Descent of the presenting part assessed with ultrasound

Artificial Intelligence, Intrapartum Ultrasound and Dystocic Delivery: AIDA (Artificial Intelligence Dystocia Algorithm), a Promising Helping Decision Support System

The position of the fetal head during engagement and progression in the birth canal is the primary cause of dystocic labor and arrest of progression, often due to malposition and malrotation. The authors performed an investigation on pregnant women in labor, who all underwent vaginal digital examination by obstetricians and midwives as well as intrapartum ultrasonography to collect four "geometric parameters", measured in all the women. All parameters were measured using artificial intelligence and machine learning algorithms, called AIDA (artificial intelligence dystocia algorithm), which incorporates a human-in-the-loop approach, that is, to use AI (artificial intelligence) algorithms that prioritize the physician's decision and explainable artificial intelligence (XAI). The AIDA was structured into five classes. After a number of "geometric parameters" were collected, the data obtained from the AIDA analysis were entered into a red, yellow, or green zone, linked to the analysis of the progress of labor. Using the AIDA analysis, we were able to identify five reference classes for patients in labor, each of which had a certain sort of birth outcome. A 100% cesarean birth prediction was made in two of these five classes. The use of artificial intelligence, through the evaluation of certain obstetric parameters in specific decision-making algorithms, allows physicians to systematically understand how the results of the algorithms can be explained. This approach can be useful in evaluating the progress of labor and predicting the labor outcome, including spontaneous, whether operative VD (vaginal delivery) should be attempted, or if ICD (intrapartum cesarean delivery) is preferable or necessary.

Parturition at term: induction, second and third stages of labor, and optimal management of life-threatening complications-hemorrhage, infection, and uterine rupture

Childbirth is a defining moment in anyone's life, and it occurs 140 million times per year. Largely a physiologic process, parturition does come with risks; one mother dies every two minutes. These deaths occur mostly among healthy women, and many are considered preventable. For each death, 20 to 30 mothers experience complications that compromise their short- and long-term health. The risk of birth extends to the newborn, and, in 2020, 2.4 million neonates died, 25% in the first day of life. Hence, intrapartum care is an important priority for society. The American Journal of Obstetrics & Gynecology has devoted two special Supplements in 2023 and 2024 to the clinical aspects of labor at term. This article describes the content of the Supplements and highlights new developments in the induction of labor (a comparison of methods, definition of failed induction, new pharmacologic agents), management of the second stage, the value of intrapartum sonography, new concepts on soft tissue dystocia, optimal care during the third stage, and common complications that account for maternal death, such as infection, hemorrhage, and uterine rupture. All articles are available to subscribers and non-subscribers and have supporting video content to enhance dissemination and improve intrapartum care. Our hope is that no mother suffers because of lack of information.

The sonopartogram

The assessment of labor progress from digital vaginal examination has remained largely unchanged for at least a century, despite the current major advances in maternal and perinatal care. Although inconsistently reproducible, the findings from digital vaginal examination are customarily plotted manually on a partogram, which is composed of a graphical representation of labor, together with maternal and fetal observations. The partogram has been developed to aid recognition of failure to labor progress and guide management-specific obstetrical intervention. In the last decade, the use of ultrasound in the delivery room has increased with the advent of more powerful, portable ultrasound machines that have become more readily available for use. Although ultrasound in intrapartum practice is predominantly used for acute management, an ultrasound-based partogram, a sonopartogram, might represent an objective tool for the graphical representation of labor. Demonstrating greater accuracy for fetal head position and more objectivity in the assessment of fetal head station, it could be considered complementary to traditional clinical assessment. The development of the sonopartogram concept would require further undertaking of serial measurements. Advocates of ultrasound will concede that its use has yet to demonstrate a difference in obstetrical and neonatal morbidity in the context of the management of labor and delivery. Taking a step beyond the descriptive graphical representation of labor progress is the question of whether a specific combination of clinical and demographic parameters might be used to inform knowledge of labor outcomes. Intrapartum cesarean deliveries and deliveries assisted by forceps and vacuum are all associated with a heightened risk of maternal and perinatal adverse outcomes. Although these outcomes cannot be precisely predicted, many known risk factors exist. Malposition and high station of the fetal head, short maternal stature, and other factors, such as caput succedaneum, are all implicated in operative delivery; however, the contribution of individual parameters based on clinical and ultrasound assessments has not been quantified. Individualized risk prediction models, including maternal characteristics and ultrasound findings, are increasingly used in women's health-for example, in preeclampsia or trisomy screening. Similarly, intrapartum cesarean delivery models have been developed with good prognostic ability in specifically selected populations. For intrapartum ultrasound to be of prognostic value, robust, externally validated prediction models for labor outcome would inform delivery management and allow shared decision-making with parents.

Asynclitism and Its Ultrasonographic Rediscovery in Labor Room to Date: A Systematic Review

Asynclitism, the most feared malposition of the fetal head during labor, still represents to date an unresolved field of interest, remaining one of the most common causes of prolonged or obstructed labor, dystocia, assisted delivery, and cesarean section. Traditionally asynclitism is diagnosed by vaginal examination, which is, however, burdened by a high grade of bias. On the contrary, the recent scientific evidence highly suggests the use of intrapartum ultrasonography, which would be more accurate and reliable when compared to the vaginal examination for malposition assessment. The early detection and characterization of asynclitism by intrapartum ultrasound would become a valid tool for intrapartum evaluation. In this way, it will be possible for physicians to opt for the safest way of delivery according to an accurate definition of the fetal head position and station, avoiding unnecessary operative procedures and medication while improving fetal and maternal outcomes. This review re-evaluated the literature of the last 30 years on asynclitism, focusing on the progressive imposition of ultrasound as an intrapartum diagnostic tool. All the evidence emerging from the literature is presented and evaluated from our point of view, describing the most employed technique and considering the future implication of the progressive worldwide consolidation of asynclitism and ultrasound.

Ultrasound in labor: clinical practice guideline and recommendation by the WAPM-World Association of Perinatal Medicine and the PMF-Perinatal Medicine Foundation

This recommendation document follows the mission of the World Association of Perinatal Medicine in collaboration with the Perinatal Medicine Foundation. We aim to bring together groups and individuals throughout the world for standardization to implement the ultrasound evaluation in labor ward and improve the clinical management of labor. Ultrasound in labor can be performed using a transabdominal or a transperineal approach depending upon which parameters are being assessed. During transabdominal imaging, fetal anatomy, presentation, liquor volume, and placental localization can be determined. The transperineal images depict images of the fetal head in which calculations to determine a proposed fetal head station can be made.

Multitask Deep Neural Network for the Fully Automatic Measurement of the Angle of Progression

The angle of progression (AoP) for assessing fetal head (FH) descent during labor is measured from the standard plane of transperineal ultrasound images as the angle between a line through the long axis of pubic symphysis (PS) and a second line from the right end of PS tangentially to the contour of the FH. This paper presents a multitask network with a shared feature encoder and three task-special decoders for standard plane recognition (Task1), image segmentation (Task2) of PS and FH, and endpoint detection (Task3) of PS. Based on the segmented FH and two endpoints of PS from standard plane images, we determined the right FH tangent point that passes through the right endpoint of PS and then computed the AoP using the above three points. In this paper, the efficient channel attention unit is introduced into the shared feature encoder for improving the robustness of layer region encoding, while an attention fusion module is used to promote cross-branch interaction between the encoder for Task2 and that for Task3, and a shape-constrained loss function is designed for enhancing the robustness to noise based on the convex shape-prior. We use Pearson's correlation coefficient and the Bland–Altman graph to assess the degree of agreement. The dataset includes 1964 images, where 919 images are nonstandard planes, and the other 1045 images are standard planes including PS and FH. We achieve a classification accuracy of 92.26%, and for the AoP calculation, an absolute mean (STD) value of the difference in AoP (∆AoP) is 3.898° (3.192°), the Pearson's correlation coefficient between manual and automated AoP was 0.964 and the Bland-Altman plot demonstrates they were statistically significant (P < 0.05). In conclusion, our approach can achieve a fully automatic measurement of AoP with good efficiency and may help labor progress in the future.