Validation of AI-Based Cephalometric Analysis in Orthodontics
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial Intelligence-Driven Cephalometric Analysis.
- Who it may be relevant to
- Registry conditions: Malocclusion. Basic parameters: 12 years — 30 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Egypt
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Validation of Artificial Intelligence-Driven Cephalometric Analysis as a Reliable Tool for Orthodontic Diagnosis and Treatment Planning
Overview
This study is designed to evaluate whether artificial intelligence can analyze cephalometric images in orthodontics as a reliable tool for diagnosis and treatment planning. The study will include orthodontic patients who need cephalometric evaluation. Participants will have their X-ray images analyzed using both the AI system and traditional manual methods. The study will compare the results to see how closely the AI measurements match the standard measurements. This information may help patients, families, and health care providers understand how AI can support orthodontic diagnosis and treatment planning.
Detailed description
Cephalometric analysis is a fundamental diagnostic tool in orthodontics. Conventional manual tracing is time-consuming and operator-dependent, while artificial intelligence-based software has been introduced to improve efficiency and consistency.
This observational study will evaluate and compare manual and AI-assisted cephalometric analyses using lateral cephalometric radiographs. Selected angular and linear measurements will be assessed, and the agreement between the two methods will be statistically analyzed to determine accuracy and reliability.
Interventions
- Diagnostic test Artificial Intelligence-Driven Cephalometric Analysis
Cephalometric analysis performed using AI software, compared with manual tracings for validation of accuracy in orthodontic diagnosis and treatment planning.
Primary outcome measures
- Accuracy of AI-driven cephalometric analysis [Time frame: Day 1]
Eligibility criteria
Inclusion criteria
- No systemic disease.
- Not receiving medical treatment that could interfere with bone metabolism.
- Good level of oral hygiene.
- No periodontal disease or radiographic evidence of bone loss.
Exclusion criteria
- Periodontally compromised patients.
- Presence of systemic diseases.
- Drug dependencies.
- Uncooperative patients.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Other
Study locations
Egypt · 1 center
- Faculty of Dentistry, Al-Azhar University — Asyut
Publications
- Kunz F, Stellzig-Eisenhauer A, Zeman F, Boldt J. Artificial intelligence in orthodontics : Evaluation of a fully automated cephalometric analysis using a customized convolutional neural network. J Orofac Orthop. 2020 Jan;81(1):52-68. doi: 10.1007/s00056-019-00203-8. Epub 2019 Dec 18. PMID 31853586
Identifiers
NCT: NCT07315152 · AI-CEPH-VAL-01