The present study aimed to evaluate the performance of QuantusFLM software, which performs quantitative analysis of lung tissue texture through ultrasound images, in predicting lung maturity in fetal growth restriction (FGR). We included patients with singleton gestations between 34 and 38 6/7 wk and divided them into two groups: FGR and control (appropriate for gestational age [AGA]). The images were captured by ultrasound according to a specific protocol up to 48 h before delivery and analyzed with QuantusFLM software. The main clinical outcome evaluated was lung maturity (i.e., the absence of neonatal respiratory morbidity). We included 111 patients; one was excluded because of low image quality, leaving 55 patients in each group. The FGR group had a lower birth weight (2207 g vs. 2891 g, p < 0.001) and a longer stay in the neonatal intensive care unit (NICU) (10 d vs. 5 d, p = 0.043). QuantusFLM software was able to predict lung maturity in FGR with accuracy, sensitivity, specificity and positive and negative predictive values of 94.5%, 96.2%, 50%, 98.1% and 33.3%, respectively. QuantusFLM had good accuracy in predicting lung maturity in FGR with reliability in identifying pulmonary maturity.
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| http://dx.doi.org/10.1016/j.ultrasmedbio.2021.08.020 | DOI Listing |
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