{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T05:56:42Z","timestamp":1792303002161,"version":"4.4.0"},"reference-count":56,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ultrasound in Obstet &amp;amp; Gyne"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To quantify fetal brain maturation in fetuses with early\u2010onset fetal growth restriction (FGR) by estimating gestational age (GA) based on the appearance of gyrification and individual brain structures from three\u2010dimensional (3D) ultrasound volumes using a deep\u2010learning model trained on optimally developing subjects. The association of altered fetal brain maturation, as a potential marker of cumulative intrauterine stress, with an increased risk of neonatal complications was also explored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This was a prospective, observational, single\u2010center cohort study of singleton pregnancies with early\u2010onset FGR conducted at the University Medical Center Utrecht  between June 2022 and June 2024. Early\u2010onset FGR was defined as an estimated fetal weight (EFW) and\/or abdominal circumference\u00a0below the 10\n                      <jats:sup>th<\/jats:sup>\n                      \u2009percentile before 32\u2009weeks' gestation, and brain sparing was defined as an umbilical artery pulsatility index (PI) above the 95\n                      <jats:sup>th<\/jats:sup>\n                      \u2009percentile in combination with a middle cerebral artery PI below the 5\n                      <jats:sup>th<\/jats:sup>\n                      \u2009percentile or a cerebroplacental ratio (CPR) &lt;\u20091. Fetal brain maturation was determined using a deep\u2010learning model, which was trained on data from an optimally developing cohort at GAs of between 18\u2009+\u20090 and 28\u2009+\u20096\u2009weeks, collected by the INTERGROWTH\u201021\n                      <jats:sup>st<\/jats:sup>\n                      Consortium. Therefore, only fetuses with a GA of &lt;\u200929.0\u2009weeks at the time of the scan were included in the analysis. Estimation of brain maturation was based on the size and shape of the Sylvian fissure (SF), parieto\u2010occipital fissure (POF) and calcarine sulcus (CLC), cerebellum (CB) and the combination of all fissures using the whole\u2010brain ultrasound scan. The mean difference between estimated GA and actual GA (\u0394GA) in days was calculated. In a subgroup analysis, \u0394GA for brain\u2010sparing FGR was compared with \u0394GA for non\u2010brain\u2010sparing FGR. Regression analysis was performed to examine the relationship between brain maturation data and potential covariates.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The study included 43 growth\u2010restricted fetuses with high\u2010quality 3D ultrasound scans (13 of which had brain\u2010sparing FGR) at a median GA of 27.1 (interquartile range (IQR), 26.1\u201327.7)\u2009weeks. The estimated GA was significantly lower than the actual GA in early\u2010onset FGR, with \u0394GA of \u20134.6 (IQR, \u20139.8 to \u20131.0)\u2009days based on the whole scan, \u0394GA of \u20134.9 (IQR, \u20139.0 to \u20131.2)\u2009days based on the SF, \u0394GA of \u20135.4 (IQR, \u20137.4 to \u20131.7)\u2009days based on the POF and CLC, and \u0394GA of \u20133.2 (IQR, \u20136.8 to 0.3)\u2009days based on the CB (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090001 for all). There was no significant difference in brain maturation between fetuses with brain\u2010sparing and those with non\u2010brain\u2010sparing FGR or between male and female fetuses. The EFW percentile correlated significantly with the degree of delayed maturation (whole\u2010scan data,\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u20090.377;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.013) and contributed to our multivariable model. Socioeconomic status, fetal sex and CPR were not associated with the delay in maturation. Seventeen neonates were born &lt;\u200932.0\u2009weeks' gestation and admitted to the neonatal intensive care unit. The \u0394GA was higher in the neonates with perinatal complications, indicating greater delay in brain maturation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Delayed fetal brain maturation in early\u2010onset FGR has been demonstrated using a 3D ultrasound deep\u2010learning model. These findings highlight the potential role of 3D ultrasound in the assessment of fetal brain maturation and support the need for continued research into these findings and their long\u2010term neurodevelopmental consequences in early\u2010onset FGR. \u00a9 2026 The Author(s).\n                      <jats:italic>Ultrasound in Obstetrics &amp; Gynecology<\/jats:italic>\n                      published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/uog.70168","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T17:05:33Z","timestamp":1769187933000},"page":"341-349","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep learning assessment of fetal brain maturation on 3D ultrasound volumes in early\u2010onset fetal growth restriction"],"prefix":"10.1002","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5914-4186","authenticated-orcid":false,"given":"L.","family":"Meijerink","sequence":"first","affiliation":[{"name":"Department of Obstetrics, Division Woman &amp; Baby, University Medical Center Utrecht Utrecht University  Utrecht The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Wyburd","sequence":"additional","affiliation":[{"name":"Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A. 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