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

NCT07295964 | Not Yet Recruiting

• 1 other identifier: STUDY3534
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Digital Occlusal Collision; Restoration Design

Keywords

Artificial intelligence; Prosthodontics; Automated Design; Occlusion Collusion

Outcome Measures

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.

  Baseline, after the adjustment of the try-in restorations

Study Arms (4)

AI driven design

EXPERIMENTAL

The restoration is designed using an AI driven software

Other: Artificial intelligence driven registration

AI driven refinement of maxillomandibular relatioship

EXPERIMENTAL

The restoration is design using a maxillomandibular relationship refined by an AI tool

Other: Artificial intelligence driven registration

Design of a restoration after automated collision correction

EXPERIMENTAL

The restoration is designed using the maxillomandibular relationship obtained after the use of a software for automated collision correction

Other: Software based registration

Design of a restoration using the registration without any further refinement

ACTIVE COMPARATOR

The restoration is designed using the conventional maxillomandibular relationship as it i obtained by the intraoral scanning without further refinement

Other: Software based registration

Interventions

Artificial intelligence driven registration OTHER

Maxillomandibular relationship is refined using AI driven tools

AI driven design; AI driven refinement of maxillomandibular relatioship

Software based registration OTHER

Maxillomandibular relationship is refined using software based algorithms

Design of a restoration after automated collision correction; Design of a restoration using the registration without any further refinement

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age \> 18 years old Absence of painful temporomandibular disorder Presence of opposing teeth Presence of a stable maximum intercuspation relationship

You may not qualify if:

• \- Pain in orofacial region Visible periapical lesion \< Class II mobility

Sponsors & Collaborators

• National and Kapodistrian University of Athens: lead

Study Sites (1)

Clinic

Athens, Attica, 11527, Greece

Location

Related Publications (16)

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Central Study Contacts

Panagiotis Ntovas, DDS, MSc

CONTACT

6985122220; pan.ntovas@gmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: QUADRUPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD Canditate, Department of Operative Dentistry, School of Dentistry, Greece

Study Record Dates

• First Submitted: January 9, 2025
• First Posted: December 22, 2025
• Study Start: January 25, 2026
• Primary Completion (Estimated): December 25, 2026
• Study Completion (Estimated): June 25, 2027
• Last Updated: December 22, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, CSR

Locations

GR (1)