AI-Based Detection of Dental Caries in Children

NCT06984029 | Not Yet Recruiting

• 1 other identifier: AI-Caries-Detect-V1
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the effects of an artificial intelligence (AI)-based caries detection system on the diagnosis and categorization of dental caries in pediatric patients. The purpose of this research is to better understand how AI may help improve the accuracy and reliability of early dental caries detection compared to traditional clinical examination methods. Participants in this study will be pediatric patients aged 6-9 years, and they will undergo clinical evaluations for dental caries. The study will compare the AI system's performance to conventional clinical examination in terms of sensitivity, specificity, and overall diagnostic accuracy. The progress of participants will be monitored over a period of six months, with regular assessments of their caries detection results. The study will assess the effectiveness, reproducibility, and diagnostic accuracy of the AI model. Throughout the study, participants will be closely monitored by dental healthcare providers to ensure their safety and well-being. Participants and their guardians are encouraged to communicate any concerns or questions with the study team.

Conditions

Dental Caries

Keywords

Dental Caries Detection; Pediatric Dentistry; Machine Learning in Dentistry; Pediatric Oral Health; Artificial Intelligence-Based Diagnostics; Caries Classification; Artificial Intelligence in Dentistry

Outcome Measures

Primary Outcomes (1)

• Diagnostic accuracy of the AI model

  Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of the AI-based model in detecting dental caries in pediatric patients.

  Within 6 months of enrollment

Secondary Outcomes (1)

• Inter-examiner reliability

  Within 6 months

Eligibility Criteria

• Age: 6 Years - 9 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)
• Sampling Method: Non-Probability Sample

Study Population

The study will include children aged 6 to 9 years attending the Pediatric Dentistry Department at Cairo University. Participants will be selected based on the presence of suspected dental caries and their ability to cooperate during intraoral imaging and examination procedures.

You may qualify if:

• Pediatric patients aged 6-9 years
• Presence of at least one decayed tooth identified during initial screening
• Cooperative behavior, allowing for intraoral imaging and clinical examination

You may not qualify if:

• Patients with systemic diseases or conditions affecting oral health
• Uncooperative patients who cannot complete the examination
• Patients with severe dental anomalies or extensive restorations that interfere with caries detection

Sponsors & Collaborators

• Noura Nageh Ramadan Ahmed: lead

Study Sites (1)

Pediatric Dentistry Department, Faculty of Dentistry, Cairo University

Cairo, Egypt

Location

Related Publications (2)

• Albano D, Galiano V, Basile M, Di Luca F, Gitto S, Messina C, Cagetti MG, Del Fabbro M, Tartaglia GM, Sconfienza LM. Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review. BMC Oral Health. 2024 Feb 24;24(1):274. doi: 10.1186/s12903-024-04046-7.

  PMID: 38402191 BACKGROUND

• Ahmed WM, Azhari AA, Fawaz KA, Ahmed HM, Alsadah ZM, Majumdar A, Carvalho RM. Artificial intelligence in the detection and classification of dental caries. J Prosthet Dent. 2025 May;133(5):1326-1332. doi: 10.1016/j.prosdent.2023.07.013. Epub 2023 Aug 26.

  PMID: 37640607 BACKGROUND

MeSH Terms

Conditions

Dental Caries

Condition Hierarchy (Ancestors)

Tooth Demineralization; Tooth Diseases; Stomatognathic Diseases

Central Study Contacts

NOURA NAGEH RAMADAN

CONTACT

+201002697772; dr.nouranageh@gmail.com

Hala Mohey Eldin

CONTACT

+20 100 145 9467; hala.mohyeldin@dentistry.cu.edu.eg

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Master's Student, Faculty of Dentistry, Cairo University

Study Record Dates

• First Submitted: May 14, 2025
• First Posted: May 22, 2025
• Study Start: June 1, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): July 1, 2026
• Last Updated: May 28, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

EG (1)