Eun-Soo Kim1, Eun-Song Lee1, Si-Mook Kang1, Eun-Ha Jung1, Elbert de Josselin de Jong2, Hoi-In Jung1, Baek-Il Kim3. 1. Department of Preventive Dentistry & Public Oral Health, BK21 PLUS Project, Yonsei University College of Dentistry, Seoul, Republic of Korea. 2. Department of Preventive Dentistry & Public Oral Health, BK21 PLUS Project, Yonsei University College of Dentistry, Seoul, Republic of Korea; Department of Health Services Research, University of Liverpool, Liverpool, United Kingdom; Inspektor Research Systems BV, Amsterdam, The Netherlands. 3. Department of Preventive Dentistry & Public Oral Health, BK21 PLUS Project, Yonsei University College of Dentistry, Seoul, Republic of Korea; Oral Science Research Institute, Yonsei University College of Dentistry, Seoul, Republic of Korea. Electronic address: drkbi@yuhs.ac.
Abstract
OBJECTIVES: This study aimed to assess the screening performance of the quantitative light-induced fluorescence (QLF) technology to detect proximal caries using both fluorescence loss and red fluorescence in a clinical situation. Moreover, a new simplified QLF score for the proximal caries (QS-Proximal) is proposed and its validity for detecting proximal caries was evaluated as well. METHODS: This clinical study included 280 proximal surfaces, which were assessed by visual-tactile and radiographic examinations and scored by each scoring system according to lesion severity. The occlusal QLF images were analysed in two different ways: (1) a quantitative analysis producing fluorescence loss (ΔF) and red fluorescence (ΔR) parameters; and (2) a new QLF scoring index. For both quantitative parameters and QS-Proximal, the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were calculated as a function of the radiographic scoring index at the enamel and dentine caries levels. RESULTS: Both ΔF and ΔR showed excellent AUROC values at the dentine caries level (ΔF=0.860, ΔR=0.902) whereas a relatively lower value was observed at the enamel caries level (ΔF=0.655, ΔR=0.686). The QS-Proximal also showed excellent AUROC ranged from 0.826 to 0.864 for detecting proximal caries at the dentine level. CONCLUSION: The QS-Proximal, which represents fluorescence changes, showed excellent performance in detecting proximal caries using the radiographic score as the gold standard.
OBJECTIVES: This study aimed to assess the screening performance of the quantitative light-induced fluorescence (QLF) technology to detect proximal caries using both fluorescence loss and red fluorescence in a clinical situation. Moreover, a new simplified QLF score for the proximal caries (QS-Proximal) is proposed and its validity for detecting proximal caries was evaluated as well. METHODS: This clinical study included 280 proximal surfaces, which were assessed by visual-tactile and radiographic examinations and scored by each scoring system according to lesion severity. The occlusal QLF images were analysed in two different ways: (1) a quantitative analysis producing fluorescence loss (ΔF) and red fluorescence (ΔR) parameters; and (2) a new QLF scoring index. For both quantitative parameters and QS-Proximal, the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were calculated as a function of the radiographic scoring index at the enamel and dentine caries levels. RESULTS: Both ΔF and ΔR showed excellent AUROC values at the dentine caries level (ΔF=0.860, ΔR=0.902) whereas a relatively lower value was observed at the enamel caries level (ΔF=0.655, ΔR=0.686). The QS-Proximal also showed excellent AUROC ranged from 0.826 to 0.864 for detecting proximal caries at the dentine level. CONCLUSION: The QS-Proximal, which represents fluorescence changes, showed excellent performance in detecting proximal caries using the radiographic score as the gold standard.
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