Intrapartum ultrasound and the choice between assisted vaginal and cesarean delivery

Abstract

Inaccurate assessment of the fetal head position and station might increase the risk for difficult or failed assisted vaginal delivery. Compared with digital vaginal examination, an ultrasound examination is objective and more accurate. The International Society of Ultrasound in Obstetrics and Gynecology has issued practical guidelines on intrapartum ultrasound in 2018 and recommended that an ultrasound assessment should be conducted when there is suspected delay or arrest of the first or second stage of labor or before considering assisted vaginal delivery. Fetal head position is assessed transabdominally by identifying the fetal occiput, orbit, or midline cerebral echo. Studies have shown that ultrasound assessment improved the correct diagnosis of fetal head position and accuracy of instrument placement, however, it did not reduce morbidity. Studies on ultrasound assessment of asynclitism are limited but show promising results. Fetal head station is assessed transperineally in the midsagittal or axial plane. Of the various ultrasound parameters, angle of progression and head-perineum distance are the most widely studied and found to be highly correlated with the clinical fetal head station. An angle of progression of 120° correlates with a clinical head station of 0 and is an important landmark for engagement of successful vaginal delivery, whereas an angle of progression of 145° correlates with a clinical head station of ≥+2 and has been associated with successful assisted vaginal delivery. In contrast, a head perineum distance of ≥40 mm has been associated with an increased risk for difficult assisted vaginal delivery. A "head-up" direction of descent assessed transperineally in sagittal plane is also a favorable factor for successful vaginal delivery. Current evidence seems to suggest that a prediction model with >1 sonographic parameter performed better than a model that only used 1 parameter. We suggest that an algorithm model incorporating both clinical and sonographic parameters would be useful in guiding clinicians on their decision for assisted vaginal delivery.