Prediction of lung maturity through quantitative ultrasound analysis of fetal lung texture in women with diabetes during pregnancy

OBJECTIVES

The present study aimed to evaluate the performance of QuantusFLM® software, which performs quantitative ultrasound analysis of fetal lung texture, in predicting lung maturity in fetuses of diabetic mothers.

METHODS

The patients included in this study were between 34 and 38 weeks and 6 days gestation and were divided into two groups: (1) patients with diabetes on medication and (2) control. The ultrasound images were performed up to 48 h prior to delivery and analyzed using QuantusFLM® software, which classified each fetus as high or low risk for neonatal respiratory morbidity based on lung maturity or immaturity.

RESULTS

A total of 111 patients were included in the study, being 55 in diabetes and 56 in control group. The pregnant women with diabetes had significantly higher body mass index (27.8 kg/m2 vs. 25.9 kg/m2, respectively, p=0.02), increased birth weight (3,135 g vs. 2,887 g, respectively, p=0.002), and a higher rate of labor induction (63.6 vs. 30.4 %, respectively, p<0.001) compared to the control group. QuantusFLM® software was able to predict lung maturity in diabetes group with 96.4 % accuracy, 96.4 % sensitivity and 100 % positive predictive value. Considering the total number of patients, the software demonstrated accuracy, sensitivity, specificity, positive predictive value and negative predictive value of 95.5 , 97.2, 33.3, 98.1 and 25 %, respectively.

CONCLUSIONS

QuantusFLM® was an accurate method for predicting lung maturity in normal and DM singleton pregnancies and has the potential to aid in deciding the timing of delivery for pregnant women with DM.

Prediction of Neonatal Respiratory Morbidity Assessed by Quantitative Ultrasound Lung Texture Analysis in Twin Pregnancies

The objective of this study was to evaluate the performance of quantitative ultrasound of fetal lung texture analysis in predicting neonatal respiratory morbidity (NRM) in twin pregnancies. This was an ambispective study involving consecutive cases. Eligible cases included twin pregnancies between 27.0 and 38.6 weeks of gestation, for which an ultrasound image of the fetal thorax was obtained within 48 h of delivery. Images were analyzed using quantusFLM^® version 3.0. The primary outcome of this study was neonatal respiratory morbidity, defined as the occurrence of either transient tachypnea of the newborn or respiratory distress syndrome. The performance of quantusFLM^® in predicting NRM was analyzed by matching quantitative ultrasound analysis and clinical outcomes. This study included 166 images. Neonatal respiratory morbidity occurred in 12.7% of cases, and it was predicted by quantusFLM^® analysis with an overall sensitivity of 42.9%, specificity of 95.9%, positive predictive value of 60%, and negative predictive value of 92.1%. The accuracy was 89.2%, with a positive likelihood ratio of 10.4, and a negative likelihood ratio of 0.6. The results of this study demonstrate the good prediction capability of NRM in twin pregnancies using a non-invasive lung texture analysis software. The test showed an overall good performance with high specificity, negative predictive value, and accuracy.