Transforming Clinical Brain Imaging to Protect the Neonatal Brain

1) Brief description of the context of the research including potential impact

The first 2 years of life are critical for the development of the neural connections and functions responsible for normal motor and cognitive functioning in humans. Perinatal injury to the developing brain often refers to as birth asphyxia, continues to remain a significant cause of neurodevelopmental disability.

We need objective, non-invasive, hospital and outpatient clinic friendly, easy to operate brain imaging tools to inform early detection of newborn brain injury; to support neurobehavioural interventions in young infants and toddlers, ultimately leading to the best possible brain development.

To answer this need, this PhD will build upon technological advancements in brain imaging and computational techniques; these include (i) magnetic resonance spectroscopy (or MRS) that can quantify bioproducts of metabolism; (ii) optical imaging, with broadband near-infrared spectroscopy (or bNIRS) and diffuse correlation spectroscopy (or DCS); a non-invasive brain imaging instrument that can map cortical oxygenation, haemodynamics, blood flow and metabolic changes from birth; and (iii) machine learning approaches for classification and prediction of newborn brain injury.

The ambition of this project is to innovate neuroimaging and redefine what can be investigated in the developing brain of infants at risk of neurodevelopmental disability.

2) Aims and Objectives

- Optimise a multimodal neuroimaging platform for neuronal functional assessment from the neonatal intensive care unit to the outpatient clinic.
- Translate and enable the use of this platform to map localized cortical responses, in infants from birth up to 5 years old, correlating with a range of abnormalities including seizures and cerebral palsy.
- Implement computational techniques such as machine learning methods for feature extractions and image analytics for classification of brain functional activity (oxygenation/flow and metabolism) and neurodevelopmental outcomes, towards biomarkers of brain health.

3) Novelty of Research Methodology

The project uses a novel combination of imaging modalities (bNIRS, DCS and MRS) combined with machine learning approaches to advance what can be investigated in the brains of neonates with brain injury in terms of real-time brain health as well as neurodevelopmental outcomes. The imaging platform will provide monitoring of blood flow, saturation and metabolism over extended time scales and will use portable equipment that can be brought to the neonatal's bedside rather than requiring moving of the patient (e.g. for an MRI).

4) Alignment to EPSRC's strategies and research areas

This project aligns with and falls under the EPSRC's research themes of "Healthcare technologies" and "Medical imaging"

5) Any companies or collaborators involved

N/A