Comparison of quantitative light-induced fluorescence and near-infrared intraoral scanner imaging for proximal caries...

Proximal caries detection remains challenging because early lesions are often inaccessible to visual inspection and bitewing radiography exposes patients to ionizing radiation. Quantitative light-induced fluorescence (QLF) and near-infrared imaging integrated into intraoral scanners are proposed as non-ionizing adjuncts. This study compared the diagnostic performance of a handheld QLF device (QrayPen C, Aiobio) and an intraoral scanner with near-infrared imaging (NIRI) (iTero Element 5D, Align Technology) for proximal caries across clinically relevant ICCMS radiographic thresholds.

In this single-center comparative diagnostic accuracy study, 66 adults contributed 297 posterior proximal sites. Each site was assessed using QrayPen (QS score, 0-3) and the iTero Element 5D near-infrared imaging system (NIRI score, 0-3). Bitewing radiographs were scored according to the International Caries Classification and Management System (ICCMS) and served as the reference standard. Diagnostic accuracy was evaluated at three pre-specified thresholds: any caries (R0 vs. R1-R6), dentin involvement (R0-R2 vs. R3-R6), and deeper dentin involvement (R0-R3 vs. R4-R6). The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and predictive values were calculated. Statistical significance was set at p < 0.05.

For any caries, AUCs were similar for QS and NIRI (0.729 vs. 0.727; p = 0.902). At the pre-specified cut-off (score ≥ 1), QS showed higher specificity than NIRI (88.1% vs. 78.2%), while sensitivities were comparable (54.7% vs. 61.1%). For dentin involvement (cut-off ≥ 2), AUC was 0.909 for QS and 0.896 for NIRI (p = 0.605); both methods showed sensitivity of 81.8%, with specificity of 95.5% for QS and 93.9% for NIRI. For radiographically deeper dentin involvement (cut-off = 3), NIRI demonstrated a slightly higher AUC than QS (0.978 vs. 0.961; p = 0.036); sensitivity/specificity were 72.2%/96.4% for QS and 83.3%/97.1% for NIRI. QS and NIRI scores were strongly correlated (Spearman ρ = 0.735; p < 0.001) with substantial ordinal agreement (linear-weighted κ = 0.707).

Both QS (QrayPen C) and NIRI (iTero Element 5D) demonstrated moderate accuracy for identifying any radiographic proximal caries and higher accuracy for radiographically deeper lesions. NIRI showed a small but statistically significant advantage for the radiographically deeper dentin involvement threshold. These non-ionizing methods may be useful adjuncts for proximal caries assessment, but do not eliminate the need for bitewing radiography when radiographic staging information is clinically required. Bitewing radiography under-detects enamel lesions, and site-level analyses did not model within-participant clustering; therefore, estimates should be interpreted as exploratory.