Department of Oral and Maxillofacial Radiology, Graduate School, Kyung Hee University, Seoul 02447, Korea.
Department of Orthodontics, Graduate School, Kyung Hee University, Seoul 02447, Korea.
Sensors (Basel). 2021 Mar 3;21(5):1741. doi: 10.3390/s21051741.
The aim of this study was to present an optimal diagnostic protocol by comparing and analyzing a conventional examination and the quantitative light-induced fluorescence (QLF) technique. Selected were 297 teeth of 153 patients to take QLF images and bitewing radiographs. Occlusal dental caries, proximal dental caries and cracks were evaluated and scored using QLF, X-ray and/or visual criteria. The sensitivity, specificity, and area under the curve (AUC) of a receiver operating characteristic analysis were calculated. Two fluorescence parameters (|ΔFmax| and ΔRmax) were utilized to evaluate the fluorescence pattern according to the severity of lesions based on QLF or X-ray criteria. QLF showed higher scores for detecting occlusal dental caries and cracks than the conventional method. ΔRmax increased more clearly than ΔFmax did with occlusal dental caries. The |ΔFmax| values of occlusal dental caries, proximal dental caries and cracks showed good AUC levels (0.84, 0.81 and 0.83, respectively). The ΔRmax of occlusal dental caries showed the highest AUC (0.91) and the ΔRmax of proximal dental caries showed a fail level (0.59) compared to bitewing radiographs. The QLF image could visualize and estimate the degree of occlusal dental caries or cracks. Consequently, the QLF technique may be an adjunct tool to conventional methods for the detection of occlusal caries and peripheral cracks.
本研究旨在通过比较和分析传统检查和定量光诱导荧光 (QLF) 技术,提出一种最佳的诊断方案。选择了 153 名患者的 297 颗牙齿进行 QLF 成像和牙合翼片拍摄。使用 QLF、X 射线和/或视觉标准评估和评分牙合面龋、邻面龋和裂纹。计算了受试者工作特征分析的灵敏度、特异性和曲线下面积 (AUC)。根据 QLF 或 X 射线标准,利用两个荧光参数 (|ΔFmax| 和 ΔRmax) 来评估根据病变严重程度的荧光模式。QLF 比传统方法显示出更高的检测牙合面龋和裂纹的评分。与邻面龋相比,ΔRmax 比 ΔFmax 更明显地增加。牙合面龋、邻面龋和裂纹的 |ΔFmax| 值均表现出良好的 AUC 水平(分别为 0.84、0.81 和 0.83)。与牙合翼片相比,牙合面龋的 ΔRmax 显示出最高的 AUC(0.91),而邻面龋的 ΔRmax 则显示出失败水平(0.59)。QLF 图像可以可视化和估计牙合面龋或裂纹的程度。因此,QLF 技术可能是传统方法检测牙合面龋和周围裂纹的辅助工具。