Magnetic Resonance Spectroscopy (MRS) Method Development

MRS is a unique tool for measuring brain metabolism. It works using the same technology as Magnetic Resonance Imaging (MRI) and is therefore non-invasive and widely available. A range of metabolites may be measured using MRS, including neurotransmitters (glutamate and GABA) as well as molecules directly involved in energy metabolism (lactate and glucose).

However, the accurate detection of low concentration metabolites presents a significant challenge due to overlap with other stronger metabolites, interference from water, artefacts and inherent noise. Therefore, improved methodology for data acquisition, processing and analysis are key areas of development for the lab.

Neurometabolic Profiling

MRI is unparalleled at revealing brain structure, however catching diseases before they cause irreparable damage to brain tissue is crucial for improved treatments and recovery. MRS offers the capability to detect subtle changes in brain metabolism that precede structural changes - providing novel disease biomarkers and mechanistic insight. The lab combines advanced MRS methodology with machine learning to discover novel neurometabolic profiles of healthy and diseased brain tissue.

Functional-MRS (fMRS)

Dynamic MRS measures allow us to examine how brain metabolism adapts during tasks and at rest, known as functional-MRS, providing unique insight into neurotransmitter dynamics and brain energetics. However, these small changes are particularly challenging to detect, and we are therefore developing novel acquisition and analysis approaches to improve the relyability and sensitivity of fMRS.

Open Science

The lab strongly supports the principles of open-science, freely sharing code and data wherever possible. The development of open-standards is a undervalued activity, and we are proud to support and contribute to efforts towards standardised MRS data storage (NIfTI MRS led by Will Clarke) and organisation (BIDS MRS led by Mark Mikkelsen).