Detection of pit and fissure sealant microleakage using autofluorescence

doi:10.21203/rs.3.rs-3336538/v1

Download PDF

Article

Detection of pit and fissure sealant microleakage using autofluorescence

https://doi.org/10.21203/rs.3.rs-3336538/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Objectives

The aim of this study was to evaluate the feasibility of detecting the presence and severity of microleakage of pit and fissure sealant using Quantitative Light-induced Fluorescence (QLF) technology.

Methods

The areas of interest (AOI) were a total of 160 pit and fissure sites obtained from the occlusal surfaces of 40 permanent teeth. Fluorescent images were acquired using a QLF device, and the ΔF_max of each AOI was analysed. After staining and cross-sectioning of the teeth, histological dye penetration was scored on a 0–3 scale. The relationship between ΔF_max and microleakage depth was analysed, and the areas under the curve (AUC) were calculated.

Results

ΔF_max showed a significant increase as microleakage depth increased, and a strong correlation with histological scores (r = -0.72, P < 0.001). ΔF_max increased 2.6 times between a sound sealant margin and severe dye penetration. AUC analysis showed a high diagnostic accuracy of microleakage depth (AUC = 0.83–0.91). The AUC that differentiated the outer half microleakage of the sealant (histological score 0 vs 1–3) was the highest at 0.91.

Conclusions

The use of autofluorescence detection based on QLF technology enabled the detection of microleakages in sealants non-destructively and demonstrated excellent diagnostic validity.

Health sciences/Risk factors

Health sciences/Signs and symptoms

Autofluorescence

Microleakage

Pit and fissure sealant

Quantitative Light-induced Fluorescence

Microleakage is defined as the passage of bacteria, oral fluids, molecules, or ions through minute gaps that are difficult to observe with the naked eye, occurring between the tooth and the dental restoration¹. Microleakage that occurs owing to poorly placed pit and fissure sealants can progress to material failure owing to wear and fatigue of the sealant². Microleakage can lead to several problems such as discoloration of the restoration, marginal fractures, recurrent decay, tooth sensitivity, and dimensional changes, ultimately leading to the need for retreatment³. Pit-and-fissure sealants have been reported to be effective in preventing dental caries and inhibiting the progression of non-cavitated carious lesions by sealing the occlusal surfaces of teeth using resin or glass ionomer cement^4–6. To prevent dental caries, the pit and fissure sealants should remain well bonded to the enamel surface and effectively prevent microleakage from the early stages^7,8. Therefore, it is important to objectively and accurately diagnose the subtle changes that occur after the restoration of pit and fissure sealants in clinical practice.

Partial microleakage can also affect the retention of the sealant. Factors that reduce its retention include errors during the sealant treatment process and material weaknesses that can lead to fractures. In addition, microleakage can cause dental caries below the sealant and complete sealant detachment⁹. Since the ability to penetrate into the narrow and fine pit and fissure of the tooth is critical for sealants, they do not contain fillers compared with composite resin restorations. Therefore, if microleakage occurs owing to the physical pressure applied to the sealant, a rapid progression of decay can occur below the sealant.

The conventional methods for detecting sealant microleakage involve assessing the boundary surface of the sealant using dye penetration, or identifying secondary carious lesions caused by microleakage via radiographs. Additionally, traditional techniques such as tactile inspection of the sealant-to-tooth interface and visual detection of colour changes in secondary carious lesions are commonly employed in clinical settings. However, these methods suffer from low validity and reliability, largely because precise measurements are difficult to obtain due to the narrow gap between the sealant and enamel^10,11. Several studies have explored the use of various optical instruments to objectively identify microleakage in sealants, thereby overcoming the limitations of traditional inspection techniques¹². Several studies have reported the use of Swept-Source Optical Coherence Tomography (SS-OCT) for detecting defects at the tooth-restoration interface^13–15.

Quantitative Light-induced Fluorescence (QLF) is a representative optical technique that utilizes the autofluorescence of teeth and bacteria. This technique involves illuminating teeth with blue-violet visible light at a wavelength of 405 nm. It quantifies the autofluorescence emitted by sound enamel or the presence of bacterial porphyrin fluorescence, allowing the quantification of dental caries or other lesions^8,16–21. According to previous studies, the use of QLF to evaluate sealant retention has shown a detection capability approximately three times superior to that of clinical examinations²². Furthermore, QLF can detect metabolic products, such as porphyrins, produced by oral bacteria through red autofluorescence. This allows the observation of bacterial structures, including plaques and calculus, as well as tissues infiltrated by bacteria, indicating red fluorescence^23,24. QLF can easily detect the occurrence of secondary caries around restorations^25–28. In the case of microleakage occurring in the pit and fissure sealant, bacteria infiltrating through the leakage can be observed using the red fluorescence of the QLF. A study evaluating the detection of secondary caries around permanent tooth sealants using QLF reported that it had higher validity in assessing enamel and dentin secondary caries than that of visual inspection and radiographic examination²⁹. Furthermore, artificial carious lesions were formed around resin restorations and evaluated using QLF. It was reported that QLF could detect incipient secondary caries, but distinguishing it from staining was challenging³⁰. However, research specifically comparing the QLF technology with the depth of microleakage in permanent tooth pit and fissure sealants is limited.

The aim of in vitro study was to evaluate the feasibility of detecting the presence and severity of microleakage of pit and fissure sealant using Quantitative Light-induced Fluorescence (QLF) technology. For this purpose, the maximum fluorescence loss parameter (ΔF_max) obtained from QLF and the dye penetration score from histological evaluation were compared.

Sample distribution

This study examined 160 sites, comprising four areas from each of the 40 teeth, with four teeth excluded due to damage incurred during the experiment (Table 1). Following dye penetration, histological evaluations revealed that approximately 22% of the tooth sections exhibited no microleakage (score 0), while 28% received a score of 3, indicating complete dye penetration into the base of the pit and fissure.

Table 1

Distribution of ΔF_max according to the dye penetration histological score after microleakage formation.
Dye penetration histological score	N(distribution%)	Fluorescence variables
Dye penetration histological score	N(distribution%)	│ΔF_max│
0	35 (21.9%)	7.3 ± 2.5 ^a
1	39 (24.4%)	11.2 ± 4.4 ^b
2	41 (25.6%)	15.9 ± 4.6 ^c
3	45 (28.1%)	19.4 ± 7.5 ^d
All values are expressed as mean ± standard deviations. │ΔF_max│ means absolute value of maximum fluorescence loss. Different letters within the same column indicate significant differences between the groups using Games–Howell post hoc analysis at a = 0.05

Differences in fluorescence variable (ΔF_max) according to the depth of sealant microleakage

As the depth of microleakage in the pit and fissure sealants increased, the absolute value of ΔF_max measured at the occlusal surface for areas with sealant microleakage that showed a significant increase (P < 0.05, Table 1, Fig. 3). The ΔF_max of the microleakage areas demonstrated a statistically significant correlation at a high level with increasing dye penetration histological scores (r = -0.72, P < 0.001). The average ΔF_max values for each dye penetration score showed significant differences among all scores (P < 0.05). Particularly, the │ΔF_max│ value for the most severe microleakage score 3 was 19.4, approximately 2.6 times higher than that of the intact condition with no microleakage (score 0, 7.3).

Diagnostic capability to distinguish the severity of microleakage using ΔF_max

To assess the diagnostic accuracy of the fluorescence variable ΔF_max in relation to the depth of microleakage in pit and fissure sealants, sensitivity, specificity, and AUC were calculated at the optimal cut-off point, based on analysis from three diagnostic thresholds (Table 2). The AUC for ΔF_max demonstrated a high level of diagnostic accuracy, ranging from 0.83 to 0.91 across all diagnostic thresholds for detecting microleakage (P < 0.001). Specifically, when distinguishing microleakage beyond the outer half of the pit and fissure sealant (histological scores 1–3) from a lack of microleakage (histological score 0), a ΔF_max value of 10.10 yielded a sensitivity of 0.82, a specificity of 0.91, and the highest AUC value of 0.91.

Table 2

Area under the ROC curve, optimum sensitivity, specificity and cut-off for the │ΔF_max│at each diagnostic threshold measured using histological analysis
Criteria for microleakage severity	Cut-off value	Sensitivity	Specificity	AUC	95% CI
Score 0/1–3	10.10	0.82	0.91	0.91	0.87–0.96
Score 0–1/2–3	10.22	0.95	0.68	0.89	0.84–0.94
Score 0–2/3	15.21	0.82	0.73	0.83	0.76–0.89
AUC, area under the curve; CI, confidence interval; ROC, receiver operating characteristic curve
score; dye penetration histological score

In this study, QLF technology, based on the autofluorescence of teeth, was employed to objectively and quantitatively assess microleakage in pit and fissure sealants. The autofluorescence variable ΔF_max exhibited the highest level of accuracy for detecting initial microleakage, enabling non-invasive identification of early-stage microleakage. Utilizing the QLF technique in clinical settings to monitor the condition of sealants and restorations allows for early-stage microleakage detection, thereby preventing the onset of severe secondary caries.

Various fluorescence variables can be obtained during the process of evaluating tooth autofluorescence using QLF technology. Among these, the parameter △F_max, which reflects areas where tooth autofluorescence is most diminished and appears darkest, was selected for this study³¹. △F_max showed a significant increase in correlation with rising histological scores at each stage, facilitating the differentiation of microleakage depth using △F_max (Table 1, Fig. 3). Moreover, a statistically significant strong correlation was observed between △F_max and histological scores (r = -0.72, P < 0.001). According to previous studies, △F_max has been reported to non-destructively evaluate early caries lesions progressing into the sub-surface areas of pits and fissures on the occlusal surface of teeth^32,33. Another study focusing on the detection of enamel cracks using QLF reported that ΔF_max has been proposed as an indicator for detecting enamel crack lesions, as the fluorescence appears more scattered and darker in the deepest part of the lesion³⁴. It was found that ΔF_max, which represents the deepest part of the lesion, serves as a stable indicator for analysing areas with tooth cracks and it is less influenced by the selection of the Area of Interest (AOI)³⁴. Based on these findings, △F_max is a reliable parameter for evaluating sealant microleakage, exhibiting low inter-examiner variability and minimal susceptibility to the methodological influences.

According to the evaluation of the diagnostic accuracy of QLF technology for detecting microleakage around the pit and fissure sealants, fluorescence variable obtained from QLF technology were valid not only for determining the presence of microleakage but also for distinguishing its severity or progression level (AUC > 0.8). In particular, △F_max exhibited the highest level of diagnostic accuracy (AUC 0.91) when distinguishing between cases of no microleakage (score 0) and all levels of microleakage (scores 1, 2, 3), achieving both high sensitivity and specificity. Sealants typically lack fillers allowing them to effectively flow into complex pit and fissure structures. As a consequence, sealants exhibit relatively lower physical strength and are highly susceptible to microleakage. Therefore, the early detection of sealant microleakage is even more critical than for other restorative materials. In this context, the effective detection of sealant microleakage—ranging from initial enamel outer-half microleakage (score 1) to deeper levels (scores 2 and 3)—using ΔF_max in this study is of significant clinical relevance.

When sealant microleakage extends beyond the inner half of the cross-sectional area (score 2 or 3), the risk of severe secondary caries development increases. In this study, diagnosing microleakage beyond the inner half exhibited high diagnostic accuracy (AUC 0.91) and sensitivity (0.95), but moderate specificity (0.68). These results are consistent with previous systematic review studies that compared various methods for detecting secondary caries in amalgam and resin composite restorations²⁹. Particularly, when sealant microleakage extends beyond the inner half, it suggests that bacteria have already penetrated the sealant base, increasing the risk of partial sealant loss or the onset of secondary caries. In such clinical scenarios, where sealant reapplication can be performed without additional tooth removal, diagnostic methods like QLF—offering higher sensitivity over specificity—are deemed to have notable clinical utility from a preventive standpoint.

The resin components comprising the sealant typically contain radiopaque fillers to facilitate their identification in dental X-rays. The type and quantity of these fillers may vary depending on the manufacturer. In this study, Clinpro sealant (3M-ESPE, USA), was utilized. Upon application and curing, this sealant turned to an opaque off-white colour when visually observed and appeared darker under fluorescent observation compared to the natural tooth enamel (Fig. 3). In a previous research, when various types of resin composites were evaluated using QLF, there were significant differences in their autofluorescence patterns. Most resin composites exhibited brighter fluorescence than natural tooth fluorescence. However, some products displayed darker fluorescence than the tooth autofluorescence. This difference in fluorescence is believed to originate from variations in the fluorescent components included in the productes³⁵. The dark fluorescence of the sealant material used in this study could have interfered with the detection of fluorescence loss due to microleakage, potentially affecting the interpretation of results in some cases. However, as reported in the previous study, using a sealant that exhibits brighter fluorescence than natural tooth enamel could enable more sensitive evaluations of fluorescence loss associated with microleakage.

QLF technology allows for the simultaneous assessment of changes in both tooth autofluorescence and red fluorescence produced by bacterial metabolites. However, because this study employed extracted teeth, it was challenging to evaluate the impact of red fluorescence originating from actual oral biofilm. In an oral environment, the red fluorescence from bacterial biofilms infiltrating the areas of sealant or restoration microleakage can indeed influence the fluorescence changes. Therefore, future research should consider evaluating not only the fluorescence changes caused by actual microleakage in the oral environment but also the fluorescence changes associated with bacteria-related microleakage.

Study design

This study followed previously described methods to artificially induce microleakage in a laboratory setting³⁶. To create microleakage of various depths in sound sealants, two application conditions were used: the method recommended by the manufacturer, and the saliva contamination method. Prior to sealant application on all teeth, a standardized pre-treatment procedure was carried out, followed by drying. Sealant application according to either the manufacturer's instructions (N = 18) or saliva contamination (N = 22) was then implemented. Subsequently, an artificial hydration process was performed to replicate conditions within the oral cavity after pit and fissure sealant application for all samples (N = 40). Following the hydration process, four evaluation areas (n = 160) on each tooth were selected as Areas of Interest (AOIs), denoted as AOI 1–4 (Fig. 1). The selection of AOIs was limited to the area of supplemental grooves on the occlusal surface, and a total of four AOIs were designated. These AOIs were located along the central groove, branching out in the buccal or lingual direction from both the mesial and distal pits for evaluation. Each tooth was captured using QLF technology from the occlusal direction, followed by dye penetration. Cross-sectioning for histological analysis was performed immediately after.

Preparation of the Specimen

The use of extracted teeth and human saliva in this study was approved by the Institutional Review Board (IRB number: 2–2017–0044) of the Yonsei University Dental Hospital. We have adhered to the STROBE guidelines on the reporting of the results. All procedures performed in the study involving extracted teeth and saliva were in accordance with the 1964 Helsinki Declaration. Participants were informed of the study, and informed consent was obtained. The extracted sound teeth were frozen at -20°C. Total 44 sound permanent molars without dental caries or discolouration were used after removal of dental plaque. The remaining deposits attached to the tooth surface were removed using a manual scaler, and a bristle brush was mounted on a low-speed handpiece (Lasungmedics, Korea) to remove the plaque on the tooth with fluoride-free pumice. And then the root was cut using a cutting equipment (Diamond discs, NTI-Kahla GmbH, Germany) and then moulded using resin on an acrylic block (15 × 12 × 6 mm) (Ortho-Jet, Lang Dental Mfg. Co., Inc., USA).

For sealant application, the pits and fissures of teeth were etched for 15 s using a 35% phosphoric acid etchant (3M-ESPE, USA), washed with a water for 10 s, and dried. Clinpro™ (3M-ESPE, USA) was used as the pit and fissure sealant material and Dr's Light™ (Good Doctors Co., Ltd, Korea) was used for light curing. The saliva contamination method involved applying human saliva (0.1 ml) to the occlusal surface, followed by absorbing excessive saliva using a scientific wiper. Following previous studies, the samples were then light-cured for 40 seconds. All of the specimens processed with either of the two different methods of sealant application (manufacturer's instructions and saliva contamination) underwent an artificial hydration process for 48 hours by immersion in distilled water. This process aimed to create an environment resembling the oral cavity while accelerating the microleakage conditions.

Acquisition of Fluorescence Images

In this study, the microleakage of sealants was assessed non-destructively by capturing fluorescent images from the occlusal surface of the tooth. Fluorescent imaging was performed at a distance of 10 cm from the occlusal surface. The imaging was carried out using the Quantitative Light-induced Fluorescence-Digital system (QLF-D biluminator TM, Inspektor Research Systems BV, Amsterdam, The Netherlands), positioned in a dark room environment. The QLF-D is a single-lens reflex camera with two light-emitting diode lamps mounted in front of a 60 mm macro lens. And 12 blue light (wavelength 405 nm) and 4 white light were attached, and each light sources were irradiated. The QLF-D continuously captured white-light and blue-light images under the same conditions. The QLF-D photographic conditions were as follows: shutter speed of 1/13, aperture value of 14, ISO 250, and fluorescence image: shutter speed of 1/50, aperture value of 10, and ISO 1600.

Quantitative Evaluation of Autofluorescence

Fluorescence analysis was conducted using fluorescent images captured from the occlusal direction prior to histological evaluation. All images were independently analysed by two trained examiners (S.M and K.M). The two examiners standardized the analysis area before the evaluations and then quantified the auto-fluorescence of the microleakages detected in the pit and fissure sealant margins using a specific program (QA2 v1.26, Inspektor Research Systems BV, Amsterdam, The Netherlands). In case of disagreement, the two examiners reached an agreement through discussion. When the sound part was selected as a patch in the pit margins of the sealant, the microleakage site showed a loss of auto-fluorescence. The maximum fluorescence loss, which represents the largest amount of fluorescence loss, was calculated as ΔF_max [%] (Fig. 1). The delta F_max (△F_max, %), which indicates the maximum fluorescence loss, refers to the darkest area where fluorescence is reduced and is reported to reflect the deepest point within that area histologically³⁴. The two examiners (S.M and K.M) conducted fluorescence analysis prior to histological assessment of microleakage severity, performing the analysis in a blinded manner without prior information about the extent of microleakage.

Histological Analysis

The teeth were immersed in a 1% methylene blue solution for 24 h to facilitate the penetration of the solution between the sealant and the occlusal surface. Nail varnish was applied to the occlusal surface, except for 1 mm on the margin of the sealant and was dried to prevent unnecessary methylene blue solution penetration from the surface. The cross-section of one pit was marked with a water erasable pen on an acrylic block moulded with a crown to analyse the mesial and distal pits and cut at the same site for histological evaluation. After each specimen was washed and dried under water, the pits were sectioned longitudinally in the buccolingual direction using a cutter (TechCut 4™, Allied High Tech Products, Inc., California, USA). Four cut sections per tooth were obtained for each pit (Fig. 1). The mesial and distal pits of each tooth were remarked by selecting the higher score for solution penetration among the same two tooth surfaces when viewed from the buccolingual direction, and four histological scores per tooth were obtained (Fig. 2). To evaluate the microleakage of the exposed cut surface and the degree of penetration of the dye, it was observed using an optical microscope (Carl Zeiss Axio Imager A1m, Oberkochen, Germany) at a magnification of 50 ×. The selection of AOIs was limited to the area of supplemental grooves on the occlusal surface, and a total of four AOIs were designated. These AOIs were located along the central groove, branching out in the buccal or lingual direction from both the mesial and distal pits for evaluation.

The dye penetration score into microleakages in the pit and fissure sealants, was evaluated according to the classification system used in a previous study (Fig. 2)³⁷. Score 0: no dye penetration; score 1: dye penetration restricted to the outer half of the pit and fissure sealant; score 2: dye penetration to the inner half of the pit and fissure sealant; score 3: dye penetration into the underlying pit and fissure. The severity of microleakage was scored based on the depth of dye penetration in the cross-sectioned samples, and these scores were compared with the QLF fluorescence outcome.

Statistical analysis

The correlation between histological results and fluorescence parameter values was analysed using Spearman's rank correlation. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of fluorescence variable was analysed to evaluate the validity of the fluorescence variable △F_max that detect each score in the histology classification. A significance level of 5% was adopted for all analyses, and the data were analysed using R, version 4.0.2 (R Core Team, Vienna, Austria).

In conclusion, QLF technology based on autofluorescence can effectively detect the presence of the sealant microleakage and its severity with excellent diagnostic accuracy. Therefore, by utilizing QLF technology in clinical settings to monitor pit and fissure sealants, it is possible to provide appropriate treatment strategies on detected microleakage for preventing secondary caries development.

Availability of Data and Materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Acknowledgments

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI20C0129) and by a grant of the Bio & Medical Technology Development Program of the National Research Foundation (NRF) & funded by the Korean government (MSIT) (No. 2022M3A9F3016364).

Author contributions

Conceptualization, Sang-mi Nam and Baek Il Kim; methodology, Sang-mi Nam and Hye-min Ku; software and validation, Sang-mi Nam; formal analysis, Sang-mi Nam and Kyoung-min Kim; investigation, Sang-mi Nam and Hye-min Ku; data curation, Sang-mi Nam and Hye-min Ku; writing—original draft preparation, Hye-min Ku and Eun-Song Lee; writing—review and editing, Eun-Song Lee and Baek Il Kim. All authors have read and agreed to the published version of the manuscript.

Schmid-Schwap, M. et al. Microleakage after thermocycling of cemented crowns--a meta-analysis. Dent. Mater. 27, 855-869 (2011).
Mjör, I. A. Clinical diagnosis of recurrent caries. J. Am. Dent. Assoc. 136, 1426-1433 (2005).
Muliyar, S. et al. Microleakage in endodontics. J. Int. Oral Health 6, 99-104 (2014).
Schwendicke, F., Jäger, A. M., Paris, S., Hsu, L. Y. & Tu, Y. K. Treating pit-and-fissure caries: a systematic review and network meta-analysis. J. Dent. Res. 94, 522-533 (2015).
Ahovuo-Saloranta, A. et al. Sealants for preventing dental decay in the permanent teeth. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD001830.pub4, Cd001830 (2013).
Wright, J. T. et al. Sealants for preventing and arresting pit-and-fissure occlusal caries in primary and permanent molars: A systematic review of randomized controlled trials-a report of the American Dental Association and the American Academy of Pediatric Dentistry. J. Am. Dent. Assoc. 147, 631-645.e618 (2016).
Hatibovic-Kofman, S., Butler, S. A. & Sadek, H. Microleakage of three sealants following conventional, bur, and air-abrasion preparation of pits and fissures. Int. J. Paediatr. Dent. 11, 409-416 (2001).
Symons, A. L., Chu, C. Y. & Meyers, I. A. The effect of fissure morphology and pretreatment of the enamel surface on penetration and adhesion of fissure sealants. J. Oral Rehabil. 23, 791-798 (1996).
Hatibovic-Kofman, S., Wright, G. Z. & Braverman, I. Microleakage of sealants after conventional, bur, and air-abrasion preparation of pits and fissures. Pediatr. Dent. 20, 173-176 (1998).
Bader, J. D., Shugars, D. A. & Bonito, A. J. A systematic review of the performance of methods for identifying carious lesions. J. Public Health Dent. 62, 201-213 (2002).
Lino, J. R. et al. Association and comparison between visual inspection and bitewing radiography for the detection of recurrent dental caries under restorations. Int. Dent. J. 65, 178-181 (2015).
Hitij, T. & Fidler, A. Effect of dental material fluorescence on DIAGNOdent readings. Acta Odontol. Scand. 66, 13-17 (2008).
Bakhsh, T. A., Sadr, A., Shimada, Y., Tagami, J. & Sumi, Y. Non-invasive quantification of resin-dentin interfacial gaps using optical coherence tomography: validation against confocal microscopy. Dent. Mater. 27, 915-925 (2011).
Oancea, R. Assessment of the sealant/tooth interface using optical coherence tomography. J. Adhes. Sci. Technol. 29, 49-58 (2015).
Hariri, I., Sadr, A., Shimada, Y., Tagami, J. & Sumi, Y. Effects of structural orientation of enamel and dentine on light attenuation and local refractive index: an optical coherence tomography study. J. Dent. 40, 387-396 (2012).
Pretty, I. A. Caries detection and diagnosis: novel technologies. J. Dent. 34, 727-739 (2006).
Park, S. W. et al. Lesion activity assessment of early caries using dye-enhanced quantitative light-induced fluorescence. Sci. Rep. 12, 11848 (2022).
Choi, J. H., Jung, E. H., Lee, E. S., Jung, H. I. & Kim, B. I. Anti-biofilm activity of chlorhexidine-releasing elastomerics against dental microcosm biofilms. J. Dent. 122, 104153 (2022).
Park, S., Lee, E. S., Jung, H. I. & Kim, B. I. Optical detection of oral biofilm in hospitalized geriatric patients using quantitative light-induced fluorescence technology. Photodiagnosis Photodyn. Ther. 39, 102962 (2022).
Lee, J. Y., Jung, H. I. & Kim, B. I. A novel model to predict tooth bleaching efficacy using autofluorescence of the tooth. J. Dent. 116, 103892 (2022).
Kim, G. M., Kim, B. R., Lee, E. S., de Josselin de Jong, E. & Kim, B. I. Detection of residual resin-based orthodontic adhesive based on light-induced fluorescence. Photodiagnosis Photodyn. Ther. 24, 69-74 (2018).
Ozyoney, G., Tagtekin, D. A., Durmusoglu, O. & Yanikoglu, F. C. Twenty-four month evaluation of fissure sealants by clinical exami-nation and quantitative light-induced fluorescence. ODFCY 4, 14-19 (2005).
Ku, H. M., Kim, E. & Kim, B. I. Red fluorescence for assessing longitudinal tooth fractures. Photodiagnosis Photodyn. Ther. 38, 102845 (2022).
Lee, E. S., Kang, S. M., Ko, H. Y., Kwon, H. K. & Kim, B. I. Association between the cariogenicity of a dental microcosm biofilm and its red fluorescence detected by Quantitative Light-induced Fluorescence-Digital (QLF-D). J. Dent. 41, 1264-1270 (2013).
Kim, H. E. Quantitative Light-Induced Fluorescence: A Potential Tool for Dental Hygiene Process. J. Dent. Hyg. Sci. 13, 115-124 (2013).
Maeng, Y. J., Lee, H. S., Lee, E. S., Yoon, H. C. & Kim, B. I. Noninvasive detection of microleakage in all-ceramic crowns using quantitative light-induced fluorescence technology. Photodiagnosis Photodyn. Ther. 30, 101672 (2020).
Lee, J. W., Lee, E. S. & Kim, B. I. Optical diagnosis of dentin caries lesions using quantitative light-induced fluorescence technology. Photodiagnosis Photodyn. Ther. 23, 68-70 (2018).
Ellwood, R. P., Gomez, J. & Pretty, I. A. Caries clinical trial methods for the assessment of oral care products in the 21st century. Adv. Dent. Res. 24, 32-35 (2012).
Lenzi, T. L., Piovesan, C., Mendes, F. M., Braga, M. M. & Raggio, D. P. In vitro performance of QLF system and conventional methods for detection of occlusal caries around tooth‐colored restorations in primary molars. Int. J. Paediatr. Dent. 26, 26-34 (2016).
Gonzalez-Cabezas, C., Fontana, M., Gomes-Moosbauer, D. & Stookey, G. K. Early detection of secondary caries using quantitative, light-induced fluorescence. OPERATIVE DENTISTRY-UNIVERSITY OF WASHINGTON- 28, 415-422 (2003).
Gmür, R. et al. In vitro quantitative light-induced fluorescence to measure changes in enamel mineralization. Clin. Oral Investig. 10, 187-195 (2006).
Angmar-Månsson, B. & ten Bosch, J. J. Quantitative light-induced fluorescence (QLF): a method for assessment of incipient caries lesions. Dentomaxillofac. Radiol. 30, 298-307 (2001).
van der Veen, M. H. & de Josselin de Jong, E. Application of quantitative light-induced fluorescence for assessing early caries lesions. Monogr. Oral Sci. 17, 144-162 (2000).
Jun, M. K. et al. Detection and Analysis of Enamel Cracks by Quantitative Light-induced Fluorescence Technology. J. Endod. 42, 500-504 (2016).
Kim, B. R., Kang, S. M., Kim, G. M. & Kim, B. I. Differences in the intensity of light-induced fluorescence emitted by resin composites. Photodiagnosis Photodyn. Ther. 13, 114-119 (2016).
Hevinga, M. A., Opdam, N. J., Frencken, J. E., Bronkhorst, E. M. & Truin, G. J. Microleakage and sealant penetration in contaminated carious fissures. J. Dent. 35, 909-914 (2007).
Ovrebö, R. C. & Raadal, M. Microleakage in fissures sealed with resin or glass ionomer cement. Scand. J. Dent. Res. 98, 66-69 (1990).

No competing interests reported.

Download PDF

Editorial decision: Revision requested
17 Jan, 2024
Reviews received at journal
29 Sep, 2023
Reviewers agreed at journal
21 Sep, 2023
Reviewers invited by journal
20 Sep, 2023
Editor assigned by journal
20 Sep, 2023
Editor invited by journal
12 Sep, 2023
Submission checks completed at journal
12 Sep, 2023
First submitted to journal
08 Sep, 2023

You are reading this latest preprint version

Detection of pit and fissure sealant microleakage using autofluorescence

Status:

Version 1

Abstract

Objectives

Methods

Results

Conclusions

Figures

Introduction

Results

Sample distribution

Differences in fluorescence variable (ΔF_max) according to the depth of sealant microleakage

Diagnostic capability to distinguish the severity of microleakage using ΔF_max

Discussions

Materials and Methods

Study design

Preparation of the Specimen

Acquisition of Fluorescence Images

Quantitative Evaluation of Autofluorescence

Histological Analysis

Statistical analysis

Conclusions

Declarations

References

Additional Declarations

Status:

Version 1

Detection of pit and fissure sealant microleakage using autofluorescence

Status:

Version 1

Abstract

Objectives

Methods

Results

Conclusions

Figures

Introduction

Results

Sample distribution

Differences in fluorescence variable (ΔFmax) according to the depth of sealant microleakage

Diagnostic capability to distinguish the severity of microleakage using ΔFmax

Discussions

Materials and Methods

Study design

Preparation of the Specimen

Acquisition of Fluorescence Images

Quantitative Evaluation of Autofluorescence

Histological Analysis

Statistical analysis

Conclusions

Declarations

References

Additional Declarations

Status:

Version 1

Differences in fluorescence variable (ΔF_max) according to the depth of sealant microleakage

Diagnostic capability to distinguish the severity of microleakage using ΔF_max