Abstract Objectives Prenatal cardiology is a part of preventive cardiology based on fetal echocardiography and fetal interventional cardiology, which facilitates treatment of congenital heart defects (CHD) in pediatric patients and consequently in adults. Timely prenatal detection of CHD plays a pivotal role in facilitating the appropriate referral of pregnant women to facilities equipped to provide thorough perinatal care within the framework of a well-structured healthcare system. The aim of this paper is to highlight the role of left atrial strain (LAS) in prenatal evaluation of fetal heart and prediction of structural and functional disorders. Methods We conducted a comprehensive literature review searching PubMed for articles published from inception up until August 2023, including the search terms “left atrial strain”, “fetal echocardiography”, and “prenatal cardiology” combined through Boolean operators. In addition, references lists of identified articles were further reviewed for inclusion. Results Our review underscores the significance of LAS parameters in fetal echocardiography as a screening tool during specific gestational windows (starting from 11 to 14 weeks of gestation, followed by better visualization between 18 and 22 weeks of gestation). The left atrial strain technique and its parameters serve as valuable indicators, not only for identifying cardiac complications but also for predicting and guiding therapeutic interventions in cases of both cardiac and noncardiac pregnancy complications in fetuses. Evidence suggests establishment of second-trimester reference strain and strain rate values by speckle-tracking echocardiography in the healthy fetal cohort is essential for the evaluation of myocardial pathologies during pregnancy. Conclusions Finding of LAS of fetal heart is feasible and probably can have potential for clinical and prognostic implications.

BACKGROUND: Following the latest trends in the development of artificial intelligence (AI), the possibility of processing an immense amount of data has created a breakthrough in the medical field. Practitioners can now utilize AI tools to advance diagnostic protocols and improve patient care. OBJECTIVE: The aim of this article is to present the importance and modalities of AI in maternal-fetal medicine and obstetrics and its usefulness in daily clinical work and decision-making process. METHODS: A comprehensive literature review was performed by searching PubMed for articles published from inception up until August 2023, including the search terms “artificial intelligence in obstetrics”, “maternal-fetal medicine”, and “machine learning” combined through Boolean operators. In addition, references lists of identified articles were further reviewed for inclusion. RESULTS: According to recent research, AI has demonstrated remarkable potential in improving the accuracy and timeliness of diagnoses in maternal-fetal medicine and obstetrics, e.g., advancing perinatal ultrasound technique, monitoring fetal heart rate during labor, or predicting mode of delivery. The combination of AI and obstetric ultrasound can help optimize fetal ultrasound assessment by reducing examination time and improving diagnostic accuracy while reducing physician workload. CONCLUSION: The integration of AI in maternal-fetal medicine and obstetrics has the potential to significantly improve patient outcomes, enhance healthcare efficiency, and individualized care plans. As technology evolves, AI algorithms are likely to become even more sophisticated. However, the successful implementation of AI in maternal-fetal medicine and obstetrics needs to address challenges related to interpretability and reliability.