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.

[1]  I. Žalud,et al.  Risks of third-trimester amniocentesis. , 2008, The Journal of reproductive medicine.

[2]  S. Schmidt,et al.  Assessment of fetal lung development by quantitative ultrasonic tissue characterization: a methodical study , 2004, Prenatal diagnosis.

[3]  Jacek M. Zurada,et al.  Classification algorithms for quantitative tissue characterization of diffuse liver disease from ultrasound images , 1996, IEEE Trans. Medical Imaging.

[4]  A. V. van Kaam,et al.  A systematic review of severe morbidity in infants born late preterm. , 2011, American journal of obstetrics and gynecology.

[5]  Abdulhakim Coskun,et al.  Quantitative Grading Using Grey Relational Analysis on Ultrasonographic Images of a Fatty Liver , 2012, Journal of Medical Systems.

[6]  W. Barth,et al.  Complications of Third‐Trimester Amniocentesis Using Continuous Ultrasound Guidance , 2002, Obstetrics and gynecology.

[7]  Ivan Amat-Roldan,et al.  Correlation Between a Semiautomated Method Based on Ultrasound Texture Analysis and Standard Ultrasound Diagnosis Using White Matter Damage in Preterm Neonates as a Model , 2011, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[8]  E. Gratacós,et al.  Gestational Age-Specific Cutoff Levels of TDx-FLM II for the Prediction of Neonatal Respiratory Distress Syndrome , 2009, Fetal Diagnosis and Therapy.

[9]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[10]  G. Bastert,et al.  Diagnosis of fetal lung maturity by ultrasound: a new method and first results , 1991, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

[11]  Mario Ziliantiá,et al.  Correlation of Ultrasonic Images of Fetal Intestine With Gestational Age and Fetal Maturity , 1983, Obstetrics and gynecology.

[12]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[13]  P. Bossuyt,et al.  Prediction of fetal lung immaturity using gestational age, patient characteristics and fetal lung maturity tests: a probabilistic approach , 2009, Archives of Gynecology and Obstetrics.

[14]  G. Saade,et al.  Timing of indicated late-preterm and early-term birth. , 2011, Obstetrics and gynecology.

[15]  R. Kryscio,et al.  Echogenicity of fetal lung: relation to fetal age and maturity. , 1985, AJR. American journal of roentgenology.

[16]  A. Gronowski,et al.  Fetal lung maturity. , 2006, Clinical biochemistry.

[17]  J. Thijssen,et al.  Variability of quantitative echographic parameters of the liver: intra- and interindividual spread, temporal- and age-related effects. , 1991, Ultrasound in medicine & biology.

[18]  C. Cetrulo,et al.  Fetal lung to liver reflectivity ratio and lung maturity , 1987, Journal of clinical ultrasound : JCU.

[19]  L. Platt,et al.  Use of ultrasound to predict fetal lung maturity in 247 consecutive elective cesarean deliveries. , 1984, Journal of reproductive medicine.

[20]  Ruey-Feng Chang,et al.  Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks. , 2002, Ultrasound in medicine & biology.

[21]  Ivan Amat-Roldan,et al.  Feasibility and Reproducibility of Fetal Lung Texture Analysis by Automatic Quantitative Ultrasound Analysis and Correlation with Gestational Age , 2012, Fetal Diagnosis and Therapy.

[22]  F. Manning,et al.  The correlation of ultrasonic placental grading and fetal pulmonary maturation in five hundred sixty-three pregnancies. , 1982, American Journal of Obstetrics and Gynecology.

[23]  Jing Du,et al.  Evaluation of breast lesions by contrast enhanced ultrasound: qualitative and quantitative analysis. , 2012, European journal of radiology.

[24]  K. Maeda,et al.  Echogenicity of fetal lung and liver quantified by the grey-level histogram width. , 1999, Ultrasound in medicine & biology.

[25]  A. G. Ramakrishnan,et al.  Fetal lung maturity analysis using ultrasound image features , 2002, IEEE Transactions on Information Technology in Biomedicine.

[26]  K. Maeda,et al.  Noninvasive fetal lung maturity prediction based on ultrasonic gray level histogram width. , 2010, Ultrasound in medicine & biology.

[27]  R L Berkowitz,et al.  The ultrasonic changes in the maturing placenta and their relation to fetal pulmonic maturity. , 1979, American journal of obstetrics and gynecology.

[28]  F. Cendes,et al.  Texture analysis of medical images. , 2004, Clinical radiology.