Teaching Anatomy with Three-dimensional Slicer: A Pre-poststudy on Spatial Understanding and Imaging Literacy in Medical Students
Roselin Peter, Annamalai Vairavan, Swarnalakshmi Sampath, Akshaya SaravananAbstract
Background:
Three-dimensional (3D) visualization tools such as 3D Slicer are revolutionizing the field of anatomical education in medicine. Conventional teaching of anatomy includes cadaveric dissection and two-dimensional imaging. Often, these methods are incapable of depicting anatomical complexity in space. Using computed tomography or magnetic resonance imaging, 3D Slicer has reconstruction capabilities that allow anatomical reconstruction in a learning setting. Implementation of this new modality in anatomical learning has immense benefits. The aim of this research is to ascertain the efficiency of 3D Slicer as a tutoring aid for students and to analyze its use for increasing conceptual knowledge of anatomy as well as an understanding of applied aspects of radiology.
Methodology:
A cohort of undergraduate students will be provided with 3D Slicer training in a structured workshop setting conducted by faculty members in the radiology department. Student learning outcomes will be assessed through pre- and postintervention questionnaires, objective structured practical examinations, and Likert scale feedback on usability and satisfaction. Qualitative analysis of student reflections will complement quantitative assessment. Statistical tests will evaluate the differences in performance before and after the intervention.
Results:
The findings indicate a significant improvement in the understanding of spatial concepts, knowledge of anatomy and its localization, and the ability to correlate imaging with gross anatomy concepts by the learners. The learners have a high level of engagement and enjoy positive responses indicating the benefits of the approach in terms of interaction and visualizing concepts compared to textbooks.
Conclusion:
3D Slicer is an important supplement to anatomy education by filling the gap between conventional and advanced learning methods. Integrating such open-source software into a learning program achieves greater insight into anatomy and improves the skill of clinical correlation with advanced training for the future of image-assisted diagnostic and therapeutic work.