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

NCT07684482 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 490

Last updated 2026-07-06

No results posted yet for this study

Summary

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.

Conditions

  • Root Canal Treatment
  • Obturation Quality

Interventions

DIAGNOSTIC_TEST

Deep learning model

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.

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-08-01
Primary Completion
2026-12-30
Completion
2027-07-01

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07684482 on ClinicalTrials.gov