Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-65
SponsorOctober University for Modern Sciences and Arts
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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
Disqualifiers
Incomplete or poor-quality digital scans Severe occlusal abnormalities affecting analysis Patients outside the specified age range
Trial design
Design model
Parallel
Treatments tested in this trial
Conventional CAD-Based Fixed Dental Prosthesis Design
Other interventionFixed 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 Design
Other interventionAn 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.
Treatment groups
1,000 Participants
are divided into 2 treatment groupsGroup A: Human-Designed Fixed Dental Prosthesis (Conventional CAD)Other 1 intervention
Group B: AI-Designed Fixed Dental ProsthesisOther 1 intervention
Trial outcomes
Primary outcomes
1
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.
Time frame
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.
Time frame
Immediately after digital crown design generationSponsors and contacts
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Source ClinicalTrials.gov