Artificial intelligence in ultrasound diagnosis of fetal congenital malformations: a review

Abstract

Timely detection of congenital malformations of the fetus remains one of the urgent problems of modern prenatal diagnostics. The survival rate of children, the volume and quality of medical care during treatment and rehabilitation directly depend on early and reliable diagnosis. In modern medicine, prenatal diagnosis is an obligatory complex of medical manipulations, various methods of examining patients to monitor the health of a pregnant woman and fetus. Ultrasound is one of the main methods of medical imaging, as it is non-invasive, safe and informative in the examination of pregnant women. Recently, technologies for processing video files and static images using artificial intelligence have been actively used in ultrasound diagnostics. This review collects and analyzes 52 sources by both foreign and domestic authors. The list of sources used includes domestic and foreign original research in the field of the use of artificial intelligence in prenatal diagnostics, systematic reviews, methodological manuals, practical and clinical recommendations, and monographs. PubMed, Google Scholar, and eLibrary were selected as search engines. A comprehensive search was performed using keywords in Russian and English: искусственный интеллект / artificial intelligence, ультразвуковая диагностика / ultrasound diagnostics, нейросеть / neural network, плод / fetus, and врождённые пороки развития / congenital malformations. The search depth was 6 years (from 2020 to 2025). The review revealed the obvious advantages of using neural network systems in prenatal diagnostics. Automation and standardization of fetal ultrasound examination make it possible to create a real-time neural network analysis algorithm and ensure quality control of the resulting echographic images. The undoubted advantages of artificial intelligence technologies are minimizing the variability of instrumental diagnosis between different specialists and reducing the time to obtain the “correct” echographic section. In addition, artificial intelligence enables the automatic identification of standard scanning planes, “recognition” of anatomical structures, and biometric measurements in the fetus. There are problems associated with the introduction of modern intelligent decision support systems in healthcare around the world and in Russia in particular. The most pressing issues are medical, legal, and ethical issues, the problem of lack of transparency in decision-making (“black box”), leading to skepticism among specialists, and poor effectiveness in diagnosing rare anomalies due to the small amount of training material. Today, modern computer technologies with the function of neural network analysis in prenatal diagnostics should be considered as a powerful auxiliary tool for doctors.

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