Accuracy of Intraoral Scan Post-processing Methods: A Clinical Trial

Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorNational and Kapodistrian University of Athens

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

None

Disqualifiers

None

Trial design

Design model

Single group

Treatments tested in this trial

  • Artificial intelligence driven registration

    Other intervention

    Maxillomandibular relationship is refined using AI driven tools

  • Software based registration

    Other intervention

    Maxillomandibular relationship is refined using software based algorithms

Treatment groups

30 Participants
are divided into 4 treatment groups
Group A: AI driven designExperimental treatment 1 intervention
Group B: AI driven refinement of maxillomandibular relatioshipExperimental treatment 1 intervention
Group C: Design of a restoration after automated collision correctionExperimental treatment 1 intervention
Group D: Design of a restoration using the registration without any further refinementActive comparator 1 intervention

Trial outcomes

Primary outcomes

1

Level of adjustment

The investigators will rate the adjustment amount 0-4 scores based on the adjustment surface, and the geometrical characteristics of the adjustment. Grade 4 adjustments will be considered to require renewal of the restoration due to a change in the anatomical contour of the reconstructions, whereas Grade 0 will be considered as perfect.

Time frame
Baseline, after the adjustment of the try-in restorations

Secondary outcomes

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

This trial is not recruiting at the moment. You can still explore other options: