Accuracy of Artificial Intelligence in Fixed Dental Prosthesis DesignNCT07432165
Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis
A study testing Conventional CAD-Based Fixed Dental Prosthesis Design and Artificial Intelligence-Based Fixed Dental Prosthesis Design in people with Accuracy of Artificial Intelligence in Fixed Dental Prosthesis Design, run by October University for Modern Sciences and Arts at 1 site in Egypt.
Trial summary
This in vitro study aims to evaluate the accuracy of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) compared with conventional computer-aided design (CAD) software. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Accuracy of Artificial Intelligence in Fixed Dental Prosthesis Design
- What is being tested?
- Conventional CAD-Based Fixed Dental Prosthesis Design and Artificial Intelligence-Based Fixed Dental Prosthesis Design
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,000 participants
- Where
- 1 siteEgypt
- Study dates
- 15 Jun 2025to 17 Jun 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 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Adults aged 18-65 years Patients with a damaged tooth requiring a fixed dental prosthesis Available digital intraoral scans Adequate occlusal anatomy for analysis of opposing teeth
Who cannot join
- Incomplete or poor-quality digital scans Severe occlusal abnormalities affecting analysis Patients outside the specified age range
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, 1 recruiting
- Recruiting
MSA University
Giza
Modern Sciences and Arts MSA October University for Modern Sciences and Arts, 002-0216672, info@msa.edu.eg
About this study
Official title: Accuracy Assessment of Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis: (An Invitro Study)
This in vitro study aims to evaluate the accuracy of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) compared with conventional computer-aided design (CAD) software. Digital scans of teeth requiring fixed dental prosthesis will be collected and used to generate prosthetic designs using two approaches: human-designed CAD restorations and AI-generated restorations.
The primary outcome is design accuracy assessed using 3D superimposition and Intersection over Union (IOU) percentage. Secondary outcomes include margin detection performance measured using F1 score, precision, and recall. A total sample size of 438 scans will be analyzed.
The study will determine whether AI-generated prosthesis designs demonstrate comparable accuracy to conventional digital designs.
Read the detailed description
This study is designed as an in vitro comparative study to assess the accuracy and performance of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) in comparison with conventional computer-aided design (CAD) software.
Digital scans of patients requiring fixed dental prosthesis will be collected from the production laboratory of the Faculty of Dentistry. Eligible scans will include adults aged 18-65 years with damaged teeth requiring FDP and adequate occlusal anatomy for analysis.
The AI workflow consists of three sequential phases: training (60%), validation (10%), and testing (30%). The AI model will be trained using natural spatial tooth morphology and historical human-designed FDP datasets. The conventional group will consist of FDPs manually designed by experienced dental professionals using CAD software.
Primary Outcome:
The primary outcome is crown design accuracy measured using 3D superimposition analysis and quantified using Intersection over Union (IOU) percentage.
Secondary Outcome:
Margin detection accuracy will be assessed using F1 score, precision, and recall metrics.
Statistical analysis will be performed using MedCalc software (Version 22). Continuous variables will be presented as mean, root mean square, and standard deviation. Comparisons between groups will be conducted using paired t-test with a significance level set at P ≤ 0.05 (two-tailed).
The null hypothesis states that there will be no statistically significant difference between AI-designed and human-designed fixed dental prostheses.
- Being tested
- Conventional CAD-Based Fixed Dental Prosthesis Design, Artificial Intelligence-Based Fixed Dental Prosthesis Design
- Keywords
- Artificial Intelligence, CAD/CAM, Fixed Dental Prosthesis, Dental Crown Design, 3D Superimposition, Deep Learning, Generative Adversarial Network (GAN), Prosthodontics
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Conventional CAD-Based Fixed Dental Prosthesis DesignOther
Also called Human Digital Design
Fixed dental prostheses will be digitally designed using conventional computer-aided design (CAD) software by experienced dental professionals. Designs will be based on occlusal anatomy and patient-specific intraoral scan data. These manually generated digital designs will serve as the comparator for evaluating accuracy against AI-generated designs using 3D superimposition and quantitative accuracy analysis.
Artificial Intelligence-Based Fixed Dental Prosthesis DesignOther
Also called AI Crown Design Model
An artificial intelligence-based automated design system will generate fixed dental prosthesis designs using deep learning algorithms. The AI model will be trained (60%), validated (10%), and tested (30%) on occlusal scan datasets and historical human-designed prostheses. Generated designs will be evaluated for accuracy and marginal precision using 3D superimposition and Intersection over Union (IoU) analysis.
| Study group | Role | What they receive |
|---|---|---|
| Human-Designed Fixed Dental Prosthesis (Conventional CAD) | Other | Fixed dental prostheses will be designed manually using conventional CAD software by experienced dental professionals based on occlusal anatomy and patient-specific scan data. The designs will serve as the control comparator to evaluate accuracy against AI-generated designs using 3D superimposition analysis. Receives: Other: Conventional CAD-Based Fixed Dental Prosthesis Design |
| AI-Designed Fixed Dental Prosthesis | Other | Fixed dental prostheses will be automatically generated using an artificial intelligence-based design system. The AI model will be trained, validated, and tested using occlusal scan datasets and historical human-designed prostheses. The generated designs will be evaluated for accuracy using 3D superimposition and Intersection over Union (IoU) analysis. Receives: Other: Artificial Intelligence-Based Fixed Dental Prosthesis Design |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AI-Designed Fixed Dental Prosthesis Compared to Human-Designed Prosthesis
Accuracy will be assessed by superimposing AI-generated crown designs and human-designed crowns using 3D imaging software. The Intersection over Union (IOU) percentage will be calculated to evaluate morphological agreement and occlusal fit between the two design approaches.
Measured: Immediately after crown design generation (at time of digital analysis)
Secondary outcomes (1)
Margin Detection Performance of AI System
Margin detection accuracy will be evaluated using F1 score, precision, and recall metrics to assess the AI model's ability to accurately identify preparation margins compared to human-designed reference models.
Measured: Immediately after digital crown design generation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Feb 2026
- Study start15 Jun 2025
- Primary completion2 Apr 2026 (estimated)
- Study completion17 Jun 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Accuracy of Artificial Intelligence in Fixed Dental Prosthesis DesignStudies of the same condition, open and under way.
- 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
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- October University for Modern Sciences and Arts
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Tarek Adham Saad Ahmed El-Shammaa, October University for Modern Sciences and Arts
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07432165
- Sponsor's protocol ID
- REC-D 1216-5
- Status last verified
- Jun 2025
- First submitted
- 19 Feb 2026
- Last updated
- 25 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Wu Z, Zhang C, Ye X, Dai Y, Zhao J, Zhao W, Zheng Y. Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study. Int Dent J. 2025 Feb;75(1):127-134. doi: 10.1016/j.identj.2024.06.023. Epub 2024 Jul 28.
PubMed 39069456Ding H, Cui Z, Maghami E, Chen Y, Matinlinna JP, Pow EHN, Fok ASL, Burrow MF, Wang W, Tsoi JKH. Morphology and mechanical performance of dental crown designed by 3D-DCGAN. Dent Mater. 2023 Mar;39(3):320-332. doi: 10.1016/j.dental.2023.02.001. Epub 2023 Feb 21.
PubMed 36822895Chau RCW, Hsung RT, McGrath C, Pow EHN, Lam WYH. Accuracy of artificial intelligence-designed single-molar dental prostheses: A feasibility study. J Prosthet Dent. 2024 Jun;131(6):1111-1117. doi: 10.1016/j.prosdent.2022.12.004. Epub 2023 Jan 9.
PubMed 36631366
Study at a glance
From the registry record, last updated by the sponsor on 25 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Accuracy Assessment of Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis: (An Invitro Study)
- ClinicalTrials.gov ID
- NCT07432165
- Acronym / sponsor ID
- REC-D 1216-5
- Keywords
- Artificial Intelligence, CAD/CAM, Fixed Dental Prosthesis, Dental Crown Design, 3D Superimposition, Deep Learning, Generative Adversarial Network (GAN), Prosthodontics
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- October University for Modern Sciences and ArtsUniversity, hospital or other
- Study start
- 15 Jun 2025 (actual)
- Primary completion
- 2 Apr 2026 (estimated)
- Study completion
- 17 Jun 2026 (estimated)
- First posted
- 25 Feb 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 in vitro study aims to evaluate the accuracy of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) compared with conventional computer-aided design (CAD) software. Digital scans of teeth requiring fixed dental prosthesis will be collected and used to generate prosthetic designs using two approaches: human-designed CAD restorations and AI-generated restorations.
The primary outcome is design accuracy assessed using 3D superimposition and Intersection over Union (IOU) percentage. Secondary outcomes include margin detection performance measured using F1 score, precision, and recall. A total sample size of 438 scans will be analyzed.
The study will determine whether AI-generated prosthesis designs demonstrate comparable accuracy to conventional digital designs.
Detailed description
This study is designed as an in vitro comparative study to assess the accuracy and performance of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) in comparison with conventional computer-aided design (CAD) software.
Digital scans of patients requiring fixed dental prosthesis will be collected from the production laboratory of the Faculty of Dentistry. Eligible scans will include adults aged 18-65 years with damaged teeth requiring FDP and adequate occlusal anatomy for analysis.
The AI workflow consists of three sequential phases: training (60%), validation (10%), and testing (30%). The AI model will be trained using natural spatial tooth morphology and historical human-designed FDP datasets. The conventional group will consist of FDPs manually designed by experienced dental professionals using CAD software.
Primary Outcome:
The primary outcome is crown design accuracy measured using 3D superimposition analysis and quantified using Intersection over Union (IOU) percentage.
Secondary Outcome:
Margin detection accuracy will be assessed using F1 score, precision, and recall metrics.
Statistical analysis will be performed using MedCalc software (Version 22). Continuous variables will be presented as mean, root mean square, and standard deviation. Comparisons between groups will be conducted using paired t-test with a significance level set at P ≤ 0.05 (two-tailed).
The null hypothesis states that there will be no statistically significant difference between AI-designed and human-designed fixed dental prostheses.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Human-Designed Fixed Dental Prosthesis (Conventional CAD) | Other | Other: Conventional CAD-Based Fixed Dental Prosthesis DesignFixed dental prostheses will be designed manually using conventional CAD software by experienced dental professionals based on occlusal anatomy and patient-specific scan data. The designs will serve as the control comparator to evaluate accuracy against AI-generated designs using 3D superimposition analysis. |
| AI-Designed Fixed Dental Prosthesis | Other | Other: Artificial Intelligence-Based Fixed Dental Prosthesis DesignFixed dental prostheses will be automatically generated using an artificial intelligence-based design system. The AI model will be trained, validated, and tested using occlusal scan datasets and historical human-designed prostheses. The generated designs will be evaluated for accuracy using 3D superimposition and Intersection over Union (IoU) analysis. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Adults aged 18-65 years Patients with a damaged tooth requiring a fixed dental prosthesis Available digital intraoral scans Adequate occlusal anatomy for analysis of opposing teeth
Key exclusion criteria (1 listed)
- Incomplete or poor-quality digital scans Severe occlusal abnormalities affecting analysis Patients outside the specified age range
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 |
|---|---|---|
| Conventional CAD-Based Fixed Dental Prosthesis DesignAlso: Human Digital DesignFixed dental prostheses will be digitally designed using conventional computer-aided design (CAD) software by experienced dental professionals. Designs will be based on occlusal anatomy and patient-specific intraoral scan data. These manually generated digital designs will serve as the comparator for evaluating accuracy against AI-generated designs using 3D superimposition and quantitative accuracy analysis. | Other | Human-Designed Fixed Dental Prosthesis (Conventional CAD) |
| Artificial Intelligence-Based Fixed Dental Prosthesis DesignAlso: AI Crown Design ModelAn artificial intelligence-based automated design system will generate fixed dental prosthesis designs using deep learning algorithms. The AI model will be trained (60%), validated (10%), and tested (30%) on occlusal scan datasets and historical human-designed prostheses. Generated designs will be evaluated for accuracy and marginal precision using 3D superimposition and Intersection over Union (IoU) analysis. | Other | AI-Designed Fixed Dental Prosthesis |
Primary outcome
Accuracy of AI-Designed Fixed Dental Prosthesis Compared to Human-Designed Prosthesis
Time frame: Immediately after crown design generation (at time of digital analysis)
Accuracy will be assessed by superimposing AI-generated crown designs and human-designed crowns using 3D imaging software. The Intersection over Union (IOU) percentage will be calculated to evaluate morphological agreement and occlusal fit between the two design approaches.
1 secondary outcome
Margin Detection Performance of AI System
Time frame: Immediately after digital crown design generation
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 Feb 2026.
- Background: PubMed 39069456Wu Z, Zhang C, Ye X, Dai Y, Zhao J, Zhao W, Zheng Y. Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study. Int Dent J. 2025 Feb;75(1):127-134. doi: 10.1016/j.identj.2024.06.023. Epub 2024 Jul 28.
- Background: PubMed 36822895Ding H, Cui Z, Maghami E, Chen Y, Matinlinna JP, Pow EHN, Fok ASL, Burrow MF, Wang W, Tsoi JKH. Morphology and mechanical performance of dental crown designed by 3D-DCGAN. Dent Mater. 2023 Mar;39(3):320-332. doi: 10.1016/j.dental.2023.02.001. Epub 2023 Feb 21.
- Background: PubMed 36631366Chau RCW, Hsung RT, McGrath C, Pow EHN, Lam WYH. Accuracy of artificial intelligence-designed single-molar dental prostheses: A feasibility study. J Prosthet Dent. 2024 Jun;131(6):1111-1117. doi: 10.1016/j.prosdent.2022.12.004. Epub 2023 Jan 9.
- Individual participant dataSharing planned: No
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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Conventional CAD-Based Fixed Dental Prosthesis Design and Artificial Intelligence-Based Fixed Dental Prosthesis Design in people with Accuracy of Artificial Intelligence in Fixed Dental Prosthesis Design, run by October University for Modern Sciences and Arts 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 1 inclusion and 1 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: looking for participants now, as of the sponsor's last update on 25 Feb 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?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of AI-Designed Fixed Dental Prosthesis Compared to Human-Designed Prosthesis (time frame: Immediately after crown design generation (at time of digital analysis)). 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 NCT07432165, which also lists 3 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 Feb 2026.