ArticleScientific reports2026
A validation of 3D imaging for non-invasive, tech-assisted diagnosis of caries and erosive tooth wear in primary teeth - an in vitro study.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This in vitro study set out to assess the agreement of 3D-colored digital dental images in detecting occlusal caries and erosive tooth wear (ETW) in primary teeth, by comparing indirect digital assessments with conventional direct visual examinations. Extracted primary molars with varying degrees of caries severity and ETW were mounted on modeling wax, with the crowns exposed for the assessments. Then, two independent experiments were conducted. The first analyzed occlusal caries in 233 extracted primary molars using the International Caries Detection and Assessment System (ICDAS, scores 0-6), while the second evaluated ETW in 164 primary molars using the Basic Erosive Wear Examination (BEWE, scores 0-3). Direct visual examinations were performed under standardized lighting, dryness and magnification. For the indirect assessment, teeth were scanned using an intraoral scanner (TRIOS 4, 3Shape), and digital images were assessed via 3Shape Unite software. Agreement between methods was determined using kappa statistics and percent agreement. Substantial agreement was found for caries detection (Kappa = 0.64; 71% agreement) with the highest concordance at ICDAS scores 4-6 (> 90%) and the lowest at score 0 (36%). For ETW, substantial agreement was also observed Kappa = 0.58; 80% agreement), with highest concordance at BEWE score 2 (99%). The digital method tended to overestimate scores 0 and 1 and underestimate scores 2 and 3 in caries detection. 3D-colored digital images demonstrated substantial agreement with conventional visual methods for detecting both dental caries and ETW in primary teeth. These results highlight its promise as a practical and non-invasive adjunct in pediatric dental diagnostics, with potential to enhance early detection and support the integration of digital tools into routine and remote oral health care.
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