title: Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity.
abstract: OBJECTIVE
  To develop and evaluate the performance of a novel method for predicting neonatal respiratory morbidity based on quantitative analysis of the fetal lung by ultrasound.
  
  
  METHODS
  More than 13,000 non-clinical images and 900 fetal lung images were used to develop a computerized method based on texture analysis and machine learning algorithms, trained to predict neonatal respiratory morbidity risk on fetal lung ultrasound images. The method, termed 'quantitative ultrasound fetal lung maturity analysis' (quantusFLM™), was then validated blindly in 144 neonates, delivered at 28 + 0 to 39 + 0 weeks' gestation. Lung ultrasound images in DICOM format were obtained within 48 h of delivery and the ability of the software to predict neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, was determined.
  
  
  RESULTS
  Mean (SD) gestational age at delivery was 36 + 1 (3 + 3) weeks. Among the 144 neonates, there were 29 (20.1%) cases of neonatal respiratory morbidity. Quantitative texture analysis predicted neonatal respiratory morbidity with a sensitivity, specificity, positive predictive value and negative predictive value of 86.2%, 87.0%, 62.5% and 96.2%, respectively.
  
  
  CONCLUSIONS
  Quantitative ultrasound fetal lung maturity analysis predicted neonatal respiratory morbidity with an accuracy comparable to that of current tests using amniotic fluid.
authors.affiliation: Transmural Biotech SL, Barcelona, Spain.
authors.forename: E
authors.initials: E
authors.lastname: Bonet-Carne
authors.forename: M
authors.initials: M
authors.lastname: Palacio
authors.forename: T
authors.initials: T
authors.lastname: Cobo
authors.forename: A
authors.initials: A
authors.lastname: Perez-Moreno
authors.forename: M
authors.initials: M
authors.lastname: Lopez
authors.forename: J P
authors.initials: JP
authors.lastname: Piraquive
authors.forename: J C
authors.initials: JC
authors.lastname: Ramirez
authors.forename: F
authors.initials: F
authors.lastname: Botet
authors.forename: F
authors.initials: F
authors.lastname: Marques
authors.forename: E
authors.initials: E
authors.lastname: Gratacos
mesh_terms: D000328:Adult; D000465:Algorithms; D000653:Amniotic Fluid / Q000000981:diagnostic imaging; D036861:Delivery, Obstetric; D005069:Evaluation Studies as Topic; D005260:Female; D005325:Fetal Organ Maturity / Q000502:physiology; D006801:Humans; D007231:Infant, Newborn; D008168:Lung / Q000000981:diagnostic imaging* / Q000196:embryology*; D011237:Predictive Value of Tests; D011247:Pregnancy; D011446:Prospective Studies; D012127:Respiratory Distress Syndrome, Newborn / Q000000981:diagnostic imaging* / Q000401:mortality; D016216:Ultrasonography, Prenatal / Q000379:methods*
keywords: fetal lung maturity; image quantitative analysis; neonatal respiratory morbidity; texture analysis