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A Fast Anatomical and Quantitative MRI Fetal Exam at Low Field

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Perinatal, Preterm and Paediatric Image Analysis (PIPPI 2022)

Abstract

Fetal Magnetic Resonance Imaging (Fetal MRI) allows insights into human development before birth, complementing conventional Ultrasound imaging with its high resolution and available numerous contrast options. Significant challenges still exist including geometric distortion caused by maternal bowel gas in echo-planar imaging, and restrictions in bore size limiting access to MRI in the obese and or claustrophobic population. Recent developments of clinical low-field scanners can meet these challenges and thus render fetal MRI more accessible. This study shows anatomical imaging and quantitative T2* mapping on a 0.55T system with an analysis pipeline for both placenta and fetal brain. Results show an expected increased overall T2* compared to higher fields, with values decreasing over gestation as shown at higher field. Future work will be directed towards exploring additional types of relaxometry and the use of the presented techniques in subjects with higher Body Mass Index. Included data and analysis code are publicly available.

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Acknowledgments

The authors thank all the participating families as well as the midwives and radiographers involved in this study. This work was supported by the NIH (Human Placenta Project—grant 1U01HD087202-01), Wellcome Trust Sir Henry Wellcome Fellowship (201374/Z/16/Z and /B), UKRI FLF (MR/T018119/1), Wellcome-EPSRC Center for Medical Engineering, the NIHR Clinical Research Facility (CRF) at Guy’s and St Thomas’. The views expressed are those of the authors and not necessarily those of the NHS or the NIHR.

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Correspondence to Jordina Aviles .

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Aviles, J. et al. (2022). A Fast Anatomical and Quantitative MRI Fetal Exam at Low Field. In: Licandro, R., Melbourne, A., Abaci Turk, E., Macgowan, C., Hutter, J. (eds) Perinatal, Preterm and Paediatric Image Analysis. PIPPI 2022. Lecture Notes in Computer Science, vol 13575. Springer, Cham. https://doi.org/10.1007/978-3-031-17117-8_2

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  • DOI: https://doi.org/10.1007/978-3-031-17117-8_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17116-1

  • Online ISBN: 978-3-031-17117-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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