Orthodontic Treatment PlanningSMILE-AINCT07133867
AI-Guided Treatment Planning in Orthodontic Patients With Missing Upper Lateral Incisors
An observational study of Orthodontic Treatment Planning and Congenitally Missing Maxillary Lateral Incisors, run by Cairo University at 1 site in Egypt.
Trial summary
This pilot study aims to evaluate the diagnostic accuracy of artificial intelligence (AI) in orthodontic treatment planning for patients with congenitally missing upper lateral incisors. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Orthodontic Treatment Planning, Congenitally Missing Maxillary Lateral Incisors
- How many people
- 110 participants
- Where
- 1 siteEgypt
- Study dates
- 28 Mar 2024to Aug 2026
- 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Orthodontic patients with confirmed diagnosis of congenital absence of one or both maxillary lateral incisors, treated or being treated at the Faculty of Oral and Dental Medicine, Cairo University, and collaborating institutions.
Who may be able to join
- Patients diagnosed with unilateral or bilateral congenitally missing maxillary lateral incisors (confirmed by panoramic radiograph).
- Availability of complete diagnostic records: intraoral photographs, extraoral photographs, cephalometric radiograph, and panoramic radiograph.
- Cases either finished (completed orthodontic treatment) or unfinished (under treatment).
- No prior prosthetic replacement for the missing lateral incisors before initial orthodontic planning.
Who cannot join
- Patients with craniofacial syndromes or cleft lip/palate.
- Cases with incomplete or poor-quality diagnostic records.
- History of previous orthodontic treatment unrelated to the current missing lateral incisor case.
- Multiple missing teeth outside the upper lateral incisor region that could affect treatment planning.
Trial locations and contacts
1 site in 1 country.
Egypt1 site
Faculty of Oral and Dental Medecine -Cairo University
Cairo, Manial, 11553
About this study
Official title: Evaluation of Artificial Intelligence in Planning the Treatment for Cases With Missing Upper Lateral Incisors (A Diagnostic Accuracy Pilot Study)
This pilot study aims to evaluate the diagnostic accuracy of artificial intelligence (AI) in orthodontic treatment planning for patients with congenitally missing upper lateral incisors. The study compares AI-generated treatment recommendations with decisions made by experienced orthodontists regarding two main treatment options: space closure and prosthetic replacement. Orthodontic records, including intraoral and extraoral photographs, panoramic radiographs, and cephalometric analyses, will be collected for each case. Two orthodontists with over 10 years of clinical experience will independently evaluate each case using a treatment decision checklist with predefined cutoff points. AI predictions will then be compared to orthodontists' consensus decisions to determine agreement rates and accuracy. The findings will provide insight into the potential role of AI in supporting complex orthodontic decision-making.
Read the detailed description
Management of congenitally missing maxillary lateral incisors is a frequent clinical challenge in orthodontics, often sparking debate among practitioners regarding the optimal treatment approach. The two primary treatment modalities are orthodontic space closure, in which adjacent teeth (usually canines) are moved into the lateral incisor position, and space opening followed by prosthetic replacement, typically with dental implants or bridges. Each option has distinct advantages and limitations in terms of esthetics, occlusion, periodontal health, and long-term stability, and the decision is influenced by multiple clinical, biological, esthetic, and patient-specific factors.
Artificial intelligence (AI), particularly through machine learning algorithms, has demonstrated high accuracy in other controversial orthodontic decision-making scenarios, such as extraction vs. non-extraction treatment and surgical vs. camouflage approaches. However, its application to lateral incisor agenesis treatment planning has not been thoroughly investigated.
This pilot diagnostic accuracy study will evaluate the performance of an AI-based decision support system in recommending treatment plans for cases with missing maxillary lateral incisors. A dataset of anticipated 100 cases will be compiled, consisting of pre-treatment records including intraoral and extraoral photographs, panoramic radiographs, and cephalometric analyses. two experienced orthodontists will independently review unfinished cases and make a treatment decision-space closure, space opening with prosthetic replacement, or undecided-using a standardized cutoff-points checklist. For finished cases, both pre- and post-treatment records will be analyzed.
A consensus decision will be established when at least two orthodontists agree; if disagreement persists, a third orthodontist will finalize the decision. AI predictions will be compared with orthodontists' consensus decisions to assess diagnostic accuracy, sensitivity, specificity, and agreement rates. This study aims to explore the feasibility of integrating AI tools into complex orthodontic decision-making and to establish a foundation for larger-scale clinical trials.
- Keywords
- Artificial Intelligence, orthodontics, missing lateral incisor, treatment planning
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Accuracy of AI in Orthodontic Treatment Planning for Missing Maxillary Lateral Incisors
The percentage agreement between AI-generated treatment decisions (space closure vs. space opening) and the consensus decisions of experienced orthodontists, based on standardized case records including intraoral photographs, cephalometric radiographs, and panoramic radiographs.
Measured: Within 6 months from case assessment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Aug 2025
- Study start28 Mar 2024
- Primary completionMar 2026 (estimated)
- Study completionAug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Orthodontic Treatment PlanningStudies of the same condition, open and under way.
- More trials run by Cairo 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
- Retrospective
- Enrolment
- 110 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Malak Mohsen Ahmed Elagramy, Cairo University
- Investigators
- Professor (Associate), Study director, orthodontic department-cairo university
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07133867
- Sponsor's protocol ID
- ORTH 7-1-3
- Acronym
- SMILE-AI
- Status last verified
- Aug 2025
- First submitted
- 14 Aug 2025
- Last updated
- 21 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of Artificial Intelligence in Planning the Treatment for Cases With Missing Upper Lateral Incisors (A Diagnostic Accuracy Pilot Study)
- ClinicalTrials.gov ID
- NCT07133867
- Acronym / sponsor ID
- SMILE-AI / ORTH 7-1-3
- Keywords
- Artificial Intelligence, orthodontics, missing lateral incisor, treatment planning
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 110 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 28 Mar 2024 (actual)
- Primary completion
- Mar 2026 (estimated)
- Study completion
- Aug 2026 (estimated)
- First posted
- 21 Aug 2025 (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 pilot study aims to evaluate the diagnostic accuracy of artificial intelligence (AI) in orthodontic treatment planning for patients with congenitally missing upper lateral incisors. The study compares AI-generated treatment recommendations with decisions made by experienced orthodontists regarding two main treatment options: space closure and prosthetic replacement. Orthodontic records, including intraoral and extraoral photographs, panoramic radiographs, and cephalometric analyses, will be collected for each case. Two orthodontists with over 10 years of clinical experience will independently evaluate each case using a treatment decision checklist with predefined cutoff points. AI predictions will then be compared to orthodontists' consensus decisions to determine agreement rates and accuracy. The findings will provide insight into the potential role of AI in supporting complex orthodontic decision-making.
Detailed description
Management of congenitally missing maxillary lateral incisors is a frequent clinical challenge in orthodontics, often sparking debate among practitioners regarding the optimal treatment approach. The two primary treatment modalities are orthodontic space closure, in which adjacent teeth (usually canines) are moved into the lateral incisor position, and space opening followed by prosthetic replacement, typically with dental implants or bridges. Each option has distinct advantages and limitations in terms of esthetics, occlusion, periodontal health, and long-term stability, and the decision is influenced by multiple clinical, biological, esthetic, and patient-specific factors.
Artificial intelligence (AI), particularly through machine learning algorithms, has demonstrated high accuracy in other controversial orthodontic decision-making scenarios, such as extraction vs. non-extraction treatment and surgical vs. camouflage approaches. However, its application to lateral incisor agenesis treatment planning has not been thoroughly investigated.
This pilot diagnostic accuracy study will evaluate the performance of an AI-based decision support system in recommending treatment plans for cases with missing maxillary lateral incisors. A dataset of anticipated 100 cases will be compiled, consisting of pre-treatment records including intraoral and extraoral photographs, panoramic radiographs, and cephalometric analyses. two experienced orthodontists will independently review unfinished cases and make a treatment decision-space closure, space opening with prosthetic replacement, or undecided-using a standardized cutoff-points checklist. For finished cases, both pre- and post-treatment records will be analyzed.
A consensus decision will be established when at least two orthodontists agree; if disagreement persists, a third orthodontist will finalize the decision. AI predictions will be compared with orthodontists' consensus decisions to assess diagnostic accuracy, sensitivity, specificity, and agreement rates. This study aims to explore the feasibility of integrating AI tools into complex orthodontic decision-making and to establish a foundation for larger-scale clinical trials.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Orthodontic patients with confirmed diagnosis of congenital absence of one or both maxillary lateral incisors, treated or being treated at the Faculty of Oral and Dental Medicine, Cairo University, and collaborating institutions.
Key inclusion criteria (4 listed)
- Patients diagnosed with unilateral or bilateral congenitally missing maxillary lateral incisors (confirmed by panoramic radiograph).
- Availability of complete diagnostic records: intraoral photographs, extraoral photographs, cephalometric radiograph, and panoramic radiograph.
- Cases either finished (completed orthodontic treatment) or unfinished (under treatment).
- No prior prosthetic replacement for the missing lateral incisors before initial orthodontic planning.
Key exclusion criteria (4 listed)
- Patients with craniofacial syndromes or cleft lip/palate.
- Cases with incomplete or poor-quality diagnostic records.
- History of previous orthodontic treatment unrelated to the current missing lateral incisor case.
- Multiple missing teeth outside the upper lateral incisor region that could affect treatment planning.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Diagnostic Accuracy of AI in Orthodontic Treatment Planning for Missing Maxillary Lateral Incisors
Time frame: Within 6 months from case assessment
The percentage agreement between AI-generated treatment decisions (space closure vs. space opening) and the consensus decisions of experienced orthodontists, based on standardized case records including intraoral photographs, cephalometric radiographs, and panoramic radiographs.
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 21 Aug 2025.
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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. This study is not recruiting at the moment.
Professor (Associate) study director
orthodontic department-cairo 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 Orthodontic Treatment Planning and Congenitally Missing Maxillary Lateral Incisors, run by Cairo 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: under way, not looking for participants, as of the sponsor's last update on 21 Aug 2025. 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?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic Accuracy of AI in Orthodontic Treatment Planning for Missing Maxillary Lateral Incisors (time frame: Within 6 months from case assessment). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Aug 2025.