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Magnetic resonance imaging of the supra-cervical fetal membrane detects an increased risk of prelabor rupture of membranes

Wenxu Qi, Peinan Zhao, Wei Wang and 10 more

Frontiers in Endocrinology · 2022

doi:10.3389/fendo.2022.1001538 (opens in a new tab)

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Abstract

Objective In 10% of term deliveries and 40% of preterm deliveries, the fetal membrane (FM) ruptures before labor. However, the ability to predict these cases of premature rupture of membranes (PROM) and preterm premature rupture of membranes (PPROM) is very limited. In this paper, our objective was to determine whether a prediction method based on T2 weighted magnetic resonance imaging (MRI) of the supra-cervical FM could predict PROM and PPROM. Methods This prospective cohort study enrolled 77 women between the 28th and 37th weeks of gestation. Two indicators of fetal membrane defects, including prolapsed depth >5 mm and signal abnormalities, are investigated for our prediction. Fisher’s exact test was used to determine whether prolapsed depth >5 mm and/or signal abnormalities were associated with PROM and PPROM. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for prolapsed depth >5 mm, signal abnormalities, and the combination of prolapsed depth >5 mm and signal abnormalities. Result Among 12 women with PROM (5 preterm and 7 term, prior to labor onset), 9 had membrane prolapse >5 mm and 5 had FM signal abnormalities. Among 65 women with rupture of membranes at term, 2 had membrane prolapse >5 mm and 1 had signal abnormalities. By Fisher’s exact test both indicators, membrane prolapse >5 mm and signal abnormalities, were associated with PROM (P<0.001, P<0.001) and PPROM (P=0.001, P<0.001). Additionally, membrane prolapse >5 mm, signal abnormalities, and the combination of the two indicators all demonstrated high specificity for predicting PROM (96.9%, 98.5%, and 100%, respectively) and PPROM (90.3%, 97.2%, and 100%, respectively). Conclusion MRI can distinguish the supra-cervical fetal membrane in vivo and may be able to identify women at high risk of PPROM.

Abstract licence: CC BY

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