{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T05:36:52Z","timestamp":1792301812196,"version":"4.4.0"},"reference-count":40,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2017,7,22]],"date-time":"2017-07-22T00:00:00Z","timestamp":1500681600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["NHLBI R01 HL116585\u201001"],"award-info":[{"award-number":["NHLBI R01 HL116585\u201001"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To investigate the ability of three\u2010dimensional (3D) MRI placental shape and textural features to predict fetal growth restriction (FGR) and birth weight (BW) for both healthy and FGR fetuses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>We recruited two groups of pregnant volunteers between 18 and 39 weeks of gestation; 46 healthy subjects and 34 FGR. Both groups underwent fetal MR imaging on a 1.5 Tesla GE scanner using an eight\u2010channel receiver coil. We acquired T2\u2010weighted images on either the coronal or the axial plane to obtain MR volumes with a slice thickness of either 4 or 8 mm covering the full placenta. Placental shape features (volume, thickness, elongation) were combined with textural features; first order textural features (mean, variance, kurtosis, and skewness of placental gray levels), as well as, textural features computed on the gray level co\u2010occurrence and run\u2010length matrices characterizing placental homogeneity, symmetry, and coarseness. The features were used in two machine learning frameworks to predict FGR and BW.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The proposed machine\u2010learning based method using shape and textural features identified FGR pregnancies with 86% accuracy, 77% precision and 86% recall. BW estimations were 0.3 \u00b1 13.4% (mean percentage error \u00b1 standard error) for healthy fetuses and \u20102.6 \u00b1 15.9% for FGR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed FGR identification and BW estimation methods using in utero placental shape and textural features computed on 3D MR images demonstrated high accuracy in our healthy and high\u2010risk cohorts. Future studies to assess the evolution of each feature with regard to placental development are currently underway.<\/jats:p>\n                    <jats:p>\n                      <jats:bold>Level of Evidence:<\/jats:bold>\n                      2\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>Technical Efficacy:<\/jats:bold>\n                      Stage 2\n                    <\/jats:p>\n                    <jats:p>J. Magn. Reson. Imaging 2018;47:449\u2013458.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.25806","type":"journal-article","created":{"date-parts":[[2017,7,22]],"date-time":"2017-07-22T05:06:42Z","timestamp":1500700002000},"page":"449-458","source":"Crossref","is-referenced-by-count":51,"title":["In vivo placental MRI shape and textural features predict fetal growth restriction and postnatal outcome"],"prefix":"10.1002","volume":"47","author":[{"given":"Sonia","family":"Dahdouh","sequence":"first","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nickie","family":"Andescavage","sequence":"additional","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"},{"name":"Division of Neonatology Children's National Health System Washington DC USA"},{"name":"Department of Pediatrics George Washington University School of Medicine Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayali","family":"Yewale","sequence":"additional","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexa","family":"Yarish","sequence":"additional","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diane","family":"Lanham","sequence":"additional","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dorothy","family":"Bulas","sequence":"additional","affiliation":[{"name":"Diagnostic Imaging &amp; Radiology Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adre J","family":"du Plessis","sequence":"additional","affiliation":[{"name":"Department of Pediatrics George Washington University School of Medicine Washington DC USA"},{"name":"Fetal &amp; Transitional Medicine Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine","family":"Limperopoulos","sequence":"additional","affiliation":[{"name":"Developing Brain Research Laboratory Children's National Health System Washington DC USA"},{"name":"Department of Pediatrics George Washington University School of Medicine Washington DC USA"},{"name":"Diagnostic Imaging &amp; Radiology Children's National Health System Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2017,7,22]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.thromres.2004.06.038"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajog.2015.08.041"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0301-2115(03)00179-9"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.1806"},{"key":"e_1_2_6_6_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0142788","article-title":"Placental insufficiency in fetuses that slow in growth but are born appropriate for gestational age: a prospective longitudinal study","volume":"11","author":"Bardien N","year":"2016","journal-title":"PLoS One"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.7863\/ultra.15.02058"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.17211"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.11136"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1159\/000324318"},{"key":"e_1_2_6_11_1","first-page":"563","article-title":"Perinatal outcome associated with sonographically detected globular placenta","volume":"51","author":"Fisteag\u2010Kiprono L","year":"2006","journal-title":"J Reprod Med"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.7733"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.2463\/mrms.mp.2015-0051"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.placenta.2010.03.001"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.152.2.6739822"},{"key":"e_1_2_6_16_1","unstructured":"AlliezP JaminC M\u00e9rigotQ et al.Point set processing. 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