP1400, (H) LP1500, (I) BP1300, (J) BP1377, (K) BP1460, (L) BP1550.

Fig. 4

Comparison of dry (left) and wet (right) images of a group 4 lesion. (A–B) Visible, (C–D) fluorescence (405/500), (E–F) BP1460 and (G–H) BP1300.

Fig. 5

Plot of the measured lesion contrast for dry samples vs. the mean lesion depth determined using OCT. Data for visible reflectance, QLF, and near-IR reflectance with BP1300, BP1460 and LP1500 are shown along with the best fit linear regression lines.

Fig. 6

Plot of the measured lesion contrast for wet samples vs. the mean lesion depth determined using OCT. Data for visible reflectance, QLF, and near-IR reflectance with BP1300, BP1460 and LP1500 are shown along with the best fit linear regression lines.

Fig. 7

Maps of the calculated lesion depth for a group 4 sample. (A) Lesion depth from OCT, (B) Visible depth composition image from digital microscope, (C) Lesion depth from near-IR (BP1460), and (D) Lesion depth from visible. Confusion maps of lesion depth comparing OCT lesion depths vs. near-IR (BP1460) (E) and visible (F). Green is true, blue is underestimate and red is overestimate.

Fig. 8

Maps of the integrated reflectivity with lesion depth (ΔR) for a group 1 sample. (A) Lesion depth from OCT, (B) Visible reflectance image, (C) Lesion integrated reflectivity with lesion depth from near-IR (BP1460), and (D) from visible. Confusion maps of lesion depth comparing OCT depths vs. near-IR (BP1460) (E) and visible (F). Green is true, blue is underestimate and red is overestimate.

Fig. 9

Stacked bar graph showing accuracy of lesion depth assessment for each lesion group for visible and near-IR (BP1460) reflectance based on point by point comparison with the lesion depth determined using OCT. Green is true, blue is underestimate and red is overestimate.

Fig. 10

Stacked bar graph showing accuracy of lesion severity assessment for each lesion group for visible and near-IR (BP1460) reflectance based on point by point comparison with the integrated reflectivity with lesion depth (ΔR) determined using OCT, Green is true, blue is underestimate and red is overestimate.