Fetal Weight Estimation Using Automated Fractional Limb Volume With 2-Dimensional Size Parameters in Diabetic Pregnancies.

Abstract

To examine the effect of adding automated fetal fractional limb volume (FLV) with conventional 2-dimensional (2D) fetal weight estimation procedures in a cohort of diabetic pregnancies. A pilot study of diabetic pregnancies measured standard fetal biometry within 7 days of delivery. Fractional arm volume (AVol) and fractional thigh volume (TVol) soft tissue parameters were measured with a commercially available automated software utility (5D Limb Vol; Samsung Medison Co, Ltd, Seoul, Korea). Three conventional weight prediction models that included only 2D size parameters were compared to FLV models that included AVol or TVol. Estimated and actual birth weight (BW) were assessed for the mean percent difference ± standard deviation of the percent differences. Systematic errors were evaluated by the Student t test, and random errors were compared by the Pitman test for correlated variances. The proportion of neonates with estimated fetal weight within 10% of BW was compared between groups by the McNemar test. Ninety gravid women were enrolled with pregestational (26.7%) or gestational (73.3%) diabetes. All prediction models were accurate, with the exception of small underestimations by the model of Schild et al (-3.8%; Ultrasound Obstet Gynecol 2004; 23:30-35). Random errors for the AVol (6.2%) and TVol (6.9%) models were significantly more precise than the other 3 prediction models: Hadlock et al (7.8%; Am J Obstet Gynecol 1985; 151:333-337), INTERGROWTH-21st (8.0%; Ultrasound Obstet Gynecol 2017; 49:478-486), and Schild et al (8.6%; P < .01). The greatest proportion of cases with BW ±10% was also classified by the AVol (91.1%) and TVol (91.1%) models, followed by Hadlock (83.3%), INTERGROWTH-21st (78.9%), and Schild (76.7%) predictions. The addition of automated FLV measurements to conventional 2D biometry was associated with improved weight predictions in this cohort of diabetic pregnancies.