Study on near-infrared diffused reflectance imaging for early caries detection

doi:10.21203/rs.3.rs-3115824/v1

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Study on near-infrared diffused reflectance imaging for early caries detection

https://doi.org/10.21203/rs.3.rs-3115824/v1

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Objective: Dental caries is one of the most prevalent chronic diseases in the world. Early detection can significantly enhance therapeutic outcomes and lessen the need for intrusive procedures. This research mainly focuses on the viability of near-infrared diffuse reflectance imaging for early caries detection.

Methods: According to the theory of diffuse reflection imaging in tissue optics, a near-infrared diffuse reflectance imagery named new-NIR was established. In order to confirm the performance of the new-NIR, 54 areas of interest in 18 teeth were investigated simultaneously by the new-NIR, DIAGNOcam, which is a comparative diagnostic technique and visual inspection by a skilled dentist as the gold standard. The performance of the new-NIR was assessed using the Spearman grade correlation coefficient.

Results:Compared with the gold standard, the sensitivity, specificity and accuracy of the new-NIR were 0.806, 0.870 and 0.833, respectively. The sensitivity, specificity and accuracy of the DIAGNOcam were 0.871, 0.913, and 0.889, respectively.

Conclusion: This technology is simple to use, non-contact, and feasible in the early stages of suggesting tooth enamel caries. Future studies will combine near-infrared diffuse reflectance imaging with an automatic classification algorithm to provide family-based oral health monitoring tools to prevent caries.

Early dental caries

near-infrared light

reflectance imaging

Caries is one of the three main non-communicable illnesses that must be prevented and treated. The 2022 Global State of Oral Health Report estimates that 2.5 billion people worldwide suffer from caries. Nevertheless, the demineralization would be reversible if the teeth could be treated in the earlier caries stage(1, 2). Therefore, early diagnosis and detection are crucial for treating and controlling dental caries(3, 4). Visual inspection, dental probing, and X-ray examination are still the most widely used clinical diagnostic techniques for clinical caries detection(5, 6). It is easy, however, to ignore the mild degree of carious lesions, particularly the occult carious lesions on the adjacent side of the teeth, which can lead to false negative misjudgment(7). In addition, X-ray examination has ionizing radiation, which cannot be detected often in the short term, especially not for children and pregnant women(8). Because preventive and less invasive treatments can reduce the need for restorative therapy, the early diagnosis of proximal caries has drawn a lot of interest(9).

Sound enamel is highly transparent in the near-infrared (NIR) range, offering possibilities to develop new non-ionizing and safe optical approaches for detecting and imaging early dental caries without the drawbacks of ionizing radiation(10). Katrin reported that 780 nm NIR reflectometry has clinical value for the early diagnosis of occlusal, buccal, and orofacial caries of molars and premolars(11). William et al. measured that reflections at longer near-infrared wavelengths produce higher contrast for early caries than other near-infrared and visible wavelengths(12). Currently, DIAGNOcam and VistaCam iX HD are two marketed NIR caries detection tools. The near-infrared transillumination-based DIAGNOcam can identify proximal enamel lesions and demonstrate the degree of enamel degradation(13). However, the DIAGNOcam have some disadvantages. For example, the laser diode with a wavelength of 780 nm used by DIAGNOcam as its illumination source produces a grainy structure of laser speckles in the image that is recorded. The VistaCam iX HD, a caries diagnostic device based on near-infrared reflection, uses 850 nm light to illuminate tooth enamel and is scattered by caries lesion tissue in tooth enamel and dentin. Caries lesions and light scattered from dentin appear bright, while intact enamel appears black(14, 15). The VistaCam iX HD requires VistaSoft software (Durr Dental) on a computer for analysis and diagnosis, increasing the inconvenience of carrying. In addition, both types of equipment are expensive and require professional operation and maintenance to ensure proper use and safety. Thus, a low-cost tool that can clearly display the hard-to-diagnose Caries site at an early stage is required.

In our previous research, based on hyperspectral imaging, we found that pigments and early caries on the tooth surface can be effectively identified in the near-infrared band(16). Therefore, a novel near-infrared diffuse reflection imaging device, new-NIR, was designed for detecting early caries. The new-NIR has no contact with the teeth and has a good price advantage. In addition, the new-NIR is portable and easy to operate, allowing less experienced inspectors to achieve similar or higher accuracy than experts. This paper evaluates the feasibility of new-NIR in detecting early tooth decay and points to future directions.

2.1. Principle

Demineralization is the process of carious formation, the excessive loss of inorganic salts from tooth enamel, resulting in irreversible demineralization. The lost inorganic material is filled with water or air to form an optical scattering center(17). The diseased dental tissue is typically more uniform in near-infrared and polarized optical microscope images than microradiography images. It indicated a nonlinear relationship between mineral loss and scattering coefficient. In other words, under a slight demineralization, the light scattering increases significantly, and the lesion worsens, but the amplitude of the increase in scattering decreases(18). In addition, the optical property measurements during the longitudinal development of early artificial demineralization suggested a similar rapid exponential increase in optical scattering during initial lesion development, followed by a more gradual increase in scattering as the lesion severity increases(19).

In the visible wavebands, the absorption of caries is small, and the scattering is larger, making the carious site shows low reflection. Pigmented areas are strongly absorbed in the visible wavebands, making them appear as black or yellow-brown patches. So, it is difficult to distinguish between caries and pigmented areas in the visible wavebands. However, the absorption of teeth in the near-infrared wavebands is weakened, mainly showing a state of strong scattering. The tooth tissue with pigment attachment is smooth, and the scattering effect of light is similar to that of a healthy tooth surface and much smaller than that of the carious areas. Due to the demineralization of tooth tissue, the structure of enamel caries is uneven, the number of hydroxyapatite crystals decreases, and the number of pores increases. Then the light scattering increases in the pores, so the reflected light captured by optical lens with limited aperture is reduced, and the image shows low brightness characterized(16, 20). Because the increased intensity of local light scattering at the carious lesion, which makes the caries appear brighter in NIR reflection images than healthy peripheral enamel(17, 21). The sound tooth enamel, which is transparent to light, appears dark in the image. But carious lesions, which scatter and reflect near-infrared light, appear brighter against the surrounding tooth enamel's dark background.

In conclusion, the spectral reflectance of carious and pigmented areas of teeth showed slight variation in the visible wavebands and could not be identified by the naked eye. The spectral reflectance of the carious areas was much lower than that of the healthy and pigmented areas in the near-infrared wavebands. Because of the increased light scattering, the enlarged pores, and the decreased reflection. Then the images show significant differences, indicating that early caries can be distinguished from pigmentation in the near-infrared wavebands and that near-infrared diffuse reflectance method can effectively diagnose early caries.

2.2. System design

The designed new-NIR imager was built based on near-infrared diffused reflection, and the 780 nm incident light was selected as the light source after testing. As a portable miniaturized device, it combines APP software in a smartphone or a Personal Access Device (PAD) and hardware equipment, which consists of three parts: an optical imaging system, a data transmission system and a power management module.

Based on the previous research(22), the designed system is shown in Fig. 1. The light source selects four near-infrared LEDs (780 ± 20 nm) in 0805 package and four white LEDs (broad spectrum, 6500 K), placed around the lens of the complementary metal-oxide semiconductor (CMOS) camera, emits high-brightness light illumination on the tooth surface. And the diffused light on the tooth surface is received by the lens and imaged on the CMOS camera. The CMOS camera converts optical signals into digital signals, obtains and stores and transmits image data. Finally, the image processing chip FH8610 (Fullhan, China) processes the images(23). The WIFI module (88w8801, USA) is used to transport the data gathered by the front-end to the APP software. The APP software can control the hardware to switch between the white and near-infrared LED channels and take the teeth photos.

3.1. Sample preparation

18 extracted human teeth (molars and premolars) with varying degrees of natural pathology and no degree of decay involving dentin were obtained from the Department of Dentistry, Shanghai's Ninth People's Hospital. According to the widely accepted ICDAS II standard, teeth with a caries index of zero to three were included in this study to study the early difficult-to-diagnose carious lesions. After the soft tissue removal, all the teeth were stored in a separate container of 0.9% sodium chloride solution to maintain sufficient moisture and a sterile environment. Any excess moisture was removed by wiping lightly with a cotton swab when the sample images were taken.

There are 54 areas of interest in 18 teeth, including sound, carious and pigmented areas. This study excludes tooth surfaces that have been restored and severe lesions. And there were no structural alterations or other types of damage besides caries, which could be seen to have fully developed roots.

3.2. Classification method

Two experienced dental clinicians from the Department of Dentistry, Shanghai's Ninth People's Hospital, directly evaluated and classified the near-mid-surface and far-mid-surface of each sample according to the International Caries Detection and Evaluation System ICDAS II. The classification results were regarded as the gold standard.

The DIAGNOcam classification standard refers to the digital bitewing radiography classification as D0-D2, where D0 indicates that the surface is intact without shadow, D1 indicates that the caries is located in the outer half of the enamel, and D2 indicates that the caries is located in the inner half of the enamel. The classification of new-NIR images uses the same classification criteria as DIAGNOcam. However, due to the different imaging principles, caries in DIAGNOcam images is dark spots, while caries lesions are bright spots in new-NIR images. Thus, D0: surface intact and no bright spots, D1: caries is limited to the outer half of the enamel, and D2: caries is limited to the inner half of the enamel.

In order to use a unified classification to compare the visual inspection method, DIAGNOcam, and new-NIR, and distinguish the intact surface and enamel damage of each method, Table.1 defines the threshold and evaluates the caries level of the three methods.

Table.1 Thresholds corresponding to the level of dental caries diagnosed by visual inspection, new-NIR and DIAGNOcam

Visual inspection	New-NIR	DIAGNOcam
0	D0	D0
1,2	D1	D1
3	D2	D2

3.3. Statistical Analysis

Statistical analysis was performed using SPSS Version 23 (SPSS Inc., Chicago, USA). Cohen's kappa (κ) was used to measure inter- and intra-rater reliability (linear weighted κ values)(24). A cross table compares the new-NIR and DIAGNOcam assessments with visual inspection scores and shows the distribution. Spearman's rank correlation was performed to measure the overall association strength between both examination methods and visual inspection. Sensitivity, specificity, and accuracy were calculated to assess the probability of correct ratings. Sensitivity for sound surfaces was defined as the ability to correctly detect sound surfaces, specificity of sound surfaces therefore as the ability to exclude a sound surface. For enamel and dentin lesions, sensitivity and specificity were defined as usual. Accuracy was defined as the proportion of results that agree with the reference standard. A true positive (TP) is a tooth that is detected as caries by the gold standard and also detected as caries by evaluation; True negative (TN) is the gold standard for teeth that are tested as healthy and evaluated as healthy; False positives (FPs) indicate teeth that are gold standard tested healthy but evaluated as caries, i.e. teeth that overestimate test results; A false negative (FN) indicates a tooth that is detected as caries by the gold standard but evaluated as healthy, i.e. underestimated the test results.

The two examiners classified the three diagnostic methods, respectively, and the interval between the two examinations was two weeks. All premolars and molars were examined in a darkroom using new-NIR. The teeth were fixed by plasticine, and the new-NIR was fixed on a bracket that could be adjusted up and down. Images were acquired above, and perpendicular to the region of interest (ROI), Fig.2 is the image of the part of the tooth acquired by new-NIR, and the caries part is in the red area. After the examination by new-NIR, the image information was acquired in a darkroom environment with DIAGNOcam and stored using KID software (Kavo Integrated Desktop, Kavo, Germany), Fig.3 shows the image of the part of the tooth taken by DIAGNOcam, and the caries part is in the red area.

Table.2 shows the cross-table for the visual inspection method for examiner 1 and examiner 2. Table.3 shows the cross-table for the first examination and the second examination in the visual inspection method. After calculation, the results were as follows: Between the two assessments of Examiner 1, the Kappa value was 0.939, and between Examiner 2, the Kappa value was 0.940. The Kappa values were higher than 0.9, demonstrating the accuracy of the examiners' internal evaluation. The Kappa value between the two examiners was 0.970 during the initial inspection and 0.848 during the subsequent inspection. Naturally, the Kappa values were higher than 0.8, demonstrating the reliability of the evaluation between the examiners.

According to the classification method of the above-mentioned visual inspection, the reliability test of new-NIR and DIAGNOcam was evaluated. The Kappa value calculation of the obtained data and the results of the visual inspection are shown in Table.4. The k-values of the assessment results between and within the examiners were > 0.81, indicating that the evaluation results within and between examiners are reliable, and the time interval has no significant effect on the reproducibility within the examiner.

Table.2 Cross table for visual inspection for examiner 1 and examiner 2

		Visual inspection 1
		Examiner 1			Total	Examiner 2			Total
		D0	D1	D2		D0	D1	D2
Visual inspection 2	D0	23	1	0	24	24	2	0	26
	D1	0	22	1	23	0	20	0	20
	D2	0	0	7	7	0	0	8	8
Total		23	23	8		24	22	8

Table.3 Cross table for the first examination and the second examination of examiner 1in the visual inspection method

		Examiner 1
		Visual inspection 1			Total	Visual inspection 2			Total
		D0	D1	D2		D0	D1	D2
Examiner 1	D0	23	1	0	24	23	3	0	26
	D1	0	22	0	22	1	19	0	20
	D2	0	0	8	8	0	1	7	8
Total		23	23	8		23	24	7

Table.4 Consistency within and between inspectors

Kappa	Checks internal consistency				Consistency between examiner
	Inspector 1			Inspector 2	First check	Second check
Visual inspection		0.939	0.940		0.970	0.848
DIAGNOcam		0.940	0.911		0.941	0.910
New-NIR		0969	0.878		0.908	0.817

The evaluation of Kappa values shows that its reliability is high, indicating that its evaluation results are accurate. Therefore, Table.5 shows the cross table for the diagnostic results (D0, D1, D2) of 54 ROI after combining the results of 2 examiners and 2 examinations. In the table, the new-NIR and DIAGNOcam evaluations were compared with the visual inspection evaluation, and their distribution was displayed, and the visual inspection verification of 54 ROI showed 23 intact surfaces, accounting for 42.6%; There were 23 cases of external caries in enamel, accounting for 42.6%, and 8 cases of internal caries in enamel, accounting for 14.8%. The overall agreement between new-NIR and visual inspection was 75.9%. 16.7% of new-NIR underestimated the severity of caries lesions, and 7.4% overestimated the severity of caries lesions. The overall agreement between DIAGNOcam and visual inspection was 83.3%, with 9.3% underestimating the severity of caries lesions and 7.4% overestimating the severity of caries lesions.

Table.5 Cross table for 54 ROI of visual inspection and new-NIR, DIAGNOcam

		New-NIR			DIAGNOcam			Total
		D0	D1	D2	D0	D1	D2	Total
Visual examination	D0	20	3	0	21	2	0	23
	D1	6	16	1	4	17	2	23
	D2	0	3	5	0	1	7	8
Total		26	22	6	25	20	9

According to Table.5, the test results of new-NIR and DIAGNOcam were compared with the visual inspection (gold standard), and the Spearman correlation analysis was performed, and the significance between the two pairs was <0.01, indicating that the correlation coefficient between the two pairs was reliable (statistically significant). The diagnostic results of DIAGNOcam were strongly correlated with the results of visual inspection with a correlation coefficient of 0.831, while the correlation between new-NIR and visual inspection was slightly lower at 0.741. The results showed that the caries detection effect of new-NIR and DIAGNOcam was better, but compared with the diagnosis results of new-NIR, the diagnostic results of DIAGNOcam were more correlated with the visual inspection method.

To compare the results of new-NIR with DIAGNOcam in correctly diagnosing the degree of caries, the sensitivity, specificity, and accuracy of the two methods were calculated, respectively. Comparing the difference of 54 ROI in the diagnosis of new-NIR. It was calculated to have a sensitivity of 0.806, a specificity of 0.870, and an accuracy of 0.833. Secondly, comparing the differences of 54 ROI in the diagnosis of DIAGNOcam. It was calculated to have a sensitivity of 0.871, specificity of 0.913, and accuracy of 0.889, as shown in Table.6. The results showed that the sensitivity, specificity and accuracy of new-NIR were > 0.8, indicating that the NIR reflection was very accurate in detecting healthy teeth and decayed teeth.

Table.6 Sensitivity, specificity, and accuracy of new-NIR and DIAGNOcam

	Sensitivity	Specificity	Accuracy
New-NIR	0.806	0.870	0.833
DIAGNOcam	0.871	0.913	0.889

This study evaluated and approved the application potential of 780 nm waveband near-infrared diffuse reflectance imaging in the diagnosis of early caries to prevent the further development of caries and avoid the occurrence of dental fillings to promote the diagnosis and application of near-infrared light in difficult early caries.

In recent years, research has been increasing on detecting dental lesions by near-infrared light. Hirasuna et al. suggested multimodal NIR imaging as a potential means for differentiating between mild fluorosis and deeper caries(25). In 2019, Northeast Normal University independently designed a near-infrared optical imaging device to detect hard tooth tissue. In this device, the light is collimated by the collimation adjustment mirror and transmitted to the liquid crystal optical modulator, which automatically adjusts the light intensity and irradiates both sides of the tooth. The Institute of Chunguang Machine, President of the Chinese Academy of Sciences, disclosed a caries diagnostic imaging device and a handheld caries diagnostic imager, in which near-infrared light is irradiated on the measured tooth through optical fiber, and the camera collects the transmission image of the measured tooth through the optical fiber. The host computer acquires and processes the transmitted image and highlights the decayed area from the tooth. CariVu (Dexis, Hatfield, Pennsylvania) invented a near-infrared caries instrument that uses 780 nm light to detect dental caries with near-infrared occlusal penetrating illumination(26).

This study also focuses on diagnosing difficult-to-diagnose caries lesions in the early stage by near-infrared imaging methods, 780 ± 20 nm was selected as the light source of the near-infrared imager (New-NIR), and the near-infrared imager was built on the basis of the original work of the laboratory. Compared with DIAGNOcam, the Kappa values were calculated to evaluate the reliability between and within examiners. The Spearman correlation coefficient was used to analyze the overall correlation strength between new-NIR and DIAGNOcam in early caries detection and visual inspection. The cross-tables were used to count true positive, true negative, false positive and false negative, calculating the sensitivity, specificity, and accuracy of each diagnostic method to assess the probability of correct rating at early caries detection. There are currently few studies on near-infrared reflectometry in caries detection. The Chinese team's research is based on near-infrared transmission imaging, as there is no related work on near-infrared reflectance imaging at this time. While new-NIR images based on near-infrared diffused reflection method have caries spots as bright spots, DIAGNOcam based on near-infrared transmission method produces dark spots in the caries area. Additionally, the near-infrared transmission method requires contact irradiation on the buccal and lingual surfaces of the teeth, whereas new-NIR has no contact irradiation above the teeth, so new-NIR does not require repeated disinfection when used.

The usefulness of near-infrared diffuse reflectance imaging for the early diagnosis of dental caries is discussed in this research. However, there are still some drawbacks that can be fully taken into account in subsequent studies to increase the system's precision. On the one hand, this study only includes a small number of samples. The 54 ROI in 18 distinct teeth were used to examine the teeth. Samples taken from the same tooth are more similar to those from different teeth or patients. As a result, future research could use a larger sample of teeth, particularly those with nearby surfaces and less deterioration. Second, the issue of stray light interference in optical system design still exists, resulting in poor image quality. Future designs should completely take into account the elimination of stray light interference, such as window antireflection film transmittance improvement, bevel assembly. Finally, the impact of moisture must be completely taken into account; This article focuses on ex vivo tooth tissue, where the moisture in the teeth has little effect on the detection equipment. However, in vivo detection, the moisture in the mouth and teeth will greatly interfere with the detection process, particularly when the indoor temperature is low. The detection equipment should be fully warmed to avoid window atomization. At the same time, the water vapor in the mouth will also affect the quality of near-infrared imaging, and the impact of these factors should be fully considered in image preprocessing. As a result, numerous interference elements must be concerned in the subsequent research and development of the equipment's essential software and hardware. Enhancing image quality will remain the system's primary focus for future advancement.

Ethics approval and consent to participate

All experimental protocols were carried out according to relevant guidelines and regulations or the Declaration of Helsinki and were approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine (No.SH9H-2020-T17-1). Written informed consent to participates in the study was obtained from the donor.

Consent for publication

Not applicable

Availability of data and materials

All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.

Competing interests

The authors declare that there are no conflicts of interest relevant to this paper.

Funding

This research was supported by the National Natural Science Foundation of China, 62175153, Shanghai Science and Technology Commission 21S902700 and National Key Research and Development Program (No.2020YFB2007504).

Authors' contributions

W.C. literature review, data analyses, interpretation of results, writing of the first draft, critical review of the manuscript, approval of the final version. Y.C.X. literature review, writing of the first draft, interpretation of results, critical review of the manuscript, approval of the final version. Z.H.Y. conception of the study, literature review, review data analyses, interpretation of results, writing of the first draft, critical review of the manuscript, approval of the final version. L.G.Y. literature review, interpretation of results, critical review of the manuscript, approval of the final version. All other authors corrected and approved the manuscript.

Acknowledgements

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Study on near-infrared diffused reflectance imaging for early caries detection

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Abstract

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1. Introduction

2. Principle and System Design

2.1. Principle

2.2. System design

3. Materials and Methods

3.1. Sample preparation

3.2. Classification method

3.3. Statistical Analysis

4. Result

5. Discussion

Declarations

References

Additional Declarations

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