Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity.
Ultrasound Obstet Gynecol
; 45(4): 427-33, 2015 Apr.
Article
em En
| MEDLINE
| ID: mdl-24919442
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Síndrome do Desconforto Respiratório do Recém-Nascido
/
Ultrassonografia Pré-Natal
/
Pulmão
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
/
Female
/
Humans
/
Newborn
/
Pregnancy
Idioma:
En
Revista:
Ultrasound Obstet Gynecol
Assunto da revista:
DIAGNOSTICO POR IMAGEM
/
GINECOLOGIA
/
OBSTETRICIA
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Espanha