R Geske, Jennifer
Mayo Clinic
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
Citations 1
Three-Dimensional-Printed Liver Model Helps Learners Identify Hepatic Subsegments: A Randomized-Controlled Cross-Over Trial
Chedid, Victor , Kamath, A. , Knudsen, John M. , Frimannsdottir, Katrin R., Yost, Kathleen J. , Geske, Jennifer R. , Taner, Timuçin , Matsumoto, Jane M., Kamath, Patrick S. , Chedid, Victor G , Kamath, Amika A, M Knudsen, John, Frimannsdottir, Katrin, R Geske, Jennifer, Geske, Jennifer , Morris, Jonathan M.
American Journal of Gastroenterology | September 25, 2020 | Volume: 115 | Issue: 11 | Pages: 1906-1910
INTRODUCTION: The purpose of this study was to find out whether 3-dimensional (3D)–printed models improved the learners' ability to identify liver segments. METHODS: A total of 116 physicians from 3 disciplines were tested in a cross-over trial at baseline and after teaching with 3D models and 2-dimensional (2D) images. Adjusted multilevel-mixed models were used to compare scores at baseline and after 3D and 2D. RESULTS: Accuracy in identifying hepatic segments was higher with 3D first than 2D (77% vs 69%; P = 0.05) and not significantly improved by a combination of 3D and 2D. Increased confidence in segment identification was highest in trainees after 3D ( P = 0.04). DISCUSSION: 3D-printed models facilitate learning hepatic segmental anatomy.