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NCT07587060

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

Sponsor: Cairo University

View on ClinicalTrials.gov

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.

Key Details

Gender

All

Age Range

18 Years - 65 Years

Study Type

OBSERVATIONAL

Enrollment

207

Start Date

2026-06-01

Completion Date

2027-09-01

Last Updated

2026-05-14

Healthy Volunteers

No

Locations (1)

Faculty of Dentistry, Cairo University

Cairo, Cairo Governorate, Egypt