Virtual Human Dissector as a learning tool for studying cross-sectional anatomy.

Abstract

Background: Within diagnostic medicine there is a continuing and marked increase in the use of two-dimensional (2D) images of cross-sectional anatomy. Medical undergraduates should therefore develop skills to interpret such images early in their education. The Virtual Human Dissector© (VHD) software facilitates such learning, permitting users to study actual images of 2D anatomical cross-sections and reconstructed three-dimensional (3D) views simultaneously. This study investigates the use of VHD in facilitating students’ ability to interpret cross-sectional images and understand the relationships between anatomical structures. Methods: First year medical students (n = 89) were randomly divided into two groups. Using a crossover design, the investigation was undertaken as two 20 minute self-directed learning (SDL) activities using VHD in a computer suite and prosections and models in the dissecting room (DR), interspersed between 3 tests identifying anatomical structures in cross-sectional images (pre-, mid- and post-session). Results: Statistical analysis of test performance revealed significant improvements in each group between the pre- and mid-session tests, and again between mid- and post-session tests. There was no significant difference between the two groups at any stage. SDL using the VHD was as effective as SDL using prosections.