RecruitingNCT05888935

Detection of Periapical Lesions on Dental Panoramic Images Based on Artificial Intelligence Using Cone Beam Computed Tomography

Sponsor: Centre Hospitalier Régional Metz-Thionville

Trial Details

Condition	Periapical Diseases
Status	Recruiting
Participants	2,000
Est. Completion	1 Dec 2027
Last Updated	24 June 2026

Primary Outcome

Artificial Intelligence software performance

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: * Patients who have had CBCT and panoramic dental imaging with less than 3 months between the two examinations Exclusion Criteria: * Patients who refused to participe in the study.

Trial Sites

Countries

France

View Registry Entry

Related Analysis

AI-Powered Detection of Periapical Lesions on Panoramic Radiographs: French Multicentre Study Seeks to Redefine Diagnostic Thresholds in Endodontic Imaging

A French multicentre study is enrolling 2,000 patients to validate a deep learning algorithm capable of detecting periapical lesions on dental panoramic radiographs, using CBCT as the reference standard. With panoramic imaging detecting as few as 20% of periapical lesions compared to 69% for CBCT, an accurate AI-assisted tool could transform diagnostic workflows in general dental practice worldwide.

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