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3D models improve understanding of congenital heart disease

INTRODUCTION: Understanding congenital heart disease (CHD) is vital for medical personnel and parents of affected children. While traditional 2D schematics serve as the typical approach used, several studies have shown these models to be limiting in understanding complex structures. Recent world-emp...

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Autores principales: Awori, Jonathan, Friedman, Seth D., Chan, Titus, Howard, Christopher, Seslar, Steve, Soriano, Brian D, Buddhe, Sujatha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8411549/
https://www.ncbi.nlm.nih.gov/pubmed/34471999
http://dx.doi.org/10.1186/s41205-021-00115-7
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author Awori, Jonathan
Friedman, Seth D.
Chan, Titus
Howard, Christopher
Seslar, Steve
Soriano, Brian D
Buddhe, Sujatha
author_facet Awori, Jonathan
Friedman, Seth D.
Chan, Titus
Howard, Christopher
Seslar, Steve
Soriano, Brian D
Buddhe, Sujatha
author_sort Awori, Jonathan
collection PubMed
description INTRODUCTION: Understanding congenital heart disease (CHD) is vital for medical personnel and parents of affected children. While traditional 2D schematics serve as the typical approach used, several studies have shown these models to be limiting in understanding complex structures. Recent world-emphasis has shifted to 3D printed models as a complement to 2D imaging to bridge knowledge and create new opportunities for experiential learning. We sought to systematically compare 3D digital and physical models for medical personnel and parent education compared to traditional methods. METHODS: 3D printed and digital models were made out of MRI and CT data for 20 common CHD. Fellows and nurse practitioners used these models to explore intra-cardiac pathologies following traditional teaching. The models were also used for parent education in outpatient settings after traditional education. The participants were then asked to fill out a Likert scale questionnaire to assess their understanding and satisfaction with different teaching techniques. These ratings were compared using paired t-tests and Pearson’s correlation. RESULTS: Twenty-five medical personnel (18 fellows; 2 nurses; 4 nurse practitioners and one attending) and twenty parents participated in the study. The diagnosis varied from simple mitral valve pathology to complex single ventricle palliation. Parent and medical personnel perceived understanding with digital models was significantly higher than traditional (p = 0.01). Subjects also felt that physical models were overall more useful than digital ones (p = 0.001). Physicians using models for parent education also perceived the models to be useful, not significantly impacting their clinical workflow. CONCLUSIONS: 3D models, both digital and printed, enhance medical personnel and parental perceived understanding of CHD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41205-021-00115-7.
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spelling pubmed-84115492021-09-09 3D models improve understanding of congenital heart disease Awori, Jonathan Friedman, Seth D. Chan, Titus Howard, Christopher Seslar, Steve Soriano, Brian D Buddhe, Sujatha 3D Print Med Research INTRODUCTION: Understanding congenital heart disease (CHD) is vital for medical personnel and parents of affected children. While traditional 2D schematics serve as the typical approach used, several studies have shown these models to be limiting in understanding complex structures. Recent world-emphasis has shifted to 3D printed models as a complement to 2D imaging to bridge knowledge and create new opportunities for experiential learning. We sought to systematically compare 3D digital and physical models for medical personnel and parent education compared to traditional methods. METHODS: 3D printed and digital models were made out of MRI and CT data for 20 common CHD. Fellows and nurse practitioners used these models to explore intra-cardiac pathologies following traditional teaching. The models were also used for parent education in outpatient settings after traditional education. The participants were then asked to fill out a Likert scale questionnaire to assess their understanding and satisfaction with different teaching techniques. These ratings were compared using paired t-tests and Pearson’s correlation. RESULTS: Twenty-five medical personnel (18 fellows; 2 nurses; 4 nurse practitioners and one attending) and twenty parents participated in the study. The diagnosis varied from simple mitral valve pathology to complex single ventricle palliation. Parent and medical personnel perceived understanding with digital models was significantly higher than traditional (p = 0.01). Subjects also felt that physical models were overall more useful than digital ones (p = 0.001). Physicians using models for parent education also perceived the models to be useful, not significantly impacting their clinical workflow. CONCLUSIONS: 3D models, both digital and printed, enhance medical personnel and parental perceived understanding of CHD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41205-021-00115-7. Springer International Publishing 2021-09-02 /pmc/articles/PMC8411549/ /pubmed/34471999 http://dx.doi.org/10.1186/s41205-021-00115-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Awori, Jonathan
Friedman, Seth D.
Chan, Titus
Howard, Christopher
Seslar, Steve
Soriano, Brian D
Buddhe, Sujatha
3D models improve understanding of congenital heart disease
title 3D models improve understanding of congenital heart disease
title_full 3D models improve understanding of congenital heart disease
title_fullStr 3D models improve understanding of congenital heart disease
title_full_unstemmed 3D models improve understanding of congenital heart disease
title_short 3D models improve understanding of congenital heart disease
title_sort 3d models improve understanding of congenital heart disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8411549/
https://www.ncbi.nlm.nih.gov/pubmed/34471999
http://dx.doi.org/10.1186/s41205-021-00115-7
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