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Title: Automatic quantitative MRI texture analysis in small-for-gestational-age fetuses discriminates abnormal neonatal neurobehavior
Author: Sanz Cortés, Magdalena
Ratta, Giuseppe A.
Figueras Retuerta, Francesc
Bonet Carné, Elisenda
Padilla Gomes, Nelly
Arranz Betegón, Ángela
Bargalló Alabart, Núria​
Gratacós Solsona, Eduard
Keywords: Neonatologia
Issue Date: 26-Jul-2013
Publisher: Public Library of Science (PLoS)
Abstract: 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 ,5th centile and as normal if all areas were .5th 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
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It is part of: PLoS One, 2013, vol. 8, num. 7, p. e69595
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ISSN: 1932-6203
Appears in Collections:Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques)
Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)
Articles publicats en revistes (BCNatal Fetal Medicine Research Center)

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