ISMRM25 - Fetal Brain Imaging

ISMRM & ISMRT Annual Meeting & Exhibition • 10-15 May 2025 • Honolulu, Hawai'i

ISMRM & ISMRT 2025 Annual Meeting & Exhibition

Digital Poster

Fetal Brain Imaging

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Fetal Brain Imaging

Digital Poster

Pediatrics

Wednesday, 14 May 2025

Exhibition Hall

14:30 - 15:30

Session Number: D-185

No CME/CE Credit

		Computer Number: 129 3785. Towards automated fetal brain biometry reporting for 3D T2w 0.55-3T MRI at 19-40 weeks gestational age range View Presentation Video A. Luis, A. Uus, J. Matthew, S. Arulkumaran, A. Egloff Collado, V. Kyriakopoulou, S. Neves Silva, J. Aviles Verdera, M. Hall, S. McElroy, K. Colford, J. Hajnal, J. Hutter, L. Story, M. Rutherford King's College London, London, United Kingdom Impact: The benefits of automating the time-consuming manual biometry method include improved diagnostic accuracy, confidence and reliability of derived measurements, enabling precise quantification of fetal brain development, as well as improved workflow efficiency and turnaround time for radiology reports.
		Computer Number: 130 3786. Pre- and Post-operative Regional Fetal Brain Growth in Fetuses with Spina Bifida Aperta View Presentation Video K. Payette, R. Kottke, P. Grehten, L. Mazzone, M. Meuli, B. Latal, N. Ochsenbein-Kölble, B. Padden, U. Moehrlen, A. Jakab University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland Impact: Longitudinal fetal brain MRI of spina bifida patients has the potential to expand our knowledge of fetal brain development in neural tube disorders.
		Computer Number: 131 3787. Super-resolution Reconstruction of Fetal Brain MRI Through Learning of Multi-view Interpolation Weights View Presentation Video S. Huang, K. Zhang, Z. Lian, G. Chen, D. Shen School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China Impact: Our end-to-end fetal brain super-resolution approach bypasses traditional two-step iterative optimization paradigm, and substantially reduces reconstruction time. It eliminates the need for slice-to-volume registration, and shifts the focus of implicit neural representation from addressing appearance estimation issues to motion estimation.
		Computer Number: 132 3788. FetalSFUDA: Source-Free Unsupervised Domain Adaptation for Fetal Brain Extraction from Different Centers or MRI Sequences View Presentation Video Y. Li, M. Liu, J. Zhu, H. Yang, J. Zheng, Z. Li, Y. Liao, H. Qu, Q. Tian Beihang University, Beijing, China Impact: Source-free unsupervised domain adaptation addresses the problem that the pre-trained fetal brain extraction model is inaccurate for data acquired with different scanning hardware and parameters. Moreover, our work supports cross-center fetal studies and promotes practical clinical diagnostic applications.
		Computer Number: 133 3789. From Fetal to Neonatal: Divergent Trajectories of Human Brain Iron Development Across Regions Revealed by Whole-Brain R2* Assessment View Presentation Video L. Ji, B. Chen, I. Menu, C. Trentacosta, M. Thomason New York University School of Medicine, New York, United States Impact: These findings provide the first insights into R2* development across birth longitudinally, laying the foundation for future research into the neural mechanisms underlying iron deficiency-related developmental disturbances.
		Computer Number: 134 3790. FreeHemoSeg: Label-Free Deep Learning Framework for Automated Segmentation of Fetal Brain Germinal Matrix and Intraventricular Hemorrhage View Presentation Video M. Liu, Y. Liao, J. Zhu, H. Li, H. Yang, J. Zheng, Z. Li, Z. Li, H. Qu, Q. Tian Tsinghua University, Beijing, China Impact: FreeHemoSeg provides accurate, automated segmentation and diagnosis of GMH-IVH without hemorrhage data and labels for training, substantially simplifying clinical workflows, aiding early diagnosis and prognosis, enabling hemorrhage volume measurement, supporting large-scale neuroscience research, and enhancing prenatal care and management strategies.
		Computer Number: 135 3791. A Comprehensive Cortical Analysis for Fetal Growth Restriction using High-resolution MRI View Presentation Video S. Huang, L. Kong, S. Bai, Z. Lian, Q. Xu, G. Chen, M. Zhao, D. Shen School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China Impact: This study analyzes fetal growth restriction (FGR) impacts on cortical development, identifying altered brain regions like the insula, cuneus, and rostral anterior cingulate, affecting sensory integration, cognition, and emotional regulation, and also highlighting areas of both vulnerability and resilience.
		Computer Number: 136 3792. CortexKAN: Multi-input KAN for fetal cortical surface reconstruction View Presentation Video H. Li, M. Liu, Y. Liao, J. Zhu, J. Zheng, H. Yang, Z. Li, H. Qu, Q. Tian Tsinghua University, Beijing, China Impact: CortexKAN model achieves superior performance in fetal cortical surface reconstruction, outperforming existing methods. Additionally, a training strategy without cortical labels was demonstrated effective, enabling accurate reconstruction when surface labels are unavailable.
		Computer Number: 137 3793. Spatiotemporal Patterning of Cortical Microstructure During Gestation View Presentation Video S. Ahmad, P-T Yap The University of North Carolina at Chapel Hill, Chapel Hill, United States Impact: In-utero characterization of cortical microstructure offers key insights into the development of brain connections and functions, aiding early detection of abnormalities linked to malformation and dysfunction.
		Computer Number: 138 3794. Spatio-Temporal Ganglionic Eminence MRI Atlas View Presentation Video T. Ciceri, A. Righini, L. Squarcina, A. Ferro, F. Arrigoni, C. Parazzini, N. Persico, S. Boito, I. Cetin, G. Conte, F. Triulzi, A. Bertoldo, P. Brambilla, D. Peruzzo IRCCS Eugenio Medea, Bosisio Parini (LC), Italy Impact: The spatio-temporal fetal MRI atlas of the GE allows researchers to study potential future clinical conditions attributable to GE alterations in pregnancy. The GE reached its maximum expansion at 21 weeks, followed by a pronounced reduction throughout the pregnancy.
		Computer Number: 139 3795. Optimisation and Validation of Fetal Brain T1 Mapping under Breath-Hold at 1.5T: Utilising Look-Locker and MOLLI Methods View Presentation Video M. Lowe, K. Colford, K. Clair, C. Fauni, W. Norman, J-D Tournier, A. Price Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom Impact: Performing T1 mapping on a cohort of fetal participants will allow a more comprehensive dataset to be collected, enabling T1 contrast to be better optimised in fetal imaging and expanding on the T1 characterisation available in the literature.
		Computer Number: 140 3796. Brain volumetry and T2* relaxometry in fetuses with Congenital Diaphragmatic Hernia View Presentation Video C. Bradshaw, J. Aviles Verdera, M. Rutherford, M. Hall, A. Uus, A. Arechvo, M. Moser, K. Nicolaides, J. Hutter, L. Story King's College London, London, United Kingdom Impact: This study has demonstrated that alterations in brain development have antenatal antecedents in fetuses with CDH. Further work is required to correlate these findings with longer term neurodevelopmental outcomes to aid prognostication and further management.
		Computer Number: 141 3797. Watch me move: Generalizable Fetal Brain Segmentations for Automatic Fetal Head Motion Tracking throughout an MRI Scan View Presentation Video J. Aviles Verdera, K. Payette, S. Neves Silva, D. Cromb, R. Tomi-Tricot, M. Hall, S. Bansal, K. St Clair, S. Counsell, L. Story, M. Rutherford, J. Hajnal, J. Hutter King's College London, London, United Kingdom Impact: First emerging signatures of human neurological development can be systematically and automatically assessed retro- and prospectively on fetal MRI. Signatures of fetal activity and their correlation to fetal health can offer new opportunities for research and future clinical application.
		Computer Number: 142 3798. Negative Impacts of Germinal Matrix-ventricular Hemorrhage on Fetal Brain Development View Presentation Video H. Li, Y. Liao, J. Zhu, M. Liu, J. Zheng, H. Yang, Z. Li, Z. Li, Q. Tian, H. Qu School of Biomedical Engineering, Tsinghua University, Beijing, China Impact: This study used a large dataset to clarify the negative consequence of GMH-IVH on prenatal and postnatal brain development, which can lead to improved diagnosis, management strategies, and potentially better outcomes for affected fetuses and infants.
		Computer Number: 143 3799. CONDITIONAL DEEP GENERATIVE NORMATIVE MODELING FOR STRUCTURAL AND DEVELOPMENTAL ANOMALY DETECTION IN THE FETAL BRAIN View Presentation Video S. You, C. S. Amador Izaguirre, G. T. Milo, S. Jeong, H. J. Yun, P. E. Grant, K. Im Boston Children's Hospital, Harvard Medical School, Boston, United States Impact: The proposed anomaly detection framework offers a new tool for clinicians to identify fetal brain anomalies with high accuracy, enhancing the precision of prenatal diagnostics. This can lead to earlier and more targeted interventions for neurodevelopmental abnormalities, potentially improving outcomes.

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Fetal & Placental Imaging

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