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3D-Printed Sinus Lift Training Models as an Educational Tool for Dental Students
Linda Daume1, Lauren Bohner1, Marcel Hanisch1
1Department of Oral and Maxillofacial Surgery, University Hospital Münster, Münster, Germany.
Journal of Dental Education
|June 24, 2026
Summary
3D-printed dental models offer a cost-effective method for training students in sinus lift procedures. These models provide good structural realism and educational value, though soft tissue simulation needs improvement.
Area of Science:
- Dental Education
- Biomedical Engineering
- Surgical Simulation
Background:
- Traditional dental training models (typodonts) have limitations in simulating complex procedures.
- Sinus lift procedures require specialized training for dental students.
- Advancements in 3D printing offer potential for creating realistic and reproducible anatomical models.
Purpose of the Study:
- To assess the efficacy of 3D-printed maxillary models for training dental students in sinus lift techniques.
- To evaluate the cost-effectiveness and suitability of 3D-printed models compared to conventional training methods.
Main Methods:
- A 3D-printed maxillary sinus lift model was developed using CAD/CAM technology.
- Thirty-one dental students evaluated the model and two sinus lift techniques (rotary instruments vs. piezosurgery).
- Student experiences were assessed via questionnaire, with statistical analysis using Wilcoxon rank sum tests.
Main Results:
- The 3D-printed model facilitated an easy-to-understand and perform sinus lift procedure.
- Students rated the two tested sinus lift techniques (rotary instruments and piezosurgery) equally.
- The gingiva mask component of the 3D-printed model received criticism.
Conclusions:
- 3D-printed maxillary models serve as a reproducible and valuable alternative to traditional typodonts for sinus lift training.
- The models demonstrate positive structural realism and educational utility for curriculum-based sinus lift procedures.
- Further refinement of soft tissue simulation is recommended to improve the fidelity of 3D-printed models.

