Abstract
Dental caries is a commonly progressive disease that proceeds through various degrees of severity that a dentist can detect. The aims of the in vivo study were to assess the accuracy of the individual model (near-infrared light transillumination [NILT] device, visual and radiographic examinations) in detecting occlusal caries, and to evaluate the performance of visual and NILT device combination for occlusal caries detection in deciding the treatment options. Fifty-two non-cavitated occlusal surfaces from 16 patients were assessed with three different diagnostic devices in random order. Identified lesions were prepared and validated. Logistic regression analysis was performed for each method. The sensitivity and specificity values for each method and the combined models were statistically measured using RStudio version 0.97.551. At the enamel level, visual detection was the most sensitive method (0.88), while NILT was the most specific (0.93). NILT scored the highest for sensitivity (0.93) at the dentine level and visual detection scored the highest for specificity (0.88). Visual detection + NILT model was significantly better (p = 0.04) compared to visual detection or NILT alone (df = 1). The visual-NILT combination is a superior model in detecting occlusal caries on permanent teeth. The model provided surplus value in caries detection hence improving the treatment decision-making in occlusal surfaces.
Highlights
There had been a parallel effort to detect caries lesion as early as possible even before the non-cavitated stage along with the development of a quantitative method for caries lesion detection (Pitts, 2004)
All procedures performed in this study were approved by the Ethical Committee of Research Management Institute (RMI), Universiti Teknologi MARA (UiTM) (600-IRMI (5/1/6) REC/115/17)
The results demonstrated a potential significance of the near-infrared light transillumination (NILT) (DIAGNOcam®) model for detecting occlusal caries with high sensitivity to conventional models
Summary
There had been a parallel effort to detect caries lesion as early as possible even before the non-cavitated stage along with the development of a quantitative method for caries lesion detection (Pitts, 2004). This effort has been driven by the acceptance that early identification provides better estimations of the disease and improves the possibility for successful preventive intervention. From a clinical perspective, this is an arguable statement as a low diagnostic threshold may lead to the detection of discoloured surfaces, increasing false-positive diagnosis (Nyvad, 2004). The use of bitewing radiographs provides supportive information to complete the clinical diagnosis in proximal and occlusal tooth surfaces (Hintze et al, 1998; Espelid et al, 2003; Schaefer et al, 2018)
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