Interobserver and intraobserver agreement of three-dimensionally printed models for the classification of proximal humeral fractures
Journal Publication ResearchOnline@JCUAbstract
Hypothesis This study aimed to examine whether three-dimensionally printed models (3D models) could improve interobserver and intraobserver agreement when classifying proximal humeral fractures (PHFs) using the Neer system. We hypothesized that 3D models would improve interobserver and intraobserver agreement compared with x-ray, two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) and that agreement using 3D models would be higher for registrars than for consultants. Methods Thirty consecutive PHF images were selected from a state-wide database and classified by fourteen observers. Each imaging modality (x-ray, 2D CT, 3D CT, 3D models) was grouped and presented in a randomly allocated sequence on two separate occasions. Interobserver and intraobserver agreements were quantified with kappa values (k), percentage agreement, and 95% confidence intervals (CIs). Results Seven orthopedic registrars and seven orthopedic consultants classified 30 fractures on one occasion (interobserver). Four registrars and three consultants additionally completed classification on a second occasion (intraobserver). Interobserver agreement was greater with 3D models than with x-ray (k ¼ 0.47, CI: 0.44-0.50, 66.5%, CI: 64.6-68.4% and k ¼ 0.29, CI: 0.26-0.31, 57.2%, CI: 55.1-59.3%, respectively), 2D CT (k ¼ 0.30, CI: 0.27-0.33, 57.8%, CI: 55.5-60.2%), and 3D CT (k ¼ 0.35, CI: 0.33-0.38, 58.8%, CI: 56.7-60.9%). Intraobserver agreement appeared higher for 3D models than for other modalities; however, results were not significant. There were no differences in interobserver or intraobserver agreement between registrars and consultants. Conclusion Three-dimensionally printed models improved interobserver agreement in the classification of PHFs using the Neer system. This has potential implications for using 3D models for surgical planning and teaching
Journal
JSES International
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Volume
5
ISBN/ISSN
2666-6383
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Issue
2
Pages Count
7
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Publisher
Elsevier
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N/A
DOI
10.1016/j.jseint.2020.10.019