ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2020
CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Spectrum of Congenital Heart Diseases in Iraqi Patients.The Eurasian journal of medicine · 2026Article
- Deep learning-based detection of murine congenital heart defects from µCT scans.Communications biology · 2025Article
- Global, regional, and national epidemiology of congenital heart disease in children from 1990 to 2021.Frontiers in cardiovascular medicine · 2025Article
- Single-cell RNA sequencing profiling of mouse cardiac cells in response to retinoic acid.Heliyon · 2024Article
- Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review.Frontiers in pharmacology · 2024Review
- Omentin-1 drives cardiomyocyte cell cycle arrest and metabolic maturation by interacting with BMP7.Cellular and molecular life sciences : CMLS · 2023Article
- EZH2 controls epicardial cell migration during heart development.Life science alliance · 2023Article
- How Parental Predictors Jointly Affect the Risk of Offspring Congenital Heart Disease: A Nationwide Multicenter Study Based on the China Birth Cohort.Frontiers in cardiovascular medicine · 2022Article
- CACCT: An Automated Tool of Detecting Complicated Cardiac Malformations in Mouse Models.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Article
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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