*4.1. Quantitative Assessment Based on Lesion Depths*

During the demineralization process, the OCT image contrast of caries is formed as the mineral content (MC) of the enamel decreases and the optical properties change [48]. Therefore, lesion depths determined by OCT images can be used to quantify early enamel caries. First, the filters are applied to remove speckle noise and enhance contrast for the OCT B-scan image, then the A-scan in the region of interest (ROI) is searched for the first pixel that exceeds the intensity threshold point, and the distance from the enamel surface to this pixel is taken as the lesion depth. The mean lesion depth is obtained by calculating the lesion depth for each A-scan in the ROI. It has been suggested to select *e*−<sup>2</sup> times the peak intensity as the signal intensity threshold. The lesion depth measured by OCT is proportional to the demineralization time [49–53]. Le et al. [49] investigated bovine enamel caries lesions with 1310-nm PS-OCT. Figure 1 shows the PS-OCT B-scan of one of the bovine enamel blocks in the perpendicular axis. It can be seen that the lesion depth increases with the enhancement of the back-scattered intensity around the enamel surface, and the lesion severity increases. The results show the mean lesion depths varies significantly from 10 to 75 μm for demineralization over 0–4 days. Moreover, there is strong correlation (r = 0.85) between the mean depth of lesion measured by PS-OCT and polarized light microscopy (PLM). Jones et al. [50] prepared artificial caries on the occlusal surfaces by using a 14-day pH cycle model and detected them with PS-OCT and digital microradiography (DM). It was found that the image contrast between the sound and lesion area in the perpendicular axis was stronger than that in the parallel axis. The mean lesion depth of caries lesions calculated from the perpendicular axis images of the ten teeth was 150 ± 30 μm, which was highly

correlated with the lesion depths obtained from DM (r = 0.811). Meng [51] and Yao et al. [52] observed an approximately linear relationship between lesion depth and demineralization time using TD-OCT. Park et al. [53] established assessment criteria for OCT using lesion depths, and conducted a concordance study between OCT and light microscopy using ex vivo teeth, which showed moderate concordance (k = 0.54, *p* ≤ 0.001) with no significant difference (*p* = 0.25). Then, smooth surface in vitro and in vivo evaluations were performed using OCT and the International Caries Detection and Assessment System (ICDAS). The extent of caries was seen to vary considerably within each ICDAS category using OCT, which could effectively complement the visual assessment with ICDAS. Yavuz et al. [54] utilized 840-nm SD-OCT to assess the remineralization of artificial enamel caries. The results showed there was a significant reduction in the lesion depth after remineralization, 311.80 (344.38), 320.10 (244.36) and 312.70 (203.80) μm for the three remineralization agents, respectively. The measured lesion depth was also compared with a surface microhardness analysis but there was no correlation between the two.

**Figure 1.** PS-OCT B-scan of bovine enamel in the perpendicular axis. D0 represents the sound area and D1–D4 represent areas demineralized for 1–4 days. A red-white-blue color chart was used, with red indicating strong reflectivity and blue indicating low reflectivity. This figure was adapted from [49].

Lesion depth is a common quantitative index used in early caries studies. The main challenge for its calculation is the difficulty in selecting an intensity threshold as the end point of a lesion, as the range of OCT images is relatively high. The method of selecting *e*−<sup>2</sup> times the peak intensity as the signal intensity threshold does not always work effectively [55]. Le et al. [49] used edge-finding algorithms based on this method to measure lesion depth. Other studies designed algorithms to determine the lesion boundary in the image and obtained lesion depth [51,56,57]. A summary of the above research results is shown in Table 1.

**Table 1.** Results of quantifying enamel caries with lesion depths.



**Table 1.** *Cont.*


**Table 1.** *Cont.*

Lesion depths of caries can visually indicate the severity of caries to some extent. However, they can only reflect part of the characteristics of the initial stage of enamel lesions, as the amount of mineral loss may be different in a certain depth range [58]. Furthermore, there is a lack of solid criteria for determining the cut-off point to define lesion depth.

#### *4.2. Quantitative Assessment Based on Reflectivity*

Many studies have used reflectivity for the quantitative assessment of early caries, since the reflectivity of caries lesions can be obtained directly from OCT signals. A commonly used quantitative index related to reflectivity is the integrated reflectivity for caries detection.

A line profile for each lesion depth is taken from B-scans, and the integrated reflectivity (Δ*R*, dB × μm) can be calculated by integrating the reflectivity from the enamel surface to various depths [50]. The observed optical depth should be divided by the enamel refraction index (n = 1.63) to determine the real lesion depth when using the line profile.

Most studies have confirmed that integrated reflectivity increases after demineralization and decreases after remineralization [49,50,57,59,60]. Le et al. [49] utilized a fixed depth algorithm and an edge detection algorithm to calculate integrated reflectivity. In the first algorithm the integration was performed to a fixed depth that needed to be greater than the maximum lesion depth, while the second algorithm could obtain the depth of the lesion. The results showed both algorithms were able to detect the difference in demineralization from 0 to 4 days, except that the fixed depth algorithm yielded a higher integrated reflectivity. Jones et al. [50] calculated the mean integrated reflectivity of artificial caries prepared by applying a 14-day pH cycle model based on the perpendicular axis PS-OCT images, and the result was 450 ± 110 arbitrary units. Meanwhile, it was demonstrated that the integrated reflectivity calculated by PS-OCT was linearly correlated with the relative mineral loss determined by DM (r = 0.755). Nee et al. [59] detected demineralization around adhesive-bound orthodontic brackets in vivo using CP-OCT for a period of 1 year and acquired 2D projection images of Δ*R* with automated algorithms. The results indicated Δ*R* for both adhesives increased remarkably with time, varying in the range from 10.2 (10.5) to 29.7 (9.4) dB × μm. PS-OCT was applied to monitor the process of remineralization of caries using an acid remineralization model by Kang et al. [60]. There were significant alterations in the integrated reflectivity of the lesion region after remineralization, from 257 ± 60.2 to 168 ± 58.5 dB × μm.

Amaechi et al. [61] scanned demineralized bovine teeth using 850-nm OCT and demonstrated that Δ*R* of the enamel reduced with the time of demineralization. They proposed the percentage reflectivity loss (*R*%) as a quantitative index as follows:

$$R\_{\%} (\text{dB} \times \text{mm}) = \frac{(R\_{\text{sound}} - R\_{\text{deminalized}})}{R\_{\text{sound}}} \times 100\% \tag{1}$$

where *Rsound* is the reflectivity of sound enamel and *Rde*min*eralized* is the reflectivity of enamel lesion.

The results showed that *R*% increased from 54.0 ± 11.27 to 86.64 ± 7.57 dB × μm with demineralization time. In a follow-on study it was demonstrated that *R*% was linearly correlated with both the mineral loss determined by transverse microradiography (TMR) (*r* = 1.00) [62] and the percentage of fluorescence loss calculated (Δ*Q*) by QLF (*R*% = 45.56 + Δ*Q*,*r* = 0.963) [63]. However, *R*% is rarely applied. A summary of the above research results is shown in Table 2.


**Table 2.** Results of quantifyin0p-[g enamel caries with reflectivity.

three 4-day periods


**Table 2.** *Cont.*

In addition, other researchers have used the mean relative reflectivity (mRR) proposed in retinal OCT imaging to assess fissure caries by using 1325-nm SS-OCT [64]. The mRR is calculated from the difference between the fissure area signal and sound enamel signal. Although the mRR of demineralized fissures were at least 6 times higher than those of sound fissures at 250, 500 and 1000 μm depths beneath the surface, the mRR was unable to accurately describe lesion mineral density (*rs* = −0.31).

In summary, the integrated reflectivity of enamel lesion calculated by OCT is linearly correlated with mineral loss. Most results confirm that the integrated reflectivity of enamel increases after demineralization, but individual studies show the opposite. Researchers often use the integrated reflectivity in combination with lesion depth to evaluate the lesion severity. However, the calculation of the integrated reflectivity suffers from similar problems to the lesion depth calculation.
