Abstract #4972
In-silico modelling of placental T2* MRI: impact of oxygenation and villous architecture
Diana Marta Cruz de Oliveira1, ZhuangJian Yang2, Alys Clark3, Joanna L James4, Avery Pennington5, Dolapo Adebo5, Sam Kersley5, Lisa Story6, Kelly Payette7,8,9, Joseph V Hajnal8,9, Jana Hutter8,9,10, Michele C Darrow5, Gowsihan Poologasundarampillai11, Josephine Naish12,13, Kate Duhig12,13, Alexander EP Heazell12,13, Rebecca J Shipley1, Daniel C Alexander2, and Paddy J Slator14,15
1Mechanical Engineering, University College London, London, United Kingdom, 2Hawkes Institute and Department of Computer Science, University College London, London, United Kingdom, 3Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand, 4Department of Obstetrics, Gynaecology and Reproductive Science, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand, 5Artificial Intelligence & Informatics, The Rosalind Franklin Institute, Harwell Campus, Didcot, United Kingdom, 6Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom, 7Center for MR-Research, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland, 8Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 9Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 10Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany, 11School of Dentistry, University of Birmingham, Birmingham, United Kingdom, 12Maternal and Fetal Health Research Centre, University of Manchester, Manchester, United Kingdom, 13Manchester Academic Health Science Centre, Saint Mary’s Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom, 14Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom, 15School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
Synopsis
Keywords: In Silico, Placenta, T2*, Prenatal, In silico
Motivation: Significant T2* changes appear in dysfunctional placentas, but the drivers remain unclear, underscoring the need for non-invasive tools to distinguish structural and functional factors.
Goal(s): To develop a realistic in-silico simulation pipeline that assesses the impact of villous structure and oxygenation changes on placental T2*.
Approach: We use in-silico placental models with realistic structures, varying oxygen saturation and tissue volumes, to calculate magnetic field shifts and generate voxel-specific T2* maps.
Results: Simulated placental T2*, consistent with in vivo data, show that hypoxia lowers T2*, especially at lower tissue volumes. Similar mean T2* for healthy and FGR vasculatures but FGR shows greater voxel-wise variability.
Impact: The simulation of placental T2* in realistic fetoplacental vasculatures disentangles oxygen/vascular abnormalities and their effects on placental function. By integrating structural and oxygen dynamics, we aim to improve early detection and understanding of placental dysfunction, thereby facilitating treatment.
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