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Despite their complementary capabilities, these modalities capture fundamentally different physical signals, potentially leading to systematic differences in image\u2010derived phenotypes (IDPs). Here, we evaluate the agreement of IDPs between US and MRI by comparing the volumes of eight brain structures from 90 subjects derived using deep\u2010learning algorithms from majority same\u2010day imaging (days between scans: mean\u2009=\u20091.2, mode\u2009=\u20090 and max\u2009=\u20094). Excellent agreement (intra\u2010class correlation coefficient, ) was observed for the cerebellum, cavum septum pellucidum, thalamus, white matter and deep grey matter volumes, with significant correlations  for most structures, except the ventricular system. Bland\u2013Altman analysis revealed some systematic biases: intracranial and cortical plate volumes were larger on US than MRI, by an average of  and , respectively. Finally, we found the labels of the brainstem and ventricular system were not comparable between the modalities. These findings highlight the necessity of structure\u2010specific adjustments when interpreting fetal brain IPDs across modalities and underscore the complementary roles of US and MRI in advancing fetal neuroimaging.<\/jats:p>","DOI":"10.1002\/hbm.70349","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T10:46:11Z","timestamp":1759315571000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Cross\u2010Modality Comparison of Fetal Brain Phenotypes: Insights From Short\u2010Interval Second\u2010Trimester <scp>MRI<\/scp> and Ultrasound Imaging"],"prefix":"10.1002","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0991-3204","authenticated-orcid":false,"given":"Madeleine K.","family":"Wyburd","sequence":"first","affiliation":[{"name":"Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicola K.","family":"Dinsdale","sequence":"additional","affiliation":[{"name":"Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vanessa","family":"Kyriakopoulou","sequence":"additional","affiliation":[{"name":"Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"},{"name":"Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Venturini","sequence":"additional","affiliation":[{"name":"Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Wright","sequence":"additional","affiliation":[{"name":"Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alena","family":"Uus","sequence":"additional","affiliation":[{"name":"Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"},{"name":"Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacqueline","family":"Matthew","sequence":"additional","affiliation":[{"name":"Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"},{"name":"Fetal Medicine Department GSTT  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily","family":"Skelton","sequence":"additional","affiliation":[{"name":"School of Health and Psychological Sciences City, University of London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6447-9626","authenticated-orcid":false,"given":"Lilla","family":"Z\u00f6llei","sequence":"additional","affiliation":[{"name":"Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital  Boston Massachusetts USA"},{"name":"Harvard Medical School  Charlestown Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Hajnal","sequence":"additional","affiliation":[{"name":"Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"},{"name":"Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana I. L.","family":"Namburete","sequence":"additional","affiliation":[{"name":"Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,10]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Adebayo J. J.Gilmer M.Muelly H. 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