Enhanced neonatal brain development MRI at ultra-high field

MRI is extremely valuable in studying normal and abnormal brain development in neonates. The developing Human Connectome Project (dHCP), led jointly by King's and Imperial, aims to map early life development by acquiring MRI anatomical and functional data from fetuses and neonates. Ongoing analysis of dHCP data is hoped to provide new insights into structural and functional development. However there remain key unknowns relating to the effects of prematurity and perinatal trauma on brain development that existing MRI approaches are unlikely to resolve.

One challenge of imaging neonates, is achieving sufficient spatial resolution to visualise small brain structures, maintaining reasonable acquisition times and acceptable noise levels. The dHCP uses a clinical 3T MRI scanner technology primarily designed for imaging adults combined with bespoke neonatal brain receiver coils and purpose designed patient handling1. However, even the dedicated acquisition protocol providing anatomical resolution of 0.8mm isotropic is still only just able to resolve key structures and for example is not able to differentiate cortical layers.
MR sensitivity increases approximately with field strength. As the associated technical challenges are overcome, UHF-MRI is only recently starting to be applied to clinical and biomedical research. For instance 7T MRI can provide information on focal brain lesions in epileptic subjects and in multiple sclerosis not visible at lower fields2,3; ultra high resolution brain imaging is also revealing astonishing anatomical details particularly with enhanced T2* contrast that makes UHF particularly well suited for studying deep nuclei characterised by high iron content4,5.
The objective of this project is to explore the benefits of UHF-MRI for enhancing the available image data quality for neonatal subjects. This will provide a closer look at the brain during a period of exuberant development, when it is both different from adult brain (with different MRI properties) and is changing fast. We aim to produce a 7T protocol that exceeds the dHCP neonatal protocol in sensitivity and resolution, and use this to explore critical facets of brain development and damage, such as patters of deep grey nuclei damage in hypoxic ischemic injury and subtle vascular changes associated with prematurity6.
Few studies scanned children at 7T, with the youngest subjects we are aware of being 5 years old7.The highest field at which neonates have been scanned is 4.7T8,9.

Since neonatal imaging has never been attempted at 7T our first task will be to demonstrate that safe operation can be assured. To the best of current knowledge there are no known inherent health risks associated with exposure to strong static magnetic fields10.

The key risk that must be addressed for any novel MRI application is subject heating during imaging, quantified by the specific absorption rate (SAR) of radiofrequency energy, intrinsically higher at higher frequencies. Safety can be assured by modelling of RF transmitter coils and comparing with detailed experiments on phantoms - an approach taken for imaging all other populations. It should be noted that there are no inherent additional risks associated with smaller subjects. On the contrary, smaller subjects are less prone to RF heating effects for many RF coil designs11 and their higher surface-to-volume ratios make neonates far less prone to systemic heating from RF fields than adults. Further, RF inhomogeneity effects, problematic for imaging larger fields of view at UHF, will be much less pronounced in neonates.

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.