AI-Based Prediction of Root Coverage Outcome From Intraoral Photographs
2026년 8월 16일 업데이트: Marmara University
Development and Internal Validation of a Deep Learning Model Predicting the Outcome of Root Coverage Surgery From Preoperative Intraoral Photographs: A Prospective Observational Cohort Study
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.
연구 개요
상태
모병
정황
상세 설명
Whether an exposed root surface can be completely covered is the central question in planning mucogingival surgery. The Cairo classification is the current diagnostic standard for that judgement, but assignment of the recession type varies between examiners and prediction of the individual surgical outcome remains largely subjective. In this cohort, consecutive systemically healthy adults with Cairo RT1,RT2 or RT3 gingival recessions are treated by a single operator with a coronally advanced flap combined with a subepithelial connective tissue graft. Recession depth, keratinised tissue width and gingival thickness are recorded at baseline and at three and six months.
Standardised intraoral photographs are obtained at each time point under fixed conditions. A deep learning model is developed to predict the six-month outcome from the preoperative photograph together with baseline clinical variables. Model performance is assessed by discrimination, calibration and prediction error, using the clinical measurement at six months as the reference standard. A secondary analysis examines whether the recession type assigned automatically from the photograph agrees with the type assigned by the examining periodontist. The model is developed and validated internally within this cohort; no external validation set is available. Its output is not shown to the operator and does not influence treatment. Reporting follows the TRIPOD recommendations for prediction model studies.
연구 유형
관찰
등록 (추정된)
36
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 연락처
- 이름: Muhammed F Dogan, Resident
- 전화번호: +905433890065
- 이메일: mfurkandogaan@gmail.com
연구 장소
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Istanbul
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Istanbul, Istanbul, 터키 (Türkiye), 34854
- 모병
- Marmara University Faculty of Dentistry Department of Periodontology
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연락하다:
- Muhammed F Dogan, Resident
- 전화번호: +905433890065
- 이메일: mfurkandogaan@gmail.com
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
예
샘플링 방법
비확률 샘플
연구 인구
The study population consists of systemically healthy adult patients (aged 18-65) presenting to the Department of Periodontology at Marmara University with esthetic concerns or dentin hypersensitivity associated with gingival recession.
The cohort includes individuals diagnosed with Cairo Class RT1 or RT2 (Miller Class I or II) gingival recession defects who are scheduled to undergo mucogingival root coverage surgery.
설명
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.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
코호트 및 개입
그룹/코호트 |
개입 / 치료 |
|---|---|
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Root coverage surgery cohort
Systemically healthy adults aged 18 to 65 years with Cairo RT1,RT2 pr RT3 gingival recessions, treated with a coronally advanced flap combined with a subepithelial connective tissue graft by a single operator and followed for six months.
All participants received the same surgical technique; no comparison group was formed and no participant was assigned to a treatment for the purposes of this study.
Standardised intraoral photographs and clinical measurements were obtained before surgery and at three and six months.
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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.
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.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Accuracy of the model in predicting root coverage at six months
기간: 6 months
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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.
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6 months
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Sensitivity and specificity of the model at the selected decision threshold
기간: 6 months
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Proportion of sites correctly identified by the model among those that achieved the outcome (sensitivity) and among those that did not (specificity), evaluated at the operating point selected on the receiver operating characteristic curve.
Both proportions are reported with 95% confidence intervals.
The reference standard is the clinical measurement made at six months by the treating periodontist, using a periodontal probe from the cemento-enamel junction to the gingival margin.
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6 months
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기타 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Calibration of the model
기간: 6 months
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Agreement between the probability predicted by the model and the frequency observed in the cohort, assessed by the calibration slope and intercept and displayed as a calibration plot.
Discrimination indicates whether the model ranks sites correctly; calibration indicates whether the predicted probabilities are numerically correct, and the two are reported separately because a model may rank well while producing miscalibrated probabilities.
The reference standard is the clinical measurement made at six months.
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6 months
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Agreement between the model-assigned and the clinician-assigned recession type
기간: Baseline
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Proportion of treated sites at which the recession type assigned by the model from the preoperative photograph matches the type assigned by the examining periodontist, reported together with quadratic weighted kappa.
The reference standard is the clinical assignment recorded at baseline according to the criteria of Cairo et al.
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Baseline
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
수사관
- 수석 연구원: Leyla Kuru, Professor, Marmara University Faculty of Dentistry Department of Periodontology
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
2025년 9월 17일
기본 완료 (추정된)
2026년 9월 17일
연구 완료 (추정된)
2027년 9월 17일
연구 등록 날짜
최초 제출
2026년 8월 16일
QC 기준을 충족하는 최초 제출
2026년 8월 16일
처음 게시됨 (실제)
2026년 8월 20일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
2026년 8월 20일
QC 기준을 충족하는 마지막 업데이트 제출
2026년 8월 16일
마지막으로 확인됨
2026년 8월 1일
추가 정보
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