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Recruiting Observational

AI-Based Prediction of Root Coverage Outcome From Intraoral Photographs

NCT07775365 · tracked via the Priya Life Science Turkey tracker
Phase
Observational
Started
2025-09-17
Last updated
2026-08-20

Condition(s) studied

Gingival Recessions

Investigational drug(s) / intervention(s)

Coronally advanced flap with subepithelial connective tissue graftDeep learning based prediction of root coverage outcome

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.

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.

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.

Eligibility

Sex
ALL
Min age
18 Years
Max age
65 Years
Healthy volunteers
Accepted
Inclusion Criteria: * Systemically healthy patients (ASA I or II status) with no contraindications for periodontal surgery. * Adult patients aged 18 to 65 years. * Presence of isolated or multiple gingival recessions classified as Cairo RT1, RT2 or RT3 in the maxilla or mandible. * Patients with good oral hygiene standards, defined as a Full Mouth Plaque Score (FMPS) and Full Mouth Bleeding Score (FMBS) of \< 20% at baseline. * Presence of an identifiable Cemento-Enamel Junction (CEJ) (Crucial for AI segmentation). Exclusion Criteria: * Patients with uncontrolled diabetes, immune system disorders, or pregnant/lactating women. * Teeth with cervical restorations or abrasions that obscure the CEJ. * Malpositioned or rotated teeth that would distort the photographic angle for AI analysis.

Primary outcome measure(s)

  • Accuracy of the model in predicting root coverage at six months — 6 months
    Difference between the root coverage predicted by a model based on preoperative intraoral photographs and baseline clinical characteristics, and the root coverage observed at six months. Root coverage is expressed as the percentage of the baseline recession depth that is covered, calculated as \[(baseline recession depth - six-month recession depth) / baseline recession depth\] × 100, from probing measurements made by the treating periodontist from the cemento-enamel junction to the gingival margin. Predictive accuracy is summarised as the mean absolute error in percentage points across all treated sites.

Trial sites (1)

FacilityCityRegionStatus
Marmara University Faculty of Dentistry Department of Periodontology Istanbul Istanbul Recruiting
Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT07775365 on ClinicalTrials.gov ↗ ← All trials in Turkey