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Background <p>Treatment of deep caries has always been a tricky part in pre-clinical dental education. Traditional standard resin teeth and several refined models failed to simulate the clinical teeth with deep caries in morphology or texture, resulting in students’ poor mastery of practical skills and an increased risk of pulp exposure in real cases. To bridge this gap, this study produced a novel 3D-printed model tooth and evaluated its feasibility in education of deep caries treatment.</p> Methods <p>Based on micro-CT and 3D scanning images, a multilayered and hardness-stratified tooth with deep caries was devised and 3D-printed. 66 teeth were evaluated after hands-on operations by 33 clinicians who were proficient in deep caries treatment and familiar with the tactile sense of traditional resin teeth and extracted natural teeth. They assessed the model tooth by rating in a questionnaire.</p> Results <p>The 3D-printed model tooth exhibited high realism in both morphology (Ø 4.58 ± 0.56) and tactile sense (Ø 4.36 ± 0.55). Compared with the standard resin tooth, the 3D-printed tooth was generally graded positively and significantly higher in all aspects (<i>p</i> &lt; 0.05), including tactile feeling (Ø 4.36 ± 0.55), structural realism (Ø 4.55 ± 0.56) and operating feasibility (Ø 4.64 ± 0.49). The model was also rated helpful for pre-clinical students to master procedures and principles in deep caries excavation (Ø 4.79 ± 0.42) and cavity preparation (Ø 4.52 ± 0.71), and was regarded suitable for practical training of deep caries treatment (Ø 4.76 ± 0.44).</p> Conclusions <p>We developed a novel multilayered and hardness-stratified 3D-printed tooth for deep caries treatment. This model achieved high realism (mean Likert 3.73–4.79 across domains; Cronbach’s alpha = 0.87) and was considered promising for pre-clinical cariology training. Future trials will evaluate its impact on student learning outcomes.</p>

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A highly realistic 3D-printed deep caries model tooth with hardness-stratified layers for pre-clinical training in deep caries management

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月25日

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  • Xinze Wu,
  • Yingying Zhang,
  • Bo Dong,
  • Jiyao Li,
  • Qinghua Zheng,
  • Min Zhang

摘要

Background

Treatment of deep caries has always been a tricky part in pre-clinical dental education. Traditional standard resin teeth and several refined models failed to simulate the clinical teeth with deep caries in morphology or texture, resulting in students’ poor mastery of practical skills and an increased risk of pulp exposure in real cases. To bridge this gap, this study produced a novel 3D-printed model tooth and evaluated its feasibility in education of deep caries treatment.

Methods

Based on micro-CT and 3D scanning images, a multilayered and hardness-stratified tooth with deep caries was devised and 3D-printed. 66 teeth were evaluated after hands-on operations by 33 clinicians who were proficient in deep caries treatment and familiar with the tactile sense of traditional resin teeth and extracted natural teeth. They assessed the model tooth by rating in a questionnaire.

Results

The 3D-printed model tooth exhibited high realism in both morphology (Ø 4.58 ± 0.56) and tactile sense (Ø 4.36 ± 0.55). Compared with the standard resin tooth, the 3D-printed tooth was generally graded positively and significantly higher in all aspects (p < 0.05), including tactile feeling (Ø 4.36 ± 0.55), structural realism (Ø 4.55 ± 0.56) and operating feasibility (Ø 4.64 ± 0.49). The model was also rated helpful for pre-clinical students to master procedures and principles in deep caries excavation (Ø 4.79 ± 0.42) and cavity preparation (Ø 4.52 ± 0.71), and was regarded suitable for practical training of deep caries treatment (Ø 4.76 ± 0.44).

Conclusions

We developed a novel multilayered and hardness-stratified 3D-printed tooth for deep caries treatment. This model achieved high realism (mean Likert 3.73–4.79 across domains; Cronbach’s alpha = 0.87) and was considered promising for pre-clinical cariology training. Future trials will evaluate its impact on student learning outcomes.