Prediction of Adverse Outcome Using Fetal MRI in Pregnancies at Risk of Preterm Birth

Plain-language summary

1.4% of babies have a very premature birth (PTB) (less than 32 weeks of pregnancy). This can result in severe life-long complications including cerebral palsy, learning and behavioural difficulties and breathing problems. This has significant cost implications for the NHS, education services and immeasurable human costs for the child and their family. Early delivery may result from maternal infection or poor attachment of the placenta to the womb, which may also cause abnormal brain and lung development. Even where obvious signs of infection are not present in the mother, subtle infection is often present in the baby. Currently there is no test routinely used to see if there is an infection of the baby inside the womb, and it is unknown how the placenta develops in babies that subsequently deliver preterm. Using MRI, the investigators will assess the baby's thymus and placenta for signs of infection and assess how the lungs and brain are developing whilst still in the womb. Machine learning techniques, where computers analyze all the results together, will then be used to see if these scans can identify babies that do poorly after birth. 137 pregnant women at high risk of PTB (between 16-32 weeks of pregnancy) and 183 women with uncomplicated pregnancies will be invited to participate. Women will have an MRI scan of the fetus assessing the lung, brain, thymus and placenta. Where high risk women do not deliver, repeat imaging will be offered every two weeks (maximum 3). After birth the investigators will see if infection was present by analysing the placenta under a microscope, and see how the baby does. All the information from scans and after birth will be put into a computer, to predict which babies do poorly after birth. Health records of the child will be accessed up to two years of age.

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