Comparing digital methods to improve fit of full-arch implant-supported prostheses
Evaluation of Passive Fit in Implant-Supported Complete-Arch Prostheses Using Three Digital Workflows, Including an Automated AI-Assisted Protocol: A Randomized Clinical Trial
This will test three digital workflows to see which gives the best passive fit for adults receiving fixed full-arch implant-supported prostheses.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 30 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Universidad Complutense de Madrid Academic / other |
| Locations | 1 site (Madrid, Madrid) |
| Trial ID | NCT07315620 on ClinicalTrials.gov |
What this trial studies
This randomized controlled trial enrolls adults needing fixed full-arch implant-supported rehabilitation and randomly assigns them 1:1:1 to one of three digital workflows for prosthesis fabrication: manual CBCT-STL alignment, splint-guided alignment, or an automated AI-assisted CBCT-STL alignment. Investigators will combine intraoral scans and CBCT data and compare the resulting definitive screw-retained frameworks for measures of passive fit using marginal, geometric, mechanical, and radiographic evaluations. The trial focuses on prostheses delivered to clinically stable, osseointegrated titanium implants and includes standardized clinical visits and imaging at a university clinic in Madrid. Results will show whether increased automation in dataset alignment improves the passive fit of full-arch frameworks.
Who should consider this trial
Good fit: Adults (18+) indicated for fixed implant-supported full-arch rehabilitation with clinically stable, osseointegrated titanium implants, no peri-implant disease, and ability to consent and attend study visits are ideal candidates.
Not a fit: Patients with active peri-implant mucositis or peri-implantitis, mobile or poorly positioned implants, uncontrolled systemic conditions, or those unable to complete follow-up are unlikely to benefit from this protocol.
Why it matters
Potential benefit: If successful, the approach could reduce mechanical complications and improve long-term prosthetic success by producing more accurate, passively fitting full-arch implant frameworks.
How similar studies have performed: Prior studies show intraoral scanning and CBCT-based digital workflows can improve prosthetic accuracy, but fully automated AI-assisted CBCT-STL alignment for full-arch passive fit is relatively novel and not yet widely validated.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Adults aged 18 years or older. 2. Patients indicated for fixed implant-supported full-arch rehabilitation in the maxilla or mandible. 3. Presence of clinically stable, osteointegrated titanium implants suitable for prosthetic rehabilitation. 4. Absence of clinical or radiographic signs of peri-implant disease. 5. Ability to understand the study procedures and provide written informed consent. 6. Willingness and ability to attend all required clinical visits and evaluations. Exclusion Criteria: 1. Presence of peri-implant mucositis or peri-implantitis at the time of evaluation. 2. Implant mobility or implant positioning that prevents proper prosthetic rehabilitation. 3. Uncontrolled systemic medical conditions that could interfere with study participation or prosthetic treatment. 4. Cognitive, psychological, or medical conditions that limit the ability to comply with study procedures. 5. Inability to complete the required clinical evaluations or follow the study protocol, as judged by the investigator.
Where this trial is running
Madrid, Madrid
- University Complutense of Madrid — Madrid, Madrid, Spain (Recruiting)
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.