PubMed · 14948201
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O MULLER. 1952. [The interdental margin].. https://pubmed.ncbi.nlm.nih.gov/14948201/
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Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.
The reduction in caries prevalence has not occurred uniformly for all dental surfaces. As the occlusal surfaces are still the most likely sites for the development of lesions, new methods of diagnosis are still being evaluated. This study compared a laser fluorescence (LF) system (DIAGNOdent) with the Ekstrands visual system for in vitro detection of occlusal caries. A total of 57 extracted molars with macroscopically intact occlusal surfaces were selected. Two-examiners assessed 110 sites by visual inspection (VI) and LF. After ten days from the first measurement, all teeth were re-evaluated through the same methods by each examiner. Caries extension was histologically assessed (X 40). The methods were compared by means of sensitivity, specificity, intra- and inter-examiner reproducibility and area under the ROC curve. The kappas test showed good intra- and inter-examiner reproducibility for both methods. VI and LF showed similar sensitivities for both examiners, however, VI showed higher specificities than LF. The overall analysis, as demonstrated by the area under the ROC curve, showed that VI had a better performance than the LF device. It was concluded that the Ekstrands visual system is more reliable than the LF device. LF should be considered only as an adjuvant for occlusal caries diagnosis.