The establishment and severity assessment of ultrasound-guided prenatal bronchopulmonary dysplasia model in rat.

To study a new method for establishing animal models of prenatal bronchopulmonary dysplasia (BPD), we used lung ultrasound score (LUS) to semi-quantitatively assess the severity of lung lesions in model rats. Lipopolysaccharide (LPS) was injected into the right lung of the fetus of the rat under ultrasound-guided, and the right lung of the neonates were scanning for LUS. Specimens were collected for pathological scoring and detection of pulmonary surfactant-associated glycoprotein (SP)-C and vascular endothelial growth factor (VEGF) expression quantity. The correlation between LUS and pathological scores was analyzed. (1) The animal models were consistent with the pathological manifestations of BPD. (2) It showed a strong positive correlation between LUS and pathological scores in animal models (r = 0.84, P < 0.005), and the expression quantity of SP-C and VEGF in lung tissue were decreased (both P < 0.05). Animal models established by ultrasound-guided puncture of the lung of rats and injection of LPS were consistent with the manifestation of BPD. This method could be used to establish animal models of BPD before birth, and the severity of BPD could be assessed by using LUS.

The Right Ventricular Fetal Tricuspid Annular Plane Systolic Excursion Index Is a New Index for Evaluating Fetal Cardiac Function of Gestational Hypertension.

ABSTRACT: The right ventricular fetal tricuspid annular plane systolic excursion index (FTI) can be used to evaluate right ventricular systolic function. The purpose of this study was to establish the reference range of the FTI in normal fetuses and evaluate its diagnostic value in hypertensive disorders during pregnancy. In this prospective observational study, the right ventricular FTI was measured in 208 normal single-gestation fetuses between 20 and 40 weeks. With the increase in gestational age, the right ventricular FTI did not significantly fluctuate. With the increase in the severity of HDCP, the right ventricular FTI decreased gradually. Compared with the normal group, the low right ventricular FTI group had a higher incidence of premature delivery and emergency delivery due to continuous abnormal fetal heart monitoring, but there were no significant differences in low birth weight, new born Apgar score less than 7 in 5 minutes, or admission to the neonatal intensive care unit. The FTI of the right ventricle of normal fetuses is relatively constant at different gestational weeks. The right ventricular FTI can be used to evaluate fetal cardiac function changes in pregnant women with HDCP.

Application of Artificial Intelligence in Anatomical Structure Recognition of Standard Section of Fetal Heart.

Congenital heart defect (CHD) refers to the overall structural abnormality of the heart or large blood vessels in the chest cavity. It is the most common type of fetal congenital defects. Prenatal diagnosis of congenital heart disease can improve the prognosis of the fetus to a certain extent. At present, prenatal diagnosis of CHD mainly uses 2D ultrasound to directly evaluate the development and function of fetal heart and main structures in the second trimester of pregnancy. Artificial recognition of fetal heart 2D ultrasound is a highly complex and tedious task, which requires a long period of prenatal training and practical experience. Compared with manual scanning, computer automatic identification and classification can significantly save time, ensure efficiency, and improve the accuracy of diagnosis. In this paper, an effective artificial intelligence recognition model is established by combining ultrasound images with artificial intelligence technology to assist ultrasound doctors in prenatal ultrasound fetal heart standard section recognition. The method data in this paper were obtained from the Second Affiliated Hospital of Fujian Medical University. The fetal apical four-chamber heart section, three vessel catheter section, three vessel trachea section, right ventricular outflow tract section, and left ventricular outflow tract section were collected at 20-24 weeks of gestation. 2687 image data were used for model establishment, and 673 image data were used for model validation. The experiment shows that the map value of this method in identifying different anatomical structures reaches 94.30%, the average accuracy rate reaches 94.60%, the average recall rate reaches 91.0%, and the average F1 coefficient reaches 93.40%. The experimental results show that this method can effectively identify the anatomical structures of different fetal heart sections and judge the standard sections according to these anatomical structures, which can provide an auxiliary diagnostic basis for ultrasound doctors to scan and lay a solid foundation for the diagnosis of congenital heart disease.