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Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease

The study aimed to evaluate the effectiveness of blood pool and myocardial models made by stereolithography in the diagnosis of different types of congenital heart disease (CHD). Two modeling methods were applied in the diagnosis of 8 cases, and two control groups consisting of experts and students...

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Autores principales: Liang, Jixiang, Zhao, Xin, Pan, Guangyu, Zhang, Gen, Zhao, Dianjiang, Xu, Jianping, Li, Dianyuan, Lu, Bingheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065034/
https://www.ncbi.nlm.nih.gov/pubmed/35505074
http://dx.doi.org/10.1038/s41598-022-11294-6
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author Liang, Jixiang
Zhao, Xin
Pan, Guangyu
Zhang, Gen
Zhao, Dianjiang
Xu, Jianping
Li, Dianyuan
Lu, Bingheng
author_facet Liang, Jixiang
Zhao, Xin
Pan, Guangyu
Zhang, Gen
Zhao, Dianjiang
Xu, Jianping
Li, Dianyuan
Lu, Bingheng
author_sort Liang, Jixiang
collection PubMed
description The study aimed to evaluate the effectiveness of blood pool and myocardial models made by stereolithography in the diagnosis of different types of congenital heart disease (CHD). Two modeling methods were applied in the diagnosis of 8 cases, and two control groups consisting of experts and students diagnosed the cases using echocardiography with computed tomography, blood pool models, and myocardial models. The importance, suitability, and simulation degree of different models were analyzed. The average diagnostic rate before and after 3D printing was used was 88.75% and 95.9% (P = 0.001) in the expert group and 60% and 91.6% (P = 0.000) in the student group, respectively. 3D printing was considered to be more important for the diagnosis of complex CHDs (very important; average, 87.8%) than simple CHDs (very important; average, 30.8%) (P = 0.000). Myocardial models were considered most realistic regarding the structure of the heart (average, 92.5%). In cases of congenital corrected transposition of great arteries, Williams syndrome, coronary artery fistula, tetralogy of Fallot, patent ductus arteriosus, and coarctation of the aorta, blood pool models were considered more effective (average, 92.1%), while in cases of double outlet right ventricle and ventricular septal defect, myocardial models were considered optimal (average, 80%).
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spelling pubmed-90650342022-05-04 Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease Liang, Jixiang Zhao, Xin Pan, Guangyu Zhang, Gen Zhao, Dianjiang Xu, Jianping Li, Dianyuan Lu, Bingheng Sci Rep Article The study aimed to evaluate the effectiveness of blood pool and myocardial models made by stereolithography in the diagnosis of different types of congenital heart disease (CHD). Two modeling methods were applied in the diagnosis of 8 cases, and two control groups consisting of experts and students diagnosed the cases using echocardiography with computed tomography, blood pool models, and myocardial models. The importance, suitability, and simulation degree of different models were analyzed. The average diagnostic rate before and after 3D printing was used was 88.75% and 95.9% (P = 0.001) in the expert group and 60% and 91.6% (P = 0.000) in the student group, respectively. 3D printing was considered to be more important for the diagnosis of complex CHDs (very important; average, 87.8%) than simple CHDs (very important; average, 30.8%) (P = 0.000). Myocardial models were considered most realistic regarding the structure of the heart (average, 92.5%). In cases of congenital corrected transposition of great arteries, Williams syndrome, coronary artery fistula, tetralogy of Fallot, patent ductus arteriosus, and coarctation of the aorta, blood pool models were considered more effective (average, 92.1%), while in cases of double outlet right ventricle and ventricular septal defect, myocardial models were considered optimal (average, 80%). Nature Publishing Group UK 2022-05-03 /pmc/articles/PMC9065034/ /pubmed/35505074 http://dx.doi.org/10.1038/s41598-022-11294-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Article
Liang, Jixiang
Zhao, Xin
Pan, Guangyu
Zhang, Gen
Zhao, Dianjiang
Xu, Jianping
Li, Dianyuan
Lu, Bingheng
Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title_full Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title_fullStr Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title_full_unstemmed Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title_short Comparison of blood pool and myocardial 3D printing in the diagnosis of types of congenital heart disease
title_sort comparison of blood pool and myocardial 3d printing in the diagnosis of types of congenital heart disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065034/
https://www.ncbi.nlm.nih.gov/pubmed/35505074
http://dx.doi.org/10.1038/s41598-022-11294-6
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