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NCT07295964
Accuracy of Intraoral Scan Post-processing Methods: A Clinical Trial
NA trial testing Artificial intelligence driven registration in Restoration Design in 30 participants. Not yet recruiting.
25 December 2026
Quick facts
| Lead sponsor | National and Kapodistrian University of Athens |
|---|---|
| Phase | NA |
| Status | Not yet recruiting |
| Study type | INTERVENTIONAL |
| Allocation | randomized |
| Design | single group |
| Masking | quadruple |
| Primary purpose | treatment |
| Enrollment | 30 |
| Start date | 25 January 2026 |
| Primary completion | 25 December 2026 |
| Estimated completion | 25 June 2027 |
| Sites | 1 location across Greece |
Drugs / interventions tested
- Artificial intelligence driven registration
- Software based registration
Conditions studied
- Restoration Design — all drugs for Restoration Design →
- Digital Occlusal Collision — all drugs for Digital Occlusal Collision →
Sponsor
National and Kapodistrian University of Athens
Who can join
18 and older, any sex, with Restoration Design or Digital Occlusal Collision. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
In the last decade, progressive developments in computer hardware, software, manufacturing technologies, and dental materials consistently enhanced the use of digital technologies in dentistry. Traditional prosthodontic techniques have relied on manual fabrication processes, which often resulted in challenges such as suboptimal prosthesis fit, compromised occlusal stability, and limited customization options. However, the advent of 3D printing technology has revolutionized the field, offering new possibilities for patient-specific prosthodontic rehabilitation. An accurate maxillomandibular relationship between the maxillary and mandibular casts is fundamental to prosthodontic practice. In the integration of intraoral scanners (IOSs) for different dental interventions, the accuracy of the digitizing methods recording the maxillomandibular relationship is similarly essential. The maxillomandibular relationship accuracy recorded by using IOSs has been analyzed in various in vitro and clinical studies. Intraoral digital scans are recorded in an unload condition, with the mouth open, while acquiring the maxillary and the mandibular intraoral scans. This condition changes when capturing the virtual occlusal records at maximum intercuspation position (MIP). Occlusal collisions are caused by the tooth location discrepancy resulting from the periodontal ligament plasticity between the recording of the intraoral digital scans and the virtual occlusal records, as well as from the intraoral scanning distortion and alignment procedures. Artificial intelligence driven program software and occlusal collisions or mesh interpenetrations tools have been proposed to improve the maxillomandibular relationship of the scanned models. The software programs of the IOSs can automatically eliminate the occlusal collisions present in virtual articulated casts. Similarly, dental computer-aided design (CAD) programs can automatically detect and eliminate occlusal collisions among the articulated intraoral digital scans imported. However, the effect of the occlusal collision corrections performed by using IOSs or CAD programs on the occlusal adjustment of the restorations is unknown.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT07295964 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by National and Kapodistrian University of Athens
- Last refreshed: 22 December 2025
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07295964.
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