Fetal vascular ultrasound assessment to identify growth restriction and reduce stillbirth

Aim of the PhD Project:

Develop a methodology which will enable fetal aortic elastic properties to be calculated from an ultrasound scan;
Develop new ultrasound protocols and signal and image processing techniques for both current clinical imaging systems and state-of-the-art ultrasound imaging;
Investigate whether aortic elasticity measured by this methodology differentiates growth-restricted from normal fetuses.

Project description:

There are over 3,000 stillbirths per year in the UK, many of which are associated with fetal growth restriction (FGR). Stillbirth affects about 1 in 200 pregnancies and is the leading cause of perinatal death. In 2016, the Lancet's "Ending Preventable Stillbirth Series" indicated that stillbirth rates in England and Wales are the highest in Western Europe and have changed little in the past 20 years.1,2 A recent UK study identified FGR, defined as a customised birthweight below the 10th percentile, as the single largest contributor to stillbirth rates, being responsible for about 43% of stillbirths.3

One of the most promising approaches to reduce stillbirths is early diagnosis of FGR. It has been shown that the high mortality rates of FGR are mainly due to lack of recognition of the condition rather than inability to manage it.4 Preventive strategies mostly focus on altering socio-economic parameters, such as improved access to care, or improving maternal wellbeing prior to pregnancy, such as reduced maternal obesity rates.1 However, these strategies are difficult to implement in the mobile, older and more obese pregnant populations of current Western societies. Therefore, a method to accurately screen for FGR to diagnose it early is required.

The main screening tool for FGR during pregnancy is fetal ultrasound (US) scanning, which can be used to measure fetal biometry (dimensions) from which fetal weight can be estimated, and fetal blood flow from which fetal adaptation to hypoxia can be assessed. However, despite these measurements, the sensitivity in detecting FGR remains <40%.5 Therefore, a more sensitive ultrasonographic marker is needed - compared to the traditional fetal biometry and blood flow Doppler examination - to identify those fetuses in the third-trimester scan who are at risk of FGR in the next few weeks.

Assessment of fetal vasculature is emerging as a novel area of research with potential to provide information about fetal cardiovascular adaptations in response to maternal stimuli at a much earlier stage than can be detected by blood flow Doppler examinations in the uterine, middle cerebral, and umbilical arteries. It is now possible to assess fetal aortic properties using advanced US-based techniques, which may have utility in FGR screening. Data suggest that growth restricted fetuses have increased aortic stiffness,6,7 however to date there is no methodology which can be used in clinical practice to assess vascular elasticity during pregnancy.

In this study, we aim to develop advanced US and pulse wave analysis techniques to estimate fetal vascular properties. This will include investigating the use of raw radio-frequency (RF) US data, as well as state-of-the-art ultrafast US imaging8, providing higher temporal resolution across the full field-of-view. We will assess whether aortic elasticity measured by these new techniques differentiates growth-restricted from normal fetuses. If our development is successful, this will provide a novel way to improve detection of FGR and reduce stillbirth rates. It is hoped that the methodology could be implemented in US scanners through our collaboration with Canon Medical Systems.

Strains on the healthcare system in the UK create an acute need for finding more effective, efficient, safe, and accurate non-invasive imaging solutions for clinical decision-making, both in terms of diagnosis and prognosis, and to reduce unnecessary treatment procedures and associated costs. Medical imaging is currently undergoing a step-change facilitated through the advent of artificial intelligence (AI) techniques, in particular deep learning and statistical machine learning, the development of targeted molecular imaging probes and novel "push-button" imaging techniques. There is also the availability of low-cost imaging solutions, creating unique opportunities to improve sensitivity and specificity of treatment options leading to better patient outcome, improved clinical workflow and healthcare economics. However, a skills gap exists between these disciplines which this CDT is aiming to fill.

Consistent with our vision for the CDT in Smart Medical Imaging to train the next generation of medical imaging scientists, we will engage with the key beneficiaries of the CDT: (1) PhD students & their supervisors; (2) patient groups & their carers; (3) clinicians & healthcare providers; (4) healthcare industries; and (5) the general public. We have identified the following areas of impact resulting from the operation of the CDT.

- Academic Impact: The proposed multidisciplinary training and skills development are designed to lead to an appreciation of clinical translation of technology and generating pathways to impact in the healthcare system. Impact will be measured in terms of our students' generation of knowledge, such as their research outputs, conference presentations, awards, software, patents, as well as successful career destinations to a wide range of sectors; as well as newly stimulated academic collaborations, and the positive effect these will have on their supervisors, their career progression and added value to their research group, and the universities as a whole in attracting new academic talent at all career levels.

- Economic Impact: Our students will have high employability in a wide range of sectors thanks to their broad interdisciplinary training, transferable skills sets and exposure to industry, international labs, and the hospital environment. Healthcare providers (e.g. the NHS) will gain access to new technologies that are more precise and cost-efficient, reducing patient treatment and monitoring costs. Relevant healthcare industries (from major companies to SMEs) will benefit and ultimately profit from collaborative research with high emphasis on clinical translation and validation, and from a unique cohort of newly skilled and multidisciplinary researchers who value and understand the role of industry in developing and applying novel imaging technologies to the entire patient pathway.

- Societal Impact: Patients and their professional carers will be the ultimate beneficiaries of the new imaging technologies created by our students, and by the emerging cohort of graduated medical imaging scientists and engineers who will have a strong emphasis on patient healthcare. This will have significant societal impact in terms of health and quality of life. Clinicians will benefit from new technologies aimed at enabling more robust, accurate, and precise diagnoses, treatment and follow-up monitoring. The general public will benefit from learning about new, cutting-edge medical imaging technology, and new talent will be drawn into STEM(M) professions as a consequence, further filling the current skills gap between healthcare provision and engineering.

We have developed detailed pathways to impact activities, coordinated by a dedicated Impact & Engagement Manager, that include impact training provision, translational activities with clinicians and patient groups, industry cooperation and entrepreneurship training, international collaboration and networks, and engagement with the General Public.