Quantifying the Sources of Phase Contrast in High Resolution Magnetic Resonance Imaging of the Human Brain.

Magnetic Resonance Imaging (MRI) is a widely used technique that allows non-invasive imaging of soft tissues in the human body and brain. One of the strengths of MRI is its flexibility in producing images that contain different contrast properties based on differences in the composition of tissues. The research proposed here will attempt to characterise fully the contrast seen in the human brain using one such technique called gradient-echo phase imaging.Phase imaging of the human brain is a relatively new technique for providing information on the properties of tissue. The popularity of this technique has risen with the increased availability of ultra high field MRI scanners which use magnetic field strengths in excess of 3tesla (T). At high field strengths the contrast seen in phase images is amplified to the point where tissue structures that could previously only be seen in histology can now be visualised in vivo. The achievable spatial resolution of phase images measured at 7T is now approaching the 100 micron length-scale yielding important information on tissue structure and composition for researchers in the field neuroscience. Until recently, the contrast seen in phase images was thought to be solely due to differences in the isotropic, volume magnetic susceptibility of tissues, arising from variations in the concentrations of materials like iron and myelin. Over the last two years, the explanation of phase contrast in the human brain has grown in complexity as result of work showing that three new mechanisms could all potentially contribute to phase contrast. These mechanisms are: anisotropic susceptibility, frequency offsets due to long range order in the microstructure of tissue, and offsets due to the exchange of magnetisation between water protons and larger molecules. The goal of the work described in this proposal is to unravel the contribution of each of the different mechanisms to phase images of the human brain and to provide a clear understanding of the origin of each contrast mechanism. The research will primarily focus on post mortem tissue samples that allow more direct measurement of phase information and histology. The information gained from the analysis of these samples will then be applied to human phase images acquired in vivo. Quantification of the different sources of contrast in vivo will provide information about iron and myelin content, and nerve fibre orientation and composition, which could in future be used to improve our understanding and ability to diagnose diseases such as Alzheimer's disease, Parkinson's disease and multiple sclerosis.

As part of the proposed research I would develop optimised techniques for extracting separate layers of contrast information from MRI phase images. These techniques would be of interest to researchers in the field of high resolution gradient echo MRI. Using these methods, the exquisite contrast available in high field phase imaging could be fully explained. Through understanding the contrast seen in phase imaging its possible applications to human imaging can be realised. These techniques, and the information available to researchers using them, will ultimately advance the field of neuroscience and MRI. The skills I learn at the Max Planck institute in Leipzig, added to the experience I gain at the two American institutions, I will bring back with me to Nottingham. I will then integrate these new skills into my work at SPMMRC as soon as possible. I will also ensure that collaboration between these institutions and the SPMMRC is kept frequent. The major long-term impact of this work to society would be on health and quality of life. T2* weighted MRI is currently a widely used clinical imaging technique. The focus at present is on modulus data, due to the simple origins of the contrast seen in these images. The research I have proposed would help to define the exact sources of contrast in phase imaging. This will strengthen the credibility of observations made by researchers and clinicians using this imaging modality, and allow the high contrast to noise seen in these images to be fully exploited. Many neurodegenerative diseases such as multiple sclerosis, Parkinson's, and Alzheimer's are hard to accurately diagnose. The inherently high signal to noise and rich structural information available with phase imaging could aid these diagnoses. The SPMMRC has long standing links with PHILLIPS, with all three of the MRI scanners installed on the site being Phillips machines. The possibility of combining the techniques I develop for processing phase images into a software add-on for Phillips MRI systems will be fully explored. It will be a top priority to explore with Phillips any applications of my research that could be important additions to the tools currently available to the MRI community.