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Development and Diagnostic Accuracy of a Deep Learning Model for Root Canal Curvature Analysis in Mandibular Molars Using CBCT Scans: A Diagnostic Accuracy Study

NCT07587060 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 207

Last updated 2026-05-14

No results posted yet for this study

Summary

Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve treatment outcomes. This study aims to develop and evaluate the diagnostic accuracy of a deep learning model for analyzing root canal curvature angles in mandibular molars from CBCT scans, compared to human expert evaluations. The model will leverage advanced AI techniques to segment and measure curvatures objectively, addressing limitations in manual interpretation, potentially standardizing case difficulty assessments and aiding clinical decision-making.

Conditions

  • Accuracy of Root Canal Curvature Analysis

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Eligibility

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

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-09-01
Completion
2027-09-01

Countries

  • Egypt

Study Locations

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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 NCT07587060 on ClinicalTrials.gov