Abstract #0713

Continuous 4D atlas of normal fetal lung development and automated CNN-based lung volumetry for motion-corrected fetal body MRI

Alena Uus¹, Irina Grigorescu¹, Aditi Shetty¹, Alexia Egloff Collado², Joseph Davidson^3,4, Milou van Poppel^1,5, Johannes Steinweg², Lisa Story², Michael Aertsen^6,7, Jan Deprest⁸, Jim Carmichael⁹, Joseph V Hajnal^1,2, Mary Rutherford², and Maria Deprez¹

¹Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ³Prenatal Cell and Gene Therapy, Elizabeth Garrett Anderson Institute of Women’s Health, University College London, London, United Kingdom, ⁴Stem Cells and Regenerative Medicine, GOS-UCL Institute of Child Health, London, United Kingdom, ⁵Department of Congenital Heart Disease, Evelina Children’s Hospital, London, United Kingdom, ⁶Department of Radiology, University Hospitals Leuven, Leuven, Belgium, ⁷Department of Imaging and Pathology, Biomedical Sciences, KU Leuven, Leuven, Belgium, ⁸Department of Obstetrics, University Hospitals KU Leuven, Leuven, Belgium, ⁹Paediatric Radiology, Evelina London Children’s Hospital, London, United Kingdom

This work presents a continuous 4D atlas of fetal lung development within 22-32 weeks gestational age (GA) generated from ~130 motion-corrected fetal body MRI datasets. The corresponding growth charts for fetal MRI lung indices are used for definition of the of normal ranges. In addition, we implemented and evaluated an automated method for fetal lung volumetry based on 3D UNet segmentations.

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