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Updated: Jul 13, 2025
Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System
Published on: May 5, 2018
Looking at a baby's heart through the lens of the mother's blood
1Bristol Medical School, Translational Health Sciences, and Bristol Heart Institute, University of Bristol, Bristol, UK.
Insights
Researchers developed a new method using artificial intelligence and proteomic data from maternal blood for early congenital heart disease (CHD) screening. This approach aims to improve upon fetal echocardiography limitations for better in-utero diagnosis.
Area of Science:
- Cardiovascular Medicine
- Proteomics
- Bioinformatics
- Artificial Intelligence
Background:
- Congenital heart disease (CHD) encompasses a spectrum of birth-related cardiovascular abnormalities.
- Current in-utero diagnostic methods like fetal echocardiography have limitations in detecting all types of CHD, particularly those affecting pulmonary veins, atrioventricular valves, or developing later in pregnancy.
- Accurate and early diagnosis of CHD is crucial for timely intervention and improved patient outcomes.
Abstract:
Congenital heart disease (CHD) comprises several cardiovascular abnormalities existing from birth. Cardiac defects range from minor asymptomatic lesions to potentially life-threatening situations. Early fetal echocardiography, the gold standard for the in-utero diagnosis of CHD, is inaccurate at identifying defects in pulmonary veins and atrioventricular valves or lesions that occur later or progress during pregnancy. In this issue of EMBO Molecular Medicine, Yin et al report new proteomic data on maternal blood samples and a novel bioinformatic and artificial intelligence approach for the early diagnosis and screening of CHD.
