Controlling structure induced variations in non-invasive perfusion MRI of neurodegeneration

Lead Research Organisation: University of Oxford
Department Name: Engineering Science

Abstract

Perfusion imaging allows us to measure the vital role played by delivery of blood to the brain in keeping it supplied with nutrients and removal of waste. Any deviations of the blood supply from normal can be a sign of disease. In particular early and subtle changes in perfusion might mark regions of the brain which are affected by degenerative diseases such as dementia before other imaging signs become obvious.
The technology exists and is increasingly widely available to image perfusion quickly and safely using Magnetic Resonance Imaging. Thus perfusion Magnetic Resonance Imaging could be a valuable tool in the understanding of dementias, as well as the diagnosis and monitoring of patients with dementia. The challenge that remains is making sufficiently specific measurements of subtle changes in blood supply that would be needed to make the technology truly useful for patients. This project addresses that problem in three ways:
> Automated removal of errors associated with imperfect measurement, for example due to motion of the patient.
> Methods to control for differences between patients due to their individual brain structure, allowing blood supply measurements to be compared between individuals or from a patient to a population of similar healthy adults. These methods remove uncertainties introduced by other differences between the brain's of individuals that are not related to perfusion.
> Generation of personalised reference perfusion images for an individual patient against which their measured perfusion can be compared to detect changes specific to that individual.
The methods and tools that are to be generated in this project will enable perfusion Magnetic Resonance Imaging to be used more effectively in the UK-wide effort to understand dementia and in the search for new and effective treatments. Ultimately the work done in this project will enable perfusion Magnetic Resonance Imaging to become a valuable clinical tool that can be used in the diagnosis and monitoring of individual patients with dementia.

Planned Impact

The expected impact of this work is in the area of clinical practice for diagnosis and monitoring of neurodegenerative diseases such as dementias. The ultimate aim being improved patient care in conjunction with improved therapies for these diseases and the resulting reduction in economic costs associated both with treatment and long term care of individuals with dementia. Even before new treatments can be developed and translated into clinical practice, the use of sensitive imaging methods, such as perfusion imaging, offers a way to provide clearer unambiguous diagnosis for patients allowing them to better plan their care and removing the added burden of uncertainty in the face of a debilitating disease.
This project provides enabling technology in the first instance for the use of non-invasive imaging of perfusion to contribute to the study of neurodegenerative diseases, assisting in the evaluation of new treatment methods. By the establishment of perfusion imaging as a valuable tool in understanding dementias it will also be possible to demonstrate the value of the technology for clinical benefit to patients. For example, studies are already demonstrating that perfusion changes occur early in neurodegeneration and can potentially stratify different subtypes of disease.
The project seeks to exploit a substantial new database of perfusion imaging information to build personalised references for brain perfusion taking into account factors such as an individual's age and brain structure. In doing so it seeks to enable non-invasive perfusion imaging to be used as a sensitive marker for changes associated with neurodegenerative disease in an individual patient. Thus this project seeks to provide enabling technology for the wider use of non-invasive perfusion imaging in the clinic, matching the increasing availability of the technique on clinical Magnetic Resonance Imaging devices already in use in hospitals.

Publications

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Title BASIL: Bayesian Inference for Arterial Spin Labeling MRI (v3) 
Description A software toolbox for quantification of cerebral perfusion and haemodynamics from Arterial Spin Labelling MRI of the brain. Currently available as part of the FMRIB Software Library (www.fmrib.ox.ac.uk/fsl). This version represents a major revision providing a range of new methods and features and compatibility with the widest range of data. 
Type Of Technology Software 
Year Produced 2017 
Impact BASIL is one of very few tools for ASL MRI data and is aimed at users in both neuroscience and clinical neurology research. Based on requests of help via the 'FSL list' the current version is now being used in at least 10 groups already, where it is contributing to their data analysis, this will in turn ultimately be evidenced from published work. 
URL http://asl-docs.readthedocs.io/en/latest/basil.html