Validation of AI-Based Cephalometric Analysis in Orthodontics

Validation of Artificial Intelligence-Driven Cephalometric Analysis as a Reliable Tool for Orthodontic Diagnosis and Treatment Planning

Status

Not yet recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07315152

Acronym

AI-CEPH

Enrollment

Registered

2026-01-02

Start date

2026-05-31

Completion date

2028-06-30

Last updated

2026-01-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Malocclusion

Keywords

Treatment planing Orthodontics cephalometric analysis

Brief summary

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_TESTArtificial Intelligence-Driven Cephalometric Analysis

Cephalometric analysis performed using AI software, compared with manual tracings for validation of accuracy in orthodontic diagnosis and treatment planning.

Study design

Observational model

OTHER

Time perspective

CROSS_SECTIONAL

Eligibility

Sex/Gender

ALL

Age

12 Years to 30 Years

Healthy volunteers

Yes

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.

Design outcomes

Primary

Measure	Time frame	Description
Accuracy of AI-driven cephalometric analysis	Day 1	Comparison of cephalometric measurements obtained using AI software with manual tracings to evaluate the accuracy and reliability of AI-driven analysis in orthodontic diagnosis.

Countries

Egypt

Contacts

Primary ContactHamdi K Khalaf, BDs

hamdikhalaf5@gmail.com201025135711

Backup ContactNoha S Mohammed, BDs

nohaelkhateeb32@gmail.com201148294667

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026