Sara Neves Silva, Alena Uus, Hadi Waheed, Simi Bansal, Kamilah St Clair, Wendy Norman, Jordina Aviles Verdera, Daniel Cromb, Tomas Woodgate, Milou van Poppel, Johannes K Steinweg, Jacqueline Matthew, Kuberan Pushparajah, David Lloyd, Vanessa Kyriakopoulou, Dimitris Siassakos, Anna David, Joseph V Hajnal, Lisa Story, Mary A Rutherford, Jana Hutter
{"title":"基于扫描仪的实时自动容量报告胎儿、羊水、胎盘和脐带在0.55T进行胎儿MRI。","authors":"Sara Neves Silva, Alena Uus, Hadi Waheed, Simi Bansal, Kamilah St Clair, Wendy Norman, Jordina Aviles Verdera, Daniel Cromb, Tomas Woodgate, Milou van Poppel, Johannes K Steinweg, Jacqueline Matthew, Kuberan Pushparajah, David Lloyd, Vanessa Kyriakopoulou, Dimitris Siassakos, Anna David, Joseph V Hajnal, Lisa Story, Mary A Rutherford, Jana Hutter","doi":"10.1002/mrm.70097","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This work aims to enable real-time automated intra-uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner.</p><p><strong>Methods: </strong>A multi-region segmentation nnUNet was trained on 146 images of 73 fetal subjects (coronal and axial orientations) for the parcellation of the fetal head, fetal body, placenta, amniotic fluid, and umbilical cord from whole uterus bSSFP stacks. A reporting tool was then developed to integrate the segmentation outputs into an automated report, providing volumetric measurements, fetal weight estimations, and z-score visualizations. The complete pipeline was subsequently deployed on a 0.55T MRI scanner, enabling real-time inference and fully automated reporting in the duration of the acquisition.</p><p><strong>Results: </strong>The segmentation pipeline was quantitatively and retrospectively evaluated on 36 stacks of 18 fetal subjects and demonstrated sufficient performance for all labels, with high scores ( <math> <semantics><mrow><mo>></mo></mrow> <annotation>$$ > $$</annotation></semantics> </math> 0.98) for the fetus, placenta, and amniotic fluid, and 0.91 for the umbilical cord. The prospective evaluation of the scanner deployment step was successfully performed on 50 cases, with the regional volumetric reports available directly on the scanner.</p><p><strong>Conclusions: </strong>This work demonstrated the feasibility of multi-regional intra-uterine segmentation, fetal weight estimation, and automated reporting in real-time. This study provides a robust baseline solution for the integration of fully automated scanner-based measurements into fetal MRI reports.</p>","PeriodicalId":18065,"journal":{"name":"Magnetic Resonance in Medicine","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T.\",\"authors\":\"Sara Neves Silva, Alena Uus, Hadi Waheed, Simi Bansal, Kamilah St Clair, Wendy Norman, Jordina Aviles Verdera, Daniel Cromb, Tomas Woodgate, Milou van Poppel, Johannes K Steinweg, Jacqueline Matthew, Kuberan Pushparajah, David Lloyd, Vanessa Kyriakopoulou, Dimitris Siassakos, Anna David, Joseph V Hajnal, Lisa Story, Mary A Rutherford, Jana Hutter\",\"doi\":\"10.1002/mrm.70097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>This work aims to enable real-time automated intra-uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner.</p><p><strong>Methods: </strong>A multi-region segmentation nnUNet was trained on 146 images of 73 fetal subjects (coronal and axial orientations) for the parcellation of the fetal head, fetal body, placenta, amniotic fluid, and umbilical cord from whole uterus bSSFP stacks. A reporting tool was then developed to integrate the segmentation outputs into an automated report, providing volumetric measurements, fetal weight estimations, and z-score visualizations. The complete pipeline was subsequently deployed on a 0.55T MRI scanner, enabling real-time inference and fully automated reporting in the duration of the acquisition.</p><p><strong>Results: </strong>The segmentation pipeline was quantitatively and retrospectively evaluated on 36 stacks of 18 fetal subjects and demonstrated sufficient performance for all labels, with high scores ( <math> <semantics><mrow><mo>></mo></mrow> <annotation>$$ > $$</annotation></semantics> </math> 0.98) for the fetus, placenta, and amniotic fluid, and 0.91 for the umbilical cord. The prospective evaluation of the scanner deployment step was successfully performed on 50 cases, with the regional volumetric reports available directly on the scanner.</p><p><strong>Conclusions: </strong>This work demonstrated the feasibility of multi-regional intra-uterine segmentation, fetal weight estimation, and automated reporting in real-time. This study provides a robust baseline solution for the integration of fully automated scanner-based measurements into fetal MRI reports.</p>\",\"PeriodicalId\":18065,\"journal\":{\"name\":\"Magnetic Resonance in Medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Magnetic Resonance in Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/mrm.70097\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Magnetic Resonance in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/mrm.70097","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T.
Purpose: This work aims to enable real-time automated intra-uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner.
Methods: A multi-region segmentation nnUNet was trained on 146 images of 73 fetal subjects (coronal and axial orientations) for the parcellation of the fetal head, fetal body, placenta, amniotic fluid, and umbilical cord from whole uterus bSSFP stacks. A reporting tool was then developed to integrate the segmentation outputs into an automated report, providing volumetric measurements, fetal weight estimations, and z-score visualizations. The complete pipeline was subsequently deployed on a 0.55T MRI scanner, enabling real-time inference and fully automated reporting in the duration of the acquisition.
Results: The segmentation pipeline was quantitatively and retrospectively evaluated on 36 stacks of 18 fetal subjects and demonstrated sufficient performance for all labels, with high scores ( 0.98) for the fetus, placenta, and amniotic fluid, and 0.91 for the umbilical cord. The prospective evaluation of the scanner deployment step was successfully performed on 50 cases, with the regional volumetric reports available directly on the scanner.
Conclusions: This work demonstrated the feasibility of multi-regional intra-uterine segmentation, fetal weight estimation, and automated reporting in real-time. This study provides a robust baseline solution for the integration of fully automated scanner-based measurements into fetal MRI reports.
期刊介绍:
Magnetic Resonance in Medicine (Magn Reson Med) is an international journal devoted to the publication of original investigations concerned with all aspects of the development and use of nuclear magnetic resonance and electron paramagnetic resonance techniques for medical applications. Reports of original investigations in the areas of mathematics, computing, engineering, physics, biophysics, chemistry, biochemistry, and physiology directly relevant to magnetic resonance will be accepted, as well as methodology-oriented clinical studies.