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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
Sponsor: Cairo University
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