Mandibular TumorNCT06945692
Assessment of Accuracy and Aesthetics Following Automated Mandibular Defect Reconstruction Using AI
A study testing patient specific reconstruction plates in people with Mandibular Tumor, run by Cairo University.
Trial summary
The Aim of the study is to evaluate Accuracy of automated mandibular defect reconstruction using Artificial intelligence and assessing impact on aesthetic and occlusion outcomes using patient-specific reconstruction plates. Read more about this study
- Who is it for?
- Ages 18 to 55 years
- Conditions the study is for
- Mandibular Tumor
- What is being tested?
- patient specific reconstruction plates
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 4 participants
- Where
- No sites listed yet
- Study dates
- 1 May 2025to 1 May 2026
- Phase
- Interventional
- 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 18 to 55 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Patients with mandibular tumors, cysts or any benign disease resulting in mandibular continuity defect.
- Age group: from 18 - 55 years old.
- No sex predilection.
- CTs or CBCTs of only healthy mandibles from an online database and real data.
Who cannot join
- Patients with mandibular malignant lesions.
- Children age group from 2-17.
- CTs Of maxilla.
- Elderly patients to be excluded due to the normal physiologic bony change.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Assessment of Accuracy and Aesthetics Following Automated Mandibular Defect Reconstruction Using Artificial Intelligence: A Case Series Study
The Aim of the study is to evaluate Accuracy of automated mandibular defect reconstruction using Artificial intelligence and assessing impact on aesthetic and occlusion outcomes using patient-specific reconstruction plates.
Read the detailed description
The digital surgical process often requires an expected mandibular reference model. Currently, the common digital surgery process, is to mirror repair or manually look for other similar mandibles for local data fusion and smoothing processing. A more accurate expected reference model is difficult to achieve, time consuming and difficult to promote in clinical practice. Moreover, rapid routing processing often has poor accuracy. For cumulative bilateral lesions, massive lesions, obvious displacement or lesions cross the middle line, there is still no effective method to predict the expected reference model in clinical practice.
The main objective for conducting this study is to propose an improved algorithm to overcome the drawbacks of recent studies using 3D Unet and to test the predictability and clinical value of virtually generated 3d models of defected mandible in real patients.
- Conditions
- Mandibular Tumor
- Being tested
- patient specific reconstruction plates
- Keywords
- Artificial intelligence, Patient specific reconstruction plates
- Medical subject headings
- Mandibular Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
patient specific reconstruction platesProcedure or surgery
Use of patient specific reconstruction plates on the 3-D virtually-generated defect using Artificial Intelligence.
| Study group | Role | What they receive |
|---|---|---|
| Patient specific reconstruction plates | Experimental | Patients with benign lesions indicated for resection and resulting in mandibular continuity defects treated with patient specific reconstruction plates. Receives: Procedure: patient specific reconstruction plates |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy Of the virtually Generated 3D model using AI
The measuring device is the AI model using the Percentage as a unit
Measured: baseline
Accuracy of AI generated model clinically
The measuring device is by Superimposition of both virtual 3-d generated model and real patient CT post operative using software ( blender ) .
( Structural Similarity Index) (SSIM)
Measured: baseline
Secondary outcomes (2)
Aethetic outcome
The measuring device is Facial appearance using a 4-point score
Measured: baseline
Occlusion
The measuring device is Digital occlusion analysis using T-scan and the unit is percentage
Measured: baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Apr 2025
- Study start1 May 2025 (estimated)
- Primary completion1 Apr 2026 (estimated)
- Study completion1 May 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Mandibular TumorStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 4 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Sarah Moustafa Mahmoud Fahmy El-Youtti, Cairo University
- Investigators
- Sarah Moustafa, MSc., Principal investigator, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06945692
- Sponsor's protocol ID
- AI in Mandibular Defects
- Status last verified
- Apr 2025
- First submitted
- 10 Apr 2025
- Last updated
- 25 Apr 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Liang Y, Huan J, Li JD, Jiang C, Fang C, Liu Y. Use of artificial intelligence to recover mandibular morphology after disease. Sci Rep. 2020 Oct 2;10(1):16431. doi: 10.1038/s41598-020-73394-5.
PubMed 33009429van Baar GJC, Forouzanfar T, Liberton NPTJ, Winters HAH, Leusink FKJ. Accuracy of computer-assisted surgery in mandibular reconstruction: A systematic review. Oral Oncol. 2018 Sep;84:52-60. doi: 10.1016/j.oraloncology.2018.07.004. Epub 2018 Jul 20.
PubMed 30115476
Study at a glance
From the registry record, last updated by the sponsor on 25 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessment of Accuracy and Aesthetics Following Automated Mandibular Defect Reconstruction Using Artificial Intelligence: A Case Series Study
- ClinicalTrials.gov ID
- NCT06945692
- Acronym / sponsor ID
- AI in Mandibular Defects
- Conditions
- Mandibular Tumor
- Keywords
- Artificial intelligence, Patient specific reconstruction plates
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 4 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 1 May 2025 (estimated)
- Primary completion
- 1 Apr 2026 (estimated)
- Study completion
- 1 May 2026 (estimated)
- First posted
- 25 Apr 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.
The Aim of the study is to evaluate Accuracy of automated mandibular defect reconstruction using Artificial intelligence and assessing impact on aesthetic and occlusion outcomes using patient-specific reconstruction plates.
Detailed description
The digital surgical process often requires an expected mandibular reference model. Currently, the common digital surgery process, is to mirror repair or manually look for other similar mandibles for local data fusion and smoothing processing. A more accurate expected reference model is difficult to achieve, time consuming and difficult to promote in clinical practice. Moreover, rapid routing processing often has poor accuracy. For cumulative bilateral lesions, massive lesions, obvious displacement or lesions cross the middle line, there is still no effective method to predict the expected reference model in clinical practice.
The main objective for conducting this study is to propose an improved algorithm to overcome the drawbacks of recent studies using 3D Unet and to test the predictability and clinical value of virtually generated 3d models of defected mandible in real patients.
Study design
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patient specific reconstruction plates | Experimental | Procedure: patient specific reconstruction platesPatients with benign lesions indicated for resection and resulting in mandibular continuity defects treated with patient specific reconstruction plates. |
Who may qualify
- Ages
- 18 to 55 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- Patients with mandibular tumors, cysts or any benign disease resulting in mandibular continuity defect.
- Age group: from 18 - 55 years old.
- No sex predilection.
- CTs or CBCTs of only healthy mandibles from an online database and real data.
Key exclusion criteria (4 listed)
- Patients with mandibular malignant lesions.
- Children age group from 2-17.
- CTs Of maxilla.
- Elderly patients to be excluded due to the normal physiologic bony change.
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 |
|---|---|---|
| patient specific reconstruction platesUse of patient specific reconstruction plates on the 3-D virtually-generated defect using Artificial Intelligence. | Procedure or surgery | Patient specific reconstruction plates |
Primary outcome
Accuracy Of the virtually Generated 3D model using AI
Time frame: baseline
The measuring device is the AI model using the Percentage as a unit
Accuracy of AI generated model clinically
Time frame: baseline
The measuring device is by Superimposition of both virtual 3-d generated model and real patient CT post operative using software ( blender ) . ( Structural Similarity Index) (SSIM)
2 secondary outcomes
Aethetic outcome
Time frame: baseline
Occlusion
Time frame: baseline
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 25 Apr 2025.
- Background: PubMed 33009429Liang Y, Huan J, Li JD, Jiang C, Fang C, Liu Y. Use of artificial intelligence to recover mandibular morphology after disease. Sci Rep. 2020 Oct 2;10(1):16431. doi: 10.1038/s41598-020-73394-5.
- Background: PubMed 30115476van Baar GJC, Forouzanfar T, Liberton NPTJ, Winters HAH, Leusink FKJ. Accuracy of computer-assisted surgery in mandibular reconstruction: A systematic review. Oral Oncol. 2018 Sep;84:52-60. doi: 10.1016/j.oraloncology.2018.07.004. Epub 2018 Jul 20.
- Individual participant dataSharing planned: No
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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.
Sarah Moustafa, MSc. principal investigator
Cairo University
Questions about this trial
What is this clinical trial studying?
A study testing patient specific reconstruction plates in people with Mandibular Tumor, run by Cairo University.
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 25 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
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 Sarah Moustafa. Moustafa, MSc. (56794540, sarah.elayoutti@dentistry.cu.edu.eg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy Of the virtually Generated 3D model using AI (time frame: baseline). The study lists 2 primary outcomes in all. 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 NCT06945692, which also lists 2 linked publications.
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 25 Apr 2025.