Completed Brain & Nervous System Lungs & Breathing

Sir Peter Mansfield Imaging Centre

In plain English

AI plain-English summary

Nottingham is building a world-leading medical imaging centre, the Sir Peter Mansfield Imaging Centre (SPMIC), by upgrading its existing MRI scanners and adding new technologies to study the whole body, not just the brain. This matters because current MRI scanners are too narrow for many patients—obese individuals cannot fit inside, and people exercising cannot be scanned. The centre will install a wide-bore 3T scanner to accommodate larger patients and an exercise bike, and add whole-body capability to its existing 7T ultra-high-field scanner, which dramatically boosts sensitivity. It will also deploy hyperpolarised gases and dynamic nuclear polarisation to study lung disease and metabolism in muscles and brain, and use real-time MEG to stimulate subjects based on their ongoing brain state. For patients with cochlear implants—who cannot undergo MEG or MRI—the centre will purchase fNIRS equipment to monitor brain activation as they adapt. If successful, the centre will transform clinical diagnostics for obesity, lung disease, metabolism, and hearing loss, and share its data and expertise with other UK centres. It will also reduce MRI noise with active noise-cancelling headphones and correct for head motion, improving image quality for patients who struggle to keep still.

View original technical description
Nottingham has considerable expertise and a long track record of success in the development of MRI. It also has strong research programmes in gastroenterology, liver disease, metabolism, sports medicine, orthopaedics, respiratory medicine, mental health, hearing and radiological sciences. This proposal aims to combine these strengths to establish a world-leading centre, the SPMIC, to drive the development and application of medical imaging. A key feature is that the centre will be set up to share our facilities and expertise, as well as the data that we acquire, with other centres. We are requesting funding for a number of items of equipment which will transform our current facilities: 1. We were the first group in the UK to install and develop a 7T MR scanner, which is the highest field MR scanner generally available worldwide. Ultra-high field MR considerably increases the sensitivity of MRI and MRS, and our work and that of others has proven the capabilities of 7T MR in the brain. There is now another 7T scanner in Oxford, and we are pleased to note that other UK groups are recognizing the advantages of 7T and are applying for such scanners through this call. We are happy to share the experience gained in pioneering MR studies at 7T. We now need to add whole body capability to our 7T scanner, to exploit the capabilities of 7T outside of the brain. We are ideally placed to do this because of our experience in using MR in experimental studies. 2. We have a long track record of using MR to study nutrition, metabolism and gastrointestinal disorders. However we are currently limited by the fact that many subjects in these studies are too large to fit into a standard MR scanner, limiting the study of obese patients. We also have considerable experience of studying the effects of exercise on the physiology and metabolism of skeletal muscle and the brain. We need to use the non-invasive capabilities of MR in this work, but are hampered by the problems involved in scanning subjects undertaking exercise. We have an exercise bike designed for use inside an MR scanner, but this is difficult to use in a conventional scanner because of the narrow bore. We have therefore requested funding for wide-bore 3T MR. 3. We have developed strong technical expertise relating to two recently-developed methods for increasing the sensitivity of MR: hyperpolarized (HP) inert gases (e.g. xenon and krypton) and dynamic nuclear polarization (DNP). Both of these techniques have the potential to produce a step change in the way MR is used clinically. We will exploit the increased sensitivity of HP inert gases in the study of lung disease and will also undertake completely novel studies that involve using DNP to study metabolism in muscles and in the brain. 4. We have made lots of progress in understanding the brain's function by using electrophysiology techniques (MEG and EEG). We will build on this by installing "real time" capability on our MEG scanner, which will allow us to perform experiments where we stimulate a subject based on their ongoing brain state. 5. As part of our hearing research, we want to study brain activation in patients who have received a cochlear implant, but MEG and MRI cannot be used for these experiments. We will therefore purchase fNIRS equipment to monitor how these patients adapt to their implants. We will site this equipment in a specially-designed room adjacent to our MR scanners, to ensure that the new facilities are as convenient as possible for patients who take part in multi-modal studies. 6. Patients often do not like having MRI scans, and one of the main reasons is acoustic noise. We will use active noise cancellation headphones to reduce the noise levels in our MR scanners. We will also install systems to detect and correct for head motion in MRI; this will greatly improve the quality of images obtained from patients who often find it hard to keep still; invaluable for clinical studies of patient

View the original record at the funder ↗

Researchers

Dorothee Auer (Co-Investigator)Ian Hall (Co-Investigator)Penny Gowland (Co-Investigator)Peter Morris (Principal Investigator)Richard Bowtell (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

EPSRC Capital Award for Core Equipment 2024/25: National facility for Ultra-high Field (11.7T) Human MRI Scanning
Application for Pre-Clinical Imaging Equipment for a Philips 3 Tesla MRI System
ICF State-of-the art preclinical MRI for advanced in vivo imaging
Cardiff University-Equipment Account
MICA: Ultra-High Field MRI: Advancing Clinical Neuroscientific Research in Experimental Medicine

Original classification

Research Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.