Use of Three-Dimensional Printed Anatomical Models to Enhance Veterinary Students' Interpretation of Computed Tomography Scans in Dogs With a Congenital Extrahepatic Portosystemic Shunt.

Abstract

The study aimed to evaluate the effectiveness of three-dimensional (3D)-printed canine anatomical models as tools to support veterinary students in interpreting computed tomography (CT) scans of dogs with congenital extrahepatic portosystemic shunts (CEPSs). Two canine anatomical models were produced: one representing normal anatomy and another depicting a splenocaval CEPS. These models were generated using CT scans from clinical cases. A total of 114 third-year veterinary students participated and were randomly assigned to either a control group (CG; n = 60) or a 3D model group (3DG; n = 54). All students underwent theoretical and practical training sessions related to CT imaging and CEPSs anatomy. Instruction was delivered through oral presentations supported by slides and illustrative images. The training included handling CT scans without CEPSs and anatomical dissection of abdominal cavities in canine or feline cadavers. Only the 3DG students used the 3D-printed models throughout all phases, including during questionnaire completion. Students' performance was assessed via a questionnaire that was administered at the end of the training sessions and accessed via a quick-response (QR) code. The questionnaire required students to identify and classify the CEPS, record their perceived difficulty, and indicate the primary imaging modality used to complete the task (multiplanar reconstruction, volume rendering, or 3D-printed anatomical models). Statistical analyses were performed using Fisher's exact test and the Mann-Whitney U test, with significance set at p < 0.05. Results showed significantly higher diagnostic accuracy in the 3DG (94.4%) compared to the CG (31.7%). The 3DG reported a moderate level of difficulty, whereas the CG perceived the task as difficult. Most students in the 3DG used the 3D-printed anatomical models (75.93%), whereas the majority in the CG relied on volume rendering (95.00%). These findings suggest that 3D-printed anatomical models can enhance students' diagnostic accuracy and reduce the perceived difficulty of interpreting complex CT images.