Neurological impairment disorders in fetuses, such as cerebral palsy, epilepsy, and autism spectrum disorder, can arise from numerous factors impacting the development of the fetal nervous system. Although diagnosing these disorders early is difficult, it is essential for prompt intervention. Recent progress in deep learning and ultrasound technology offers the potential to create a tool for early detection. Development of the TRUEAID system is based on combining the meticulously tuned Kurjak Antenatal Neurodevelopmental Test (KANET) with a sophisticated convolutional neural network for construction of an AI empowered ultrasound module capable of automated diagnostic decision support in the field of fetal neurodevelopmental risk assessment. The model's performance was evaluated using accuracy metrics, precision, sensitivity, specificity, F1 score, and Mathesson Correlation Coefficient (MCC). The custom CNN architecture achieved an overall accuracy of 93.83%. This pilot study lays the foundation for AI-based fetal neurobehavioral assessment, providing a promising tool for the early detection of fetal neurological impairment disorders. The research holds implications for improving outcomes for affected children and making advanced diagnostic capabilities accessible in diverse healthcare settings.

BACKGROUND Left atrial strain (LAS) analysis represents a newer non-invasive, sensitive and specific technique for assessing left atrial (LA) function and early detection of its deformation and dysfunction. However, its applicability in mitral regurgitation (MR) in pediatric population remains unexplored, raising pertinent questions regarding its potential role in evaluating the severity and progression of the disease. OBJECTIVE To investigate the impact of chronic MR in children and adolescents on LA remodeling and function. METHODS The study included 100 participants. Patients with primary and secondary chronic MR lasting at least 5 years fit our inclusion criteria. The exclusion criteria from the study were: patients with functional mitral regurgitation due to primary cardiomyopathies, patients with artificial mitral valve, patients with MR who had previously undergone surgery due to obstructive lesions of the left heart (aortic stenosis, coarctation of the aorta), patients with significant atrial rhythm disorders (atrial fibrillation, atrial flutter). The echocardiographic recordings were conducted by two different cardiologists. Outcome data was reported as mean and standard deviation (SD) or median and interquartile range (Q1-Q3). RESULTS The study included 100 participants, of whom 50 had MR and the remaining 50 were without MR. The average age of all participants was 15.8 ± 1.2 years, with a gender distribution of 37 males and 63 females. There was a significant difference in the values of LA volume index (LAVI), which were higher in patients with MR (p= 0.0001), S/D ratio (and parameters S and D; p= 0.001, p= 0.0001, p= 0.013), mitral annulus radius (p= 0.0001), E/A ratio (p= 0.0001), as well as septal e' (m/s), lateral e' (m/s), and average E/e' ratio, along with the values of TV peak gradient and LV global longitudinal strain (%). There was no significant difference in LA strain parameters, nor in LA stiffness index (LASI). CONCLUSION Our findings revealed significant differences in several echocardiographic parameters in pediatric patients with MR relative to those without MR, providing insight into the multifaceted cardiac structural and functional effects of MR in this vulnerable population.

BACKGROUND Left atrial stiffness index (LASI), defined as the ratio of early diastolic transmitral flow velocity/lateral mitral annulus myocardial velocity (E/e') to peak atrial strain, reflects reduced left atrial (LA) compliance and represents an emerging marker that can be used for noninvasive measurement of fibrosis of LA in patients with mitral regurgitation (MR). OBJECTIVE To investigate the impact of chronic MR in children and adolescents on the remodeling and function of the LA, quantified through strain parameters and diastolic function. METHODS The study included fifty patients (n= 50) diagnosed with primary and secondary chronic MR lasting at least 5 years. The echocardiographic recordings were performed by a third party, two cardiologists actively engaged in echocardiography on a daily basis. RESULTS Older participants had higher values of the LASI (r= 0.467, p= 0.001). Participants with higher LASI values had a smaller LA reservoir (r= 0.784, p= 0.0001) and smaller LA conduit values (r=-0.374, p= 0.00). Participants with higher LASI values had a larger LA diameter (r= 0.444, p-value= 0.001) and higher average E/e' ratio (r= 0.718, p= 0.0001). There was a significant difference (p= 0.04) in the LASI among participants based on the MR jet area (< 20.85 cm2/⩾ 20.85 cm2), LASI was higher in participants with an area greater than 20.85 cm2. Differences in other parameters such as LA reservoir, LA conduit, LA contractile were not statistically significant. CONCLUSION Increased LA stiffness is associated with diminished atrial compliance and reservoir capacity, and LASI has a potential to as an early marker for assessing disease severity and progression in pediatric MR.

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.

BACKGROUND Left atrial (LA) strain analysis has emerged as a noninvasive technique for assessing LA function and early detection of myocardial deformation. Recently, its application has also shown promise in the pediatric population, spanning diverse cardiac conditions that demand accurate and sensitive diagnostic measures. OBJECTIVE This research endeavors to explore the role of LA strain parameters and contribute to the growing body of knowledge in pediatric cardiology, paving the way for more effective and tailored approaches to patient care. METHODS A comprehensive literature review was conducted to gather evidence from studies using echocardiographic strain imaging techniques across pediatric populations. RESULTS LA strain parameters exhibited greater sensitivity than conventional atrial function indicators, with early detection of diastolic dysfunction and LA remodeling in pediatric cardiomyopathy, children with multisystem inflammatory syndrome, rheumatic heart disease, as well as childhood renal insufficiency and obesity offering prognostic relevance as potential markers in these pediatric subpopulations. However, there remains a paucity of evidence concerning pediatric mitral valve pathology, justifying further exploration. CONCLUSION LA strain analysis carries crucial clinical and prognostic implications in pediatric cardiac conditions, with reliable accuracy and sensitivity to early functional changes.