Automatic quantitative MRI texture analysis in small-for-gestational-age fetuses discriminates abnormal neonatal neurobehavior.

BACKGROUND: We tested the hypothesis whether texture analysis (TA) from MR images could identify patterns associated with an abnormal neurobehavior in small for gestational age (SGA) neonates. METHODS: Ultrasound and MRI were performed on 91 SGA fetuses at 37 weeks of GA. Frontal lobe, basal ganglia, mesencephalon and cerebellum were delineated from fetal MRIs. SGA neonates underwent NBAS test and were classified as abnormal if ≥ 1 area was <5(th) centile and as normal if all areas were >5(th) centile. Textural features associated with neurodevelopment were selected and machine learning was used to model a predictive algorithm. RESULTS: Of the 91 SGA neonates, 49 were classified as normal and 42 as abnormal. The accuracies to predict an abnormal neurobehavior based on TA were 95.12% for frontal lobe, 95.56% for basal ganglia, 93.18% for mesencephalon and 83.33% for cerebellum. CONCLUSIONS: Fetal brain MRI textural patterns were associated with neonatal neurodevelopment. Brain MRI TA could be a useful tool to predict abnormal neurodevelopment in SGA.

Performance of an automatic quantitative ultrasound analysis of the fetal lung to predict fetal lung maturity.

OBJECTIVE: The objective of the study was to evaluate the performance of automatic quantitative ultrasound analysis (AQUA) texture extractor to predict fetal lung maturity tests in amniotic fluid. STUDY DESIGN: Singleton pregnancies (24.0-41.0 weeks) undergoing amniocentesis to assess fetal lung maturity (TDx fetal lung maturity assay [FLM]) were included. A manual-delineated box was placed in the lung area of a 4-chamber view of the fetal thorax. AQUA transformed the information into a set of descriptors. Genetic algorithms extracted the most relevant descriptors and then created and validated a model that could distinguish between mature or immature fetal lungs using TDx-FLM as a reference. RESULTS: Gestational age at enrollment was (mean [SD]) 32.2 (4.5) weeks. According to the TDx-FLM results, 41 samples were mature and 62 were not. The imaging biomarker based on AQUA presented a sensitivity 95.1%, specificity 85.7%, and an accuracy 90.3% to predict a mature or immature lung. CONCLUSION: Fetal lung ultrasound textures extracted by AQUA provided robust features to predict TDx-FLM results.