Conventional vs. digital wax-up: A crossover study on accuracy and undergraduate student satisfaction
The aim of this study was to compare the accuracy and user experience of diagnostic wax-ups performed by dental students using conventional and digital Computer-Aided Design (CAD) methods. A crossover design was implemented with 105 fourth-year dental students. Each participant completed diagnostic wax-ups using both methods on standardized 3D-printed models, with a one-week washout period. Spatial visualization skills were assessed via the Mental Rotation Test (MRT) prior to the wax-up tasks. The conventional method involved manual wax sculpting, while the digital method utilized Meshmixer 3.5 software for teeth adaptation. Accuracy was evaluated using Iterative Closest Point (ICP) algorithms and metrics such as mean squared distance, Chamfer distance, and Hausdorff distance. After each session, a user experience questionnaire was administered. The conventional method yielded significantly higher accuracy ( p < 0.001) compared to the digital method. Nevertheless, students strongly preferred the digital approach for its ease of use ( p < 0.001). MRT results showed no significant correlation between the 3D spatial skills and wax-up accuracy for both methods. Conventional wax-ups demonstrated higher accuracy, while the digital method was favored for its user-friendliness. The absence of a correlation between spatial skills and performance suggests that other factors may influence outcomes. Digital solutions such as Meshmixer provide a cost-effective CAD alternative in resource-limited educational settings. Using easily implementable CAD software in dental schools could allow more CAD training within the curriculum, helping bridge the gap between undergraduate training and postgraduate practice, where CAD is extensively used. • Conventional wax-ups were more precise, highlighting their higher accuracy. • Students prefer digital wax-ups despite lower accuracy, due to their ease of use. • No significant correlation between 3D visualization skills and wax-up accuracy. • Meshmixer offers a CAD alternative for resource-limited dental education.
Authors
- Abhishek Kumar (ORCID: https://orcid.org/0000-0003-3729-3524)
- Antoine Galibourg (ORCID: https://orcid.org/0000-0003-0643-4646)
- Anastasios Grigoriadis (ORCID: https://orcid.org/0000-0002-3323-8299)
- Cathy Nabet (ORCID: https://orcid.org/0000-0003-1384-2154)
- Florent Destruhaut (ORCID: https://orcid.org/0000-0002-1011-2212)
- E. A. Masson
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Toulouse III - Paul Sabatier (FR)
- Inserm (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- Karolinska Institutet (SE)
- Centre de recherche en Epidémiologie et Santé des Populations (FR)
- Laboratoire d'Anthropologie Sociale (FR)
- Centre for Health Equity Studies (SE)
Publication Details
- Journal
- Digital Dentistry Journal
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1016/j.ddj.2025.100003
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00