A new software tool designed by researchers at The Rosalind Franklin Institute, University of Manchester and collaborators to support decision making in pregnancies at high-risk of stillbirth is to receive a cash injection.
The new grant funded by an Engineering and Physical Sciences Research Council (EPSRC) Health Technologies Connectivity Award will assess the benefit and suitability of the software for use within the NHS.
The researchers hope the software, called SADIE (In Silico Assessment of pregnancy via Digital Integrated Environments) will help doctors tackle the stubbornly high prevalence of stillbirths. Late-term losses are especially hard to foresee, as clinicians continue to lack an accurate means of assessing a baby's oxygen supply before birth.
Around half of stillbirths are associated with fetal growth restriction (FGR), a condition caused by impaired placental function that limits the baby's growth. Current ultrasound tools detect only around half of FGR cases, and even when identified, there is no treatment. Clinicians must instead make complex decisions about the timing of birth, balancing the risks of premature delivery against the danger of waiting too long.
Professor Alex Heazell from The University of Manchester said: "Today's clinical decision-making relies on indirect indicators such as Doppler ultrasound, fetal movements and heart rate patterns. While umbilical artery Doppler has helped reduce stillbirth risk in premature babies, most stillbirths still occur in pregnancies where Doppler results appear normal. Crucially, no existing clinical test can directly assess fetal oxygenation - the primary driver of stillbirth risk."
Dr Michele Darrow from the Rosalind Franklin Institute said: "By integrating computational physics-based modelling, imaging science and physiological insights, the software we have developed is able to generate real-time, actionable information."
The researchers are working with international partners at the University of Auckland to address the gap by rethinking how routinely collected clinical data are interpreted. The Auckland team's work focuses on integrating physiological understanding with advanced physics-based modelling. This approach underpins the development of SADIE, which uses existing ultrasound technology and clinical data to predict fetal oxygen status in under 30 seconds.
Dr Darrow added: "While the proof-of-principle results are promising, further work is needed before SADIE can be tested in large‑scale clinical trials. This new funding aims to ensure the models can run reliably in real time and produce predictions that clinicians can rely on."
Working with clinicians and health system leaders, the team will also assess where SADIE will fit within current NHS care pathways. This step is essential to designing future clinical trials that can demonstrate whether smarter use of ultrasound data can reduce stillbirth while avoiding unnecessary early intervention.
By combining imaging science, computational modelling and clinical insight, this work reflects the researcher's mission to develop transformative technologies that improve human health.
