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 midsession 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.