NCT07404007

Detection of Proximal Caries in Bitewing Radiography Using Artificial Intelligence

Detection of Proximal Caries in Bitewing Radiography Using Artificial Intelligence - A Diagnostic Clinical Study

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 2,000 (actual)
• Sponsor: Cairo University · Academic / Other
• Sex: All
• Age: 18 Years – 70 Years
• Healthy volunteers: Accepted

Summary

Using a sequence of bitewing radiographs, Artificial intelligence assists in identifying interproximal caries. For the identification of dental caries in bitewing, periapical, and panoramic radiographs, a trained deep learning network will be created This study aimed to investigate the reliability of a novel Artificial Intelligence model based on deep learning in the detection of Proximal Caries using Digital Bitewing Radiographs. (BW).

Conditions

• Proximal Caries
• Tooth Caries

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Artificial Intelligence (AI): Deep learning that is applied in Diagnosis of the proximal Caries	Artificial intelligence was used as a deep-learning diagnostic tool to detect proximal caries on digital bitewing radiographs. The system analyzed images and generated probability scores and visual markers for suspected lesions. Its performance was compared with expert examiner diagnoses as the reference standard. AI results were used for evaluation only and did not influence patient treatment decisions.
DIAGNOSTIC_TEST	Manual annotation of Digital Bitewing Radiograph by human experts	Digital bitewing radiographs were manually annotated by calibrated human experts to identify the presence and location of proximal caries. Annotations were performed using standardized diagnostic criteria and dedicated imaging software to mark suspected lesions. These expert markings served as the reference standard for comparison with the artificial intelligence outputs. Inter-examiner agreement was assessed, and disagreements were resolved by consensus.

Timeline

• Start date: 2023-01-15
• Primary completion: 2025-09-15
• Completion: 2025-12-01
• First posted: 2026-02-11
• Last updated: 2026-02-11

Locations

1 site across 1 country: Egypt