Clinical Research Directory

Diagnostic Accuracy of Oral Images, OPGs, and Questionnaires vs. Clinical Assessment for Periodontal Disease

Sponsor: Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University

Summary

This is a multi-center, cross-sectional diagnostic study aimed at evaluating the accuracy of various non-invasive methods-including self-reported questionnaires, intra-oral photographs, smartphone images, intraoral scans (IOS), and orthopantomographs (OPGs)-in detecting periodontal health and disease, compared to clinical periodontal examination as the gold standard. The study will enroll 2,000 subjects across five centers, representing the full spectrum of periodontal conditions (health, gingivitis, and periodontitis stages I-IV). Participants will undergo a standardized clinical examination, radiographic imaging, and complete validated questionnaires. Machine learning models (e.g., HC-Net+ for OPGs and DLM for oral image) will be used to analyze images and integrate data domains. The primary outcome is the diagnostic accuracy (sensitivity, specificity, AUROC) of each method alone and in combination for classifying periodontal status. The study aims to validate and refine AI-based tools for scalable, efficient periodontal screening in clinical and community settings.

Official title: Diagnostic Accuracy of Oral Images, Orthopantomographs (OPGs) and Self-Reported Questionnaires vs. Clinical Assessment for Detecting Periodontal Health and Disease: a Multi-center Diagnostic Study

Key Details

Conditions

Locations (1)