Work

The Use of 3D ‐Printed Teeth Models for Crown Preparation Training: Perceptions of Postgraduate Dental Trainees

Year: 2026

Type: article

Abstract: BACKGROUND: Typodont teeth used in preclinical dental training often lack the anatomical fidelity and tactile realism of natural dentition. With advancements in 3D printing, it is now feasible to design and fabricate highly realistic, patient-specific tooth models for educational use. METHODS: A mixed-methods study was conducted with 64 postgraduate dental trainees. Custom 3D-printed tooth models were created using intraoral scans and printed with two material types: Crowntec (CT) and Model 2.0 (M2.0). Participants completed standardised crown preparations and then responded to a validated questionnaire assessing model realism, training effectiveness and user preference. Quantitative responses were analysed using descriptive statistics and open-ended responses were thematically analysed. RESULTS: CT models were significantly rated higher than M2.0 and standard typodont teeth (STT) in terms of hardness (Ø 4.58 ± 0.75), haptic feedback (Ø 4.48 ± 0.67) and training suitability (Ø 4.56 ± 0.69). Compared to natural teeth, CT models were perceived as realistic in hardness (Ø 3.33 ± 1.07) and tactile feedback (Ø 3.97 ± 0.94). The artificial gingiva mask received moderate ratings in texture (Ø 3.33 ± 0.99) and consistency (Ø 3.5 ± 0.98). Qualitative themes included model design improvements, perceived educational value and cost-effectiveness. Despite a high initial setup cost, CT models were deemed educationally superior. CONCLUSION: 3D-printed dental models, particularly those using Crowntec resin, offer a realistic, reproducible and effective alternative to traditional models for teaching crown preparation. These models have the potential to improve training outcomes and merit integration into dental curricula.

Source: European Journal Of Dental Education

DOI: 10.1111/eje.70189

Authors: Ahmed Hatem, Ahmed Ghoneima, Haitham Elbishari, Amar Hassan Khamis, Fatemeh Amir‐Rad

Institutions: Mohammed Bin Rashid University of Medicine and Health Sciences, University of California, Los Angeles, Queen's University Belfast, University of Manchester

Language: English

Topic: Anatomy and Medical Technology

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $4,330