Objectives: To prolong tooth life expectancy, tooth wear resulting in dentin exposure should be detected early. However, the most objective methods are clinically limited. We validated fluorescence parameters for distinguishing enamel from dentin-exposed wear in clinical images. Methods: Quantitative light-induced fluorescence (QLF) images of 73 adults (age range: 22–48 years, mean: 33.81 ± 7.71 years), including 1949 teeth with varying tooth wear degrees, without restorations, caries, or cusp area fractures, were used to calculate the ΔFwear values. Areas-of-interest (AOIs) were selected from QLF images; the ΔFwear values and the tooth wear index (TWI) were calculated for each tooth. The ΔFwear values were compared according to the TWI scores. The optimum ΔFwear values for distinguishing enamel and dentin-exposed wear were determined using the receiver operating characteristic (ROC) curve analysis. Results: Overall, 1949 AOIs were evaluated. The median ΔFwear values for teeth with TWI scores 0, 1, and 2 (5.7 %, 10.3 %, and 17.0 %) differed significantly (P < 0.001). The optimum cutoff ΔFwear values were 12.1 and 14.7 in the anterior and posterior teeth, respectively; the corresponding areas under the ROC values (AUROCs) were 0.86 and 0.93 (sensitivity: 0.79 and 0.85; specificity: 0.79 and 0.85, respectively). The ΔFwear cutoff values for different age groups were within a range (12.7–13.7) and showed high validity (sensitivity, specificity, and AUROC: 0.78, 0.77–0.78, and 0.87–0.88, respectively). Conclusions: At the optimum threshold, the ΔFwear values showed high validity for distinguishing dentin exposure in worn teeth (AUROC: 0.87‒0.93) and could determine pathological tooth wear, particularly in posterior teeth. Clinical significance: We demonstrated the feasibility of using QLF to detect dentin-exposed tooth wear and present optimal thresholds according to age. In addition, we confirmed the possibility using such image data for objective and cost-effective epidemiological investigation and application in tele-dentistry.
Bibliographical noteFunding Information:
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 ). Hoi In Jung has contributed as a co-corresponding author with the corresponding author, Baek-Il Kim.
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). Hoi In Jung has contributed as a co-corresponding author with the corresponding author, Baek-Il Kim.
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