AI-Assisted Colorimetric Diagnosis of Peri-Implant Mucosal Erythema

NCT07349095 | Recruiting

• 1 other identifier: SH9H-2025-196-imp
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

1. 1.Background and Rationale The visual diagnosis of peri-implant mucosal erythema (redness), a key sign of inflammation, is highly subjective and varies significantly among clinicians, leading to inconsistencies in early detection and monitoring of peri-implant diseases. There is a critical need for an objective, quantitative, and reliable tool to standardize this assessment. Recent advances in artificial intelligence (AI) and colorimetric analysis of digital intraoral scans offer a promising solution to this clinical challenge.
2. 2.Primary Objectives
3. 3.Study Design
4. 4.Participants and Methods
5. 5.Key Outcome Measures
6. 6.Significance This study seeks to translate a subjective clinical sign into an objective, AI-powered diagnostic biomarker. If successful, the proposed system could become a valuable decision-support tool in daily practice and clinical research, promoting earlier, more consistent, and standardized monitoring of peri-implant tissue health, ultimately improving patient care.

Conditions

Peri-implant Mucositis

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy of the AI system for detecting peri-implant mucosal erythema, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC).

  The primary outcome is the diagnostic accuracy of the AI-based colorimetric system in classifying an image as showing erythema or not. Accuracy is quantified by the Area Under the Receiver Operating Characteristic Curve (AUC), with expert visual diagnosis serving as the reference standard. The AUC, along with its 95% confidence interval, will be calculated separately for the internal development set and the independent external validation set to assess model performance and generalizability.

  At the completion of image analysis for the external validation set, approximately 3 months after study start

Study Arms (1)

AI-Assisted Diagnostic Evaluation for Peri-Implant Mucosal Erythema

EXPERIMENTAL

Participants in this single-arm study undergo evaluation using the investigational AI-based colorimetric system. The study involves two distinct participant roles: 1) Patient Participants who have previously received intraoral scans contribute their de-identified digital dental images (3D surface files and 2D screenshots) for AI model development and validation. 2) Clinician Participants (including experts, general dentists, and students) take part in a prospective observer study. In a controlled, crossover manner, they diagnose a standardized set of peri-implant mucosal images first without any aid, and then with the assistance of the AI system, which provides an objective color index value and visual bounding boxes around suspected erythematous regions. The primary aim for this arm is to assess the diagnostic accuracy, reliability, and clinical utility of the AI system across both technical (vs. expert reference) and human (clinician performance enhancement) endpoints.

Diagnostic Test: AIa assisted diagnosis

Interventions

AIa assisted diagnosis DIAGNOSTIC_TEST

Participants in this single-arm study undergo evaluation using the investigational AI-based colorimetric system. The study involves two distinct participant roles: 1) Patient Participants who have previously received intraoral scans contribute their de-identified digital dental images (3D surface files and 2D screenshots) for AI model development and validation. 2) Clinician Participants (including experts, general dentists, and students) take part in a prospective observer study. In a controlled, crossover manner, they diagnose a standardized set of peri-implant mucosal images first without any aid, and then with the assistance of the AI system, which provides an objective color index value and visual bounding boxes around suspected erythematous regions. The primary aim for this arm is to assess the diagnostic accuracy, reliability, and clinical utility of the AI system across both technical (vs. expert reference) and human (clinician performance enhancement) endpoints.

AI-Assisted Diagnostic Evaluation for Peri-Implant Mucosal Erythema

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

Consecutive patients aged 18 and above, with single or splinted implant-supported restorations visiting the Department of Oral and Maxillofacial Implantology Shanghai Ninth People's Hospital for regular implant maintenance will be included. Participants were excluded if i) pregnancy or intention to become pregnant; ii) with any systemic diseases/conditions that are contraindications to dental implant treatment; and iii) inability or unwillingness to give written informed consent.

Contact the study team to discuss eligibility requirements. They can help determine if this study is right for you.

Sponsors & Collaborators

• Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University: lead

Study Sites (1)

Department of Oral Maxillofacial Implantology Shanghai Ninth People's Hospital

Shanghai, China

RECRUITING

Central Study Contacts

Junyu Shi, Professor

CONTACT

021 5331 4050; sakyamuni_jin@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: January 9, 2026
• First Posted: January 16, 2026
• Study Start: September 1, 2025
• Primary Completion: January 30, 2026
• Study Completion: February 27, 2026
• Last Updated: January 16, 2026

Record last verified: 2026-01

Locations

CN (1)