Abstract #2407
Normative volumetry growth models for the fetus, placenta and amniotic fluid for 3D 3T T2w fetal MRI during 16 – 40 weeks GA range
Alena U. Uus1,2, Megan Hall3,4, Alexia Egloff Collado5, Carla Avena Zampieri3, Charline Bradshaw3, Maria Deprez6, Jacqueline Matthew1,6, Kathleen Colford3, Joseph V. Hajnal1,7, Mary A. Rutherford3, Jana Hutter1,6,8, and Lisa Story3,5,9
1Early life imaging research department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, 2Biomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, 3Early life imaging research department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 4Department of Women and Children’s Health, King’s College London, London, United Kingdom, 5Department of Women and Children’s Health, King's College London, London, United Kingdom, 6Biomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 7Imaging physics and engineering research department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 8Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany, 9Fetal Medicine Unit, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
Synopsis
Keywords: Fetal, Fetal, fetal MRI, growth charts, segmentation
Motivation: There is a need for normalisation for fetal volumetry studies and lack of normative growth models for placenta, amniotic fluid and whole fetus.
Goal(s): Is is feasible to combine fetal, amniotic fluid and placenta segmentation into a combined pipeline for 3D fetal MRI with normative models?
Approach: We used deep learning segmentation to process 145 normal control MRI datasets and generate growth models for 16 - 40 week GA.
Results: We presented the first combined fetus, placenta and amniotic fluid growth models for motion corrected 3D 3T T2w fetal MRI during the 2nd and 3rd trimesters based on deep learning segmentations from 145 controls.
Impact: These models and segmentation network could be potentially used in other research studies for normalisation of fetal organ volumetry.
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