Diagnostic Accuracy of a Deep Learning Framework for Automated Evaluation of Root Canal Obturation Quality From Periapical Radiographs

Starting soon · Not applicable

Conditions studied: Root Canal Treatment, Obturation Quality

In brief

This study aims to develop and evaluate an artificial intelligence (AI)-based system that can automatically assess the quality of root canal fillings using dental X-ray images. The AI system will analyze important features of the filling, including its length, uniformity, and shape, and classify the treatment quality as acceptable or needing improvement. The study will use previously collected, anonymized dental X-ray images of teeth that have received root canal treatment. Experienced dental specialists will evaluate these images to provide a reference standard, which will be compared with the AI system's results. The goal of this research is to determine whether AI can provide a reliable and consistent method for evaluating root canal treatment outcomes. In the future, such technology may help dentists make more accurate decisions, improve treatment evaluation, and contribute to better patient care.

Key facts

Study ID

NCT07684482

Run by

Cairo University

People needed

490

Starts

2026-08-01

Expected to finish

2027-07-01

Last updated by the study team

2026-07-06

Who can join

Age: 18 and older, up to 60. Sex: any. Healthy volunteers: not accepted.

Full record on ClinicalTrials.gov

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