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

What this study involves

The registry does not currently label this study as recruiting. Ask about its status before planning a screening visit.

Study type

Observational

Phase

Not applicable / not listed

Age range

18 years - 65 years

Sex eligible

All sexes

Healthy volunteers

Not accepted

Participants

207 Estimated

These are starting points, not an eligibility decision. The research team must review the full requirements.

About the research

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.

Who may be able to participate?

The list below is the sponsor’s full registry wording. It can include conditions, prior treatment, test results and other requirements. A match in search does not mean you qualify.

Inclusion Criteria:

• CBCT scans of mandibular molars of Egyptian patients aging from 18 to 65 years old
• Small Field of view (FOV) including maximum a quadrant
• Voxel size not larger than 2mm
• Mandibular molars showing complete root formation
• Carious or non-carious teeth
• Absence of artifacts, dental implants in the adjacent teeth

Exclusion Criteria:

• Mandibular first and second molars with developmental anomalies, external or internal root resorption, root canal calcification, previous root canal treatment, post restorations, and/or root caries
• CBCT images of sub-optimal quality or artifacts/high scatter interfering with proper assessment

Study population

The accepted sample size (n) will be 207, when the accuracy is (90.48%) and marginal error (4 %) by adopting confidence interval (95%), using Staskingdom calculator.

Treatment, groups and participation

The registry may describe treatments and study duration without a complete visit calendar. Ask the study team for the exact schedule, procedures, risks, costs and alternatives. Keep your usual care plan unless your treating clinician tells you otherwise.

Assignment

Not reported

Masking

Not reported

What researchers are measuring

Outcome measures describe what is being studied. They are not proof that a treatment works.

Primary measures

Research locations (1)

The overall study status and a local site’s status can differ. Confirm that location’s availability before traveling.

1 locations

Study team and timeline

Lead sponsor

Cairo University

Study start

Nov 6, 2026 Actual

Primary completion

Sep 1, 2027 Estimated

Study completion

Sep 1, 2027 Estimated

First posted

May 14, 2026 Actual

Last updated

Nov 10, 2026 Actual

Official study contacts

No central contact is listed. Check the locations and the official record.