Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/162519
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Burgos Artizzu, Xavier P. | - |
dc.contributor.author | Pérez Moreno, Álvaro | - |
dc.contributor.author | Coronado Gutiérrez, David | - |
dc.contributor.author | Gratacós Solsona, Eduard | - |
dc.contributor.author | Palacio, Montse | - |
dc.date.accessioned | 2020-05-26T21:00:09Z | - |
dc.date.available | 2020-05-26T21:00:09Z | - |
dc.date.issued | 2019-02-13 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | http://hdl.handle.net/2445/162519 | - |
dc.description.abstract | The objective of this study was to evaluate the performance of a new version of quantusFLM®, a software tool for prediction of neonatal respiratory morbidity (NRM) by ultrasound, which incorporates a fully automated fetal lung delineation based on Deep Learning techniques. A set of 790 fetal lung ultrasound images obtained at 24 + 0-38 + 6 weeks' gestation was evaluated. Perinatal outcomes and the occurrence of NRM were recorded. quantusFLM® version 3.0 was applied to all images to automatically delineate the fetal lung and predict NRM risk. The test was compared with the same technology but using a manual delineation of the fetal lung, and with a scenario where only gestational age was available. The software predicted NRM with a sensitivity, specificity, and positive and negative predictive value of 71.0%, 94.7%, 67.9%, and 95.4%, respectively, with an accuracy of 91.5%. The accuracy for predicting NRM obtained with the same texture analysis but using a manual delineation of the lung was 90.3%, and using only gestational age was 75.6%. To sum up, automated and non-invasive software predicted NRM with a performance similar to that reported for tests based on amniotic fluid analysis and much greater than that of gestational age alone. | - |
dc.format.extent | 7 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Nature Publishing Group | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1038/s41598-019-38576-w | - |
dc.relation.ispartof | Scientific Reports, 2019, vol. 9, p. 1950 | - |
dc.relation.uri | https://doi.org/10.1038/s41598-019-38576-w | - |
dc.rights | cc-by (c) Burgos-Artizzu, Xavier P. et al., 2019 | - |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es | - |
dc.source | Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques) | - |
dc.subject.classification | Malalties del pulmó | - |
dc.subject.classification | Pulmó | - |
dc.subject.classification | Fetus | - |
dc.subject.other | Pulmonary diseases | - |
dc.subject.other | Lung | - |
dc.subject.other | Fetus | - |
dc.title | Evaluation of an improved tool for non-invasive prediction of neonatal respiratory morbidity based on fully automated fetal lung ultrasound analysis | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 696846 | - |
dc.date.updated | 2020-05-26T21:00:09Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.pmid | 30760806 | - |
Appears in Collections: | Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) Articles publicats en revistes (BCNatal Fetal Medicine Research Center) Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
696846.pdf | 1.17 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License