Enhancing medical imaging teaching on scoliosis: Efficacy of learning method integrating 3D printing and artificial intelligence technologies.
J Med Imaging Radiat SciJul 17, 2026 (epub)
Clinical ResearchRadiology (Diagnostic)
Mengna Tang, Yaojun Jiang, Jishuai Hu et al.
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In 30 seconds
This randomized controlled trial evaluated the effectiveness of integrating 3D printing and artificial intelligence in scoliosis education among 36 undergraduate medical imaging students. The experimental group outperformed the control group in theoretical knowledge (91.01 ± 4.48 vs. 82.49 ± 4.08) and imaging case analysis (90.24 ± 4.77 vs. 80.61 ± 6.33), with significant differences (p < 0.001).
Key findings
- Experimental group scored 91.01 ± 4.48 in theoretical knowledge vs. 82.49 ± 4.08 in control group.
- Imaging case analysis scores were 90.24 ± 4.77 for experimental vs. 80.61 ± 6.33 for control.
- Experimental group reported higher scores in spatial imagination and overall comprehensive ability, p < 0.001.
- Teaching satisfaction was higher in the experimental group, though not statistically significant (p = 0.60).
Why it matters
Enhanced teaching methods that incorporate technology can significantly improve students' understanding and skills in medical imaging, which is crucial for effective patient care and clinical decision-making.