MalocclusionAI-CEPHNCT07315152
Validation of AI-Based Cephalometric Analysis in Orthodontics
An observational study of Malocclusion, run by Al-Azhar University at 1 site in Egypt.
Trial 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. Read more about this study
- Who is it for?
- Ages 12 to 30 yearsHealthy volunteers can take part
- Conditions the study is for
- Malocclusion
- What is being tested?
- Artificial Intelligence-Driven Cephalometric Analysis
- How many people
- 55 participants
- Where
- 1 siteEgypt
- Study dates
- May 2026to Jun 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 12 to 30 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Study population: consists of orthodontic patients aged 12 to 40 years who require orthodontic diagnosis and treatment planning. Participants will have good-quality lateral cephalometric radiographs taken using standardized imaging protocols. The study includes both male and female patients with no previous orthodontic treatment.
Who may be able to join
- 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.
Who cannot join
- Periodontally compromised patients.
- Presence of systemic diseases.
- Drug dependencies.
- Uncooperative patients.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Egypt1 site
Faculty of Dentistry, Al-Azhar University
Asyut, Asyut Governorate, 71524
Hamdi K Ali, BDs, 201025135711, hamdikhalaf5@gmail.com
Noha S Mohammed, BDs, 201148294667, nohaelkhateeb32@gmail.com
About this study
Official title: Validation of Artificial Intelligence-Driven Cephalometric Analysis as a Reliable Tool for Orthodontic Diagnosis and Treatment Planning
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.
Read the 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.
- Conditions
- Malocclusion
- Being tested
- Artificial Intelligence-Driven Cephalometric Analysis
- Keywords
- Treatment planing Orthodontics cephalometric analysis
- Medical subject headings
- Malocclusion
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-Driven Cephalometric AnalysisDiagnostic test
Cephalometric analysis performed using AI software, compared with manual tracings for validation of accuracy in orthodontic diagnosis and treatment planning.
| Study group | Role | What they receive |
|---|---|---|
| Patients | Patients undergoing routine cephalometric analysis, used to validate AI-driven measurements against manual tracings. Receives: Diagnostic Test: Artificial Intelligence-Driven Cephalometric Analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AI-driven cephalometric analysis
Comparison of cephalometric measurements obtained using AI software with manual tracings to evaluate the accuracy and reliability of AI-driven analysis in orthodontic diagnosis.
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Jan 2026
- Study startMay 2026 (estimated)
- Primary completionJun 2027 (estimated)
- Study completionJun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for MalocclusionStudies of the same condition, open and under way.
- More trials run by Al-Azhar UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 55 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Al-Azhar University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hamdi Khalaf Ali, Al-Azhar University
- Investigators
- Mohammed A Mohammed, DDs,phD, Principal investigator, Al-Azhar University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07315152
- Sponsor's protocol ID
- AI-CEPH-VAL-01
- Acronym
- AI-CEPH
- Status last verified
- Dec 2025
- First submitted
- 18 Dec 2025
- Last updated
- 7 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: The decision to share individual participant data has not yet been finalized. Considerations regarding participant confidentiality, data protection regulations, and ongoing study procedures may affect the ability to share IPD in the future.
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.
PubMed 31853586
Study at a glance
From the registry record, last updated by the sponsor on 7 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of Artificial Intelligence-Driven Cephalometric Analysis as a Reliable Tool for Orthodontic Diagnosis and Treatment Planning
- ClinicalTrials.gov ID
- NCT07315152
- Acronym / sponsor ID
- AI-CEPH / AI-CEPH-VAL-01
- Conditions
- Malocclusion
- Keywords
- Treatment planing Orthodontics cephalometric analysis
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 55 participants (estimated)
- Lead sponsor
- Al-Azhar UniversityUniversity, hospital or other
- Study start
- May 2026 (estimated)
- Primary completion
- Jun 2027 (estimated)
- Study completion
- Jun 2028 (estimated)
- First posted
- 2 Jan 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients | – | Diagnostic Test: Artificial Intelligence-Driven Cephalometric AnalysisPatients undergoing routine cephalometric analysis, used to validate AI-driven measurements against manual tracings. |
Who may qualify
- Ages
- 12 to 30 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
- Study population
- consists of orthodontic patients aged 12 to 40 years who require orthodontic diagnosis and treatment planning. Participants will have good-quality lateral cephalometric radiographs taken using standardized imaging protocols. The study includes both male and female patients with no previous orthodontic treatment.
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (4 listed)
- Periodontally compromised patients.
- Presence of systemic diseases.
- Drug dependencies.
- Uncooperative patients.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence-Driven Cephalometric AnalysisCephalometric analysis performed using AI software, compared with manual tracings for validation of accuracy in orthodontic diagnosis and treatment planning. | Diagnostic test | Patients |
Primary outcome
Accuracy of AI-driven cephalometric analysis
Time frame: 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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jan 2026.
- Background: PubMed 31853586Kunz 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.
- Scientific and biomedical literature related to orthodontics and artificial intelligence.Link provided by the sponsor.
- Individual participant dataSharing planned: Undecided. The decision to share individual participant data has not yet been finalized. Considerations regarding participant confidentiality, data protection regulations, and ongoing study procedures may affect the ability to share IPD in the future.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Mohammed A Mohammed, DDs,phD principal investigator
Al-Azhar University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Malocclusion, run by Al-Azhar University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 7 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hamdi K Khalaf, BDs (201025135711, hamdikhalaf5@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of AI-driven cephalometric analysis (time frame: Day 1). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07315152, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Jan 2026.