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CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models
Congenital heart disease (CHD) is the major cause of morbidity/mortality in infancy and childhood. Using a mouse model to uncover the mechanism of CHD is essential to understand its pathogenesis. However, conventional 2D phenotyping methods cannot comprehensively exhibit and accurately distinguish v...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175298/ https://www.ncbi.nlm.nih.gov/pubmed/32328433 http://dx.doi.org/10.1002/advs.201903592 |
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author | Chu, Qing Jiang, Haobin Zhang, Libo Zhu, Dekun Yin, Qianqian Zhang, Hao Zhou, Bin Zhou, Wenzhang Yue, Zhang Lian, Hong Liu, Lihui Nie, Yu Hu, Shengshou |
author_facet | Chu, Qing Jiang, Haobin Zhang, Libo Zhu, Dekun Yin, Qianqian Zhang, Hao Zhou, Bin Zhou, Wenzhang Yue, Zhang Lian, Hong Liu, Lihui Nie, Yu Hu, Shengshou |
author_sort | Chu, Qing |
collection | PubMed |
description | Congenital heart disease (CHD) is the major cause of morbidity/mortality in infancy and childhood. Using a mouse model to uncover the mechanism of CHD is essential to understand its pathogenesis. However, conventional 2D phenotyping methods cannot comprehensively exhibit and accurately distinguish various 3D cardiac malformations for the complicated structure of heart cavity. Here, a new automated tool based on microcomputed tomography (micro‐CT) image data sets known as computer‐assisted cardiac cavity tracking (CACCT) is presented, which can detect the connections between cardiac cavities and identify complicated cardiac malformations in mouse hearts automatically. With CACCT, researchers, even those without expert training or diagnostic experience of CHD, can identify complicated cardiac malformations in mice conveniently and precisely, including transposition of the great arteries, double‐outlet right ventricle and atypical ventricular septal defect, whose accuracy is equivalent to senior fetal cardiologists. CACCT provides an effective approach to accurately identify heterogeneous cardiac malformations, which will facilitate the mechanistic studies into CHD and heart development. |
format | Online Article Text |
id | pubmed-7175298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71752982020-04-23 CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models Chu, Qing Jiang, Haobin Zhang, Libo Zhu, Dekun Yin, Qianqian Zhang, Hao Zhou, Bin Zhou, Wenzhang Yue, Zhang Lian, Hong Liu, Lihui Nie, Yu Hu, Shengshou Adv Sci (Weinh) Full Papers Congenital heart disease (CHD) is the major cause of morbidity/mortality in infancy and childhood. Using a mouse model to uncover the mechanism of CHD is essential to understand its pathogenesis. However, conventional 2D phenotyping methods cannot comprehensively exhibit and accurately distinguish various 3D cardiac malformations for the complicated structure of heart cavity. Here, a new automated tool based on microcomputed tomography (micro‐CT) image data sets known as computer‐assisted cardiac cavity tracking (CACCT) is presented, which can detect the connections between cardiac cavities and identify complicated cardiac malformations in mouse hearts automatically. With CACCT, researchers, even those without expert training or diagnostic experience of CHD, can identify complicated cardiac malformations in mice conveniently and precisely, including transposition of the great arteries, double‐outlet right ventricle and atypical ventricular septal defect, whose accuracy is equivalent to senior fetal cardiologists. CACCT provides an effective approach to accurately identify heterogeneous cardiac malformations, which will facilitate the mechanistic studies into CHD and heart development. John Wiley and Sons Inc. 2020-02-20 /pmc/articles/PMC7175298/ /pubmed/32328433 http://dx.doi.org/10.1002/advs.201903592 Text en © 2020 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Full Papers Chu, Qing Jiang, Haobin Zhang, Libo Zhu, Dekun Yin, Qianqian Zhang, Hao Zhou, Bin Zhou, Wenzhang Yue, Zhang Lian, Hong Liu, Lihui Nie, Yu Hu, Shengshou CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title | CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title_full | CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title_fullStr | CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title_full_unstemmed | CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title_short | CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models |
title_sort | cacct: an automated tool of detecting complicated cardiac malformations in mouse models |
topic | Full Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175298/ https://www.ncbi.nlm.nih.gov/pubmed/32328433 http://dx.doi.org/10.1002/advs.201903592 |
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