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AI-Based Prediction of Root Coverage Outcome From Intraoral Photographs

NCT07775365 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 36

Last updated 2026-08-20

No results posted yet for this study

Summary

This study evaluates whether the outcome of root coverage surgery can be predicted from a preoperative intraoral photograph. Adults with Cairo RT1,RT2 or RT3 gingival recessions treated with a coronally advanced flap and a connective tissue graft are followed for six months. Standardised photographs and clinical measurements are obtained before surgery and at each follow-up visit. A deep learning model is developed to predict the surgical outcome from the preoperative photograph and baseline clinical variables, and its performance is compared with the outcome measured clinically at six months. The model does not influence treatment decisions.

Conditions

  • Gingival Recessions

Interventions

PROCEDURE

Coronally advanced flap with subepithelial connective tissue graft

A coronally advanced flap is raised over the recession defect and a subepithelial connective tissue graft harvested from the palate is positioned beneath it, after which the flap is sutured coronal to the cemento-enamel junction. Graft thickness, length and width are recorded for each treated site. The procedure was performed as routine clinical care and was not assigned for research purposes.

DIAGNOSTIC_TEST

Deep learning based prediction of root coverage outcome

Preoperative intraoral photographs and baseline clinical variables are analysed by a deep learning model that predicts the outcome of root coverage surgery. The model output is not used in clinical decision making and does not influence treatment; it is compared retrospectively with the outcome measured by the treating periodontist at six months. The same photographs are also used to assign the recession type automatically, which is compared with the clinical assignment.

Sponsors & Collaborators

  • Marmara University

    lead OTHER

Principal Investigators

  • Leyla Kuru, Professor · Marmara University Faculty of Dentistry Department of Periodontology

Eligibility

Min Age
18 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-09-17
Primary Completion
2026-09-17
Completion
2027-09-17

Countries

  • Turkey (Türkiye)

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 NCT07775365 on ClinicalTrials.gov