Use of tracheobronchial tree 3-dimensional printed model: does it improve trainees’ understanding of segmentation anatomy? A prospective study

Abstract

Abstract Background This prospective study investigated whether the use of 3D-printed model facilitates novice learning of radiology anatomy on multiplanar computed tomography (CT) when compared to traditional 2D-based learning tools. Specifically, whether the use of a 3D printed model improved interpretation of multiplanar CT tracheobronchial anatomy. Methods Thirty-one medical students (10F, 21 M) from years one to three were recruited, matched for gender and level of training and randomized to 2D or 3D group. Students underwent 20-min self-study session using 2D-printed image or 3D-printed model of the tracheobronchial tree. Immediately after, students answered 10 multiple-choice questions (Test 1) to identify tracheobronchial tree branches on multiplanar CT images. Two weeks later, identical test (Test 2) was used to assess retention of information. Mean scores of 2D and 3D groups were calculated. Student’s t test was used to compare mean differences in tests scores and analysis of variance (ANOVA) was used to assess the interaction of gender, CT imaging plane and time on test scores between the two groups. Results For test 1, 2D group had higher mean score than 3D group although not statistically significant (7.69 and 7.43, p = 0.39). Mean scores for Test 2 were significantly lower than for Test 1 (7 and 7.57, p = 0.03) with mean score decline for 2D group (Test 1 = 7.69, Test 2 = 6.63, p = 0.03), and similar score for 3D group (Test 1 and 2 = 7.43). There was no statistically significant interaction of gender and test score over time. Significant interaction between group and time of test was found for axial CT images but not for coronal images. Conclusions Use of a 3D-printed model of the tracheobronchial anatomy had no immediate advantage over traditional 2D-printed images for learning CT anatomy. However, use of a 3D model improved students’ ability to retain learned information, irrespective of gender.

Keywords

• 3D printing
• 3D-printed models
• Computed tomography
• Medical education