Standard MRI scans the brain in black and white. This project will develop a technique called PARASHIFT MRI that uses specially designed contrast agents to capture multiple chemical signals at once, effectively turning that black-and-white image into colour. The problem is that current MRI can only detect a single signal at a time, making it impossible to watch how different biological processes—like inflammation and neurodegeneration—interact in a living brain. In Alzheimer’s, stroke, and brain cancer, researchers know these processes are linked, but they cannot see how they influence each other in real time. This technique aims to fill that gap by allowing simultaneous readouts of multiple compounds, even at low concentrations. If successful, the approach could transform how clinicians monitor brain disease and treatment effects. For stroke and brain cancer—the two conditions the researcher will test first—it could reveal when and where inflammation drives damage, enabling more targeted therapies. The same method could later apply to neurodegenerative diseases and mental health conditions, offering a practical tool for tracking disease progression and drug response in living patients.
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The brain is a black-box when it comes to understanding disease. It is full of crucial details that could give untold information on how to treat and manage neurological diseases and disorders, but we lack the tools to effectively read those details. While imaging technologies give us a window to observe certain processes, they are often extremely limited. A good example is magnetic resonance imaging (MRI), which has led to countless breakthroughs in the clinic and is used to diagnose and manage patients every day. It is, however, typically limited to a single channel - essentially, we are looking at the brain in black and white instead of colour. This limitation is particularly true when looking at chemical and biological properties of the brain. There are some techniques that begin to allow imaging of multiple signals (i.e. colours), but they are limited to substances present at very high abundances within the brain. A classic example where this would be relevant is in Alzheimer's disease. There is a well-established relationship between the devastating neurodegeneration observed and brain's natural defence system. This co-occurring condition, neuroinflammation, is linked to the long-term deterioration seen in patients, but we struggle to fully understand how they are connected and how they interplay. Much like the classic chicken and egg conundrum, we are often unsure on which comes first or how that comes to be. If we could simultaneously watch how these different processes work at the same time in a living brain, we would significantly improve our understanding and be able to monitor the effects of treatments and interventions more closely. This scenario is not just limited to Alzheimer's disease, but in almost every neurological disease we can think of. Every neurodegenerative disease, brain tumours, stroke, and even mental health issues would all benefit from an improved understanding of the real-time interplay of various biological systems all working - or, more importantly, failing to work - together. I have developed a technique that greatly expands the range and sensitivity of multi-signal MRI by using carefully designed contrast agents in a process called PARASHIFT MRI. This approach allows much lower levels of compounds to be detected in the living brain with multiple readouts available. We have previously demonstrated its approach in the body, and I now aim to focus on applying the technique to study markers of brain disease in much more detail than we are currently able. This pioneering MRI technique will be supplemented by complementary cutting-edge techniques, such as mass spectrometry imaging, to further understand the brain in unprecedented depth. I will focus on stroke and brain cancer as exemplar model systems in the initial stage of my fellowship as they represent clinically vital examples of both acute and chronic inflammation, respectively. Beyond, the findings from my work will have key applications in neurodegenerative disease and across a broad spectrum of neurological disorders. By combining these new tools for comprehensively detecting, characterising, and monitoring brain disease markers, my approach will reimagine how we look at the diseased brain and retrieve untold levels of information to help us tackle this pressing societal burden.
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