{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T17:40:38Z","timestamp":1773337238299,"version":"3.50.1"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:00:00Z","timestamp":1773273600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Gansu Province Clinical Research Center for Ultrasonography","award":["2020-0411-SFC-0021"],"award-info":[{"award-number":["2020-0411-SFC-0021"]}]},{"name":"The Gansu Provincial Natural Science Foundation","award":["23JRRA1383"],"award-info":[{"award-number":["23JRRA1383"]}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background and aim<\/jats:title>\n                    <jats:p>Deep learning has improved medical image analysis but often produces opaque decisions and correlation-driven predictions that may diverge from clinical reasoning. We hypothesize that a physiology-informed hybrid framework, which explicitly models placenta\u2013pulmonary interactions and integrates multimodal data, could provide interpretable and reliable guidance for assessing fetal lung maturity (FLM) and optimizing antenatal glucocorticoids (GCs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>In a prospective cohort study involving 320 pregnancies\u2014including 160 with hypertensive disorders of pregnancy (HDP)\u2014each with weekly acquisitions from 28 to 36\u202fweeks, we combined 2D\/3D ultrasound, shear-wave elastography, Doppler, and maternal plasma metabolomics. A biophysical placenta\u2013pulmonary coupling model used the umbilical artery pulsatility index (PI) and a metabolomic hypoxia\u2013steroid score to represent placental reserve, while backscatter integrals and elastography were used to characterize fetal lung properties. Constrained by this model, a dual-branch network was developed: (i) a cross-modal attention Transformer with self-supervised contrastive learning to generate unsupervised FLM stages from fused representations and (ii) a spatiotemporal convolution\u2013LSTM network to predict individualized GC dosing and the optimal administration window. A composite loss penalized both projected respiratory distress syndrome (RDS) risk and the biomarker-derived neurotoxicity index.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The cross-modal representations clustered into four distinct maturity stages matching biochemical benchmarks, with an inter-stage silhouette score of 0.72. A downstream classifier achieved 92.3% accuracy in discriminating early from late maturity. The dosing branch predicted the GC dose within \u00b10.5\u202fmg of clinically prescribed regimens and reduced projected RDS risk by 27% compared to standard dosing, while maintaining the biomarker-derived neurotoxicity index below the prespecified threshold.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>A mechanism-guided, multimodal AI framework constrained by placenta\u2013pulmonary physiology transforms imaging features into traceable decision pathways that align with clinical cognition. This interpretable framework may enable non-invasive FLM staging and individualized GC therapy, providing hypothesis-generating decision support that warrants external validation and prospective trials.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1791481","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T06:48:42Z","timestamp":1773298122000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Placenta\u2013pulmonary coupling\u2013guided multimodal AI for fetal lung maturity staging and individualized glucocorticoid therapy"],"prefix":"10.3389","volume":"13","author":[{"given":"Bin","family":"Ma","sequence":"first","affiliation":[{"name":"Ultrasound Medical Center, The Second Hospital of Lanzhou University","place":["Lanzhou, China"]},{"name":"Gansu Province Clinical Research Center for Ultrasonography","place":["Lanzhou, China"]},{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Ran","sequence":"additional","affiliation":[{"name":"Center for Diagnosis and Treatment of Cervical Lesions, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feilei","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhicheng","family":"Yue","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanwu","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongxin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Diagnosis, Gansu Provincial Maternity and Child-care Hospital","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Nie","sequence":"additional","affiliation":[{"name":"Ultrasound Medical Center, The Second Hospital of Lanzhou University","place":["Lanzhou, China"]},{"name":"Gansu Province Clinical Research Center for Ultrasonography","place":["Lanzhou, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,12]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1039","DOI":"10.1001\/jama.2015.10244","article-title":"Trends in care practices, morbidity, and mortality of extremely preterm neonates, 1993-2012","volume":"314","author":"Stoll","year":"2015","journal-title":"JAMA"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"CD004454","DOI":"10.1002\/14651858.CD004454.pub4","article-title":"Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth","volume":"12","author":"McGoldrick","year":"2020","journal-title":"Cochrane Database Syst Rev"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1097\/AOG.0b013e3181924d3b","article-title":"Adverse effects of antenatal glucocorticoids 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