Handheld Three-dimensional Scanning in Medical Education: Feasibility of Student-generated Donor-based Digital 3D Models

Document Type

Article

Publication Title

Anatomical Sciences Education

Abstract

This descriptive feasibility study examined whether medical students could generate anatomically coherent digital three-dimensional (3D) models from donor dissections using a handheld surface scanner. Two second-year medical students used an Artec Space Spider scanner to generate digital 3D models of four anatomical structure groups: heart, brachial plexus, spinal cord, and celiac trunk. Anatomical accuracy was defined as the presence of expected curricular structures and quantified using structure-presence scores (proportion of expected curricular structures identifiable in each model). Reliability was evaluated by repeated scanning of the celiac trunk, and image quality was assessed by comparing grayscale histogram distributions between a digital model and its corresponding photograph. Across all anatomical structure groups, the mean structure-presence score was 0.892, indicating that most expected structures were identifiable in the student-generated models. Structure-presence scores varied by anatomical structure group, with lower scores for the brachial plexus (mean = 0.773, p = 0.021) than for the heart (p = 0.073) and spinal cord (p = 0.321). Repeat scanning of the celiac trunk reproduced all expected structures, demonstrating consistent structural capture. Grayscale histogram analysis showed reduced intensity variation in the digital 3D model relative to photography, while preserving discernible anatomical boundaries sufficient for identification. These findings suggest that medical students can generate anatomically coherent, reusable digital 3D models from donor dissections using handheld surface-scanning technology. Although surface scanning may be less effective for small or deeply situated neurovascular structures, these models may serve as manipulable resources extending access to donor anatomy beyond the laboratory.

DOI

10.1002/ase.70296

Publication Date

7-6-2026

Keywords

3D surface scanning, anatomical modeling, digital anatomy, digital reconstruction; experiential learning, gross anatomy education, student‐generated learning

ISSN

1935-9780

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