Photography-based dental plaque detection and report generation among preschool children using PlaqueSAM

Dental plaque is the primary etiological factor for common oral diseases such as dental caries and gingivitis, particularly affecting susceptible populations including children. Preventing plaque-induced dental diseases in paediatric patients remains a global challenge as certain plaque regions are often missed during daily cleaning. Early detection and removal of plaque are essential but often difficult to achieve consistently. A routine monitoring tool that visualizes plaque accumulation on primary teeth could allow parents to actively track their children's oral health, enabling timely prevention and intervention for dental caries and periodontal diseases. Inspired by these, we present PlaqueSAM, an automatic plaque detection system using intraoral photographs captured by smartphones. By uploading six guided images assisted with alignment overlays, PlaqueSAM can generate a comprehensive plaque detection report with visual references. The PlaqueSAM was developed using 3,402 prospectively collected intraoral photographs from 567 preschool children across 11 kindergartens in Hong Kong using a three-stage training strategy based on a multi-task learning paradigm. The performance of PlaqueSAM was quantitatively evaluated on 81 children, achieving sensitivity, specificity, and accuracy of 76.58%, 82.47%, and 79.60%, respectively. This system demonstrates superior plaque detection capabilities without requiring disclosing agents or plastic retractors typically used by dental professionals, making it highly practical for home use to maintain oral hygiene and reduce the risk of common oral diseases. By enabling dynamic monitoring of daily plaque accumulation and cleaning, PlaqueSAM has significant potential to advance teledentistry, promoting children's oral health remotely, conveniently, and at lower cost.