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.
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.
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.
Organisations
- University of Oxford (Lead Research Organisation)
- Human Connectome Project (Collaboration)
- UK Biobank (Collaboration)
- Trinity College Dublin (Collaboration)
- Fraunhofer Society (Project Partner)
- UK Biobank (Project Partner)
- Gold Standard Phantoms (Project Partner)
- European Cooperation in Science and Technology (Project Partner)
Publications
Buck J
(2018)
Sensitivity of Multiphase Pseudocontinuous Arterial Spin Labelling (MP pCASL) Magnetic Resonance Imaging for Measuring Brain and Tumour Blood Flow in Mice.
in Contrast media & molecular imaging
Carone D
(2019)
ICA-based denoising for ASL perfusion imaging.
in NeuroImage
Cherukara MT
(2019)
Model-based Bayesian inference of brain oxygenation using quantitative BOLD.
in NeuroImage
Clement P
(2022)
ASL-BIDS, the brain imaging data structure extension for arterial spin labeling.
in Scientific data
Griffanti L
(2021)
Adapting the UK Biobank Brain Imaging Protocol and Analysis Pipeline for the C-MORE Multi-Organ Study of COVID-19 Survivors.
in Frontiers in neurology
Harms MP
(2018)
Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.
in NeuroImage
Jezzard P
(2018)
Arterial spin labeling for the measurement of cerebral perfusion and angiography.
in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Kirk TF
(2020)
Toblerone: Surface-Based Partial Volume Estimation.
in IEEE transactions on medical imaging
Description | Please see EP/P012361/2 as the continuation of this award at the University of Nottingham |
Exploitation Route | Please see EP/P012361/2 as the continuation of this award at the University of Nottingham |
Sectors | Healthcare Pharmaceuticals and Medical Biotechnology |
Description | Tools developed in this project have been used in population studies, findings of which are now being reported to the general public: https://www.eatthis.com/news-obesity-major-side-effect-study/ https://www.youtube.com/watch?v=J4LzukYExTs Tools developed in this project have been used by pharmaceutical companies to evaluate the efficacy of novel drug treatments by examining their effect on blood flow in the brain, this impact being realised by the use of software tools developed in this project being implemented by specialist imaging clinical trials organisations. |
First Year Of Impact | 2021 |
Sector | Healthcare |
Impact Types | Societal Economic |
Title | Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow |
Description | The simulation data, preprocessed in vivo data, and analysis code used in the NeuroImage article titled 'Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow' (https://doi.org/10.1016/j.neuroimage.2020.117246). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/3986787 |
Title | Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow |
Description | The simulation data, preprocessed in vivo data, and analysis code used in the NeuroImage article titled 'Designing and Comparing Optimized Pseudo-Continuous Arterial Spin Labeling Protocols for Measurement of Cerebral Blood Flow' (https://doi.org/10.1016/j.neuroimage.2020.117246). |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/3986788 |
Description | Human Connectome Project, Developing and Ageing Studies |
Organisation | Human Connectome Project |
Sector | Charity/Non Profit |
PI Contribution | Design and implementation of the Arterial Spin Labelling Perfusion MRI analysis pipeline for the Ageing and Developing Cohort studies. |
Collaborator Contribution | Access to data and expertise. |
Impact | 10.1016/j.neuroimage.2018.09.060 |
Start Year | 2018 |
Description | The Irish Longitudinal Study on Ageing (TILDA) |
Organisation | Trinity College Dublin |
Country | Ireland |
Sector | Academic/University |
PI Contribution | Analysis methods for Arterial Spin Labelling perfusion MRI data collected. |
Collaborator Contribution | Provision of Arterial Spin Labelling perfusion MRI data for evaluation of new analysis methods. |
Impact | 10.1016/j.neurobiolaging.2021.04.008 10.1016/j.neuroimage.2021.117741 |
Start Year | 2017 |
Description | UK Biobank Imaging Study |
Organisation | UK Biobank |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Expert guidance on the acquisition and analysis of Arterial Spin Labelling perfusion MRI within the Imaging Study component of UK Biobank. |
Collaborator Contribution | Access to neuroimaging data. |
Impact | 10.3389/fneur.2021.753284 |
Start Year | 2017 |
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 |
Title | OXASL_OptPCASL |
Description | OXASL_OPTPCASL is a package for generating optimal PLDs for PCASL experiments in order to maximise sensitivity to CBF, ATT or both. |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
Impact | Recently released to the community. |
URL | https://oxasl-optpcasl.readthedocs.io/ |
Title | QuantiCEST (Quantiphyse - CEST widget) |
Description | A tool for the analysis of Chemical Exchange Saturation Transfer MRI data. This provides aces to advanced tools for analysis of CEST data within a graphical environment that is more accessible for users in clinical disciplines and commercial users. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | This tool is currently being evaulated by users working on clinical research applications of CEST MRI. |
URL | https://quantiphyse.readthedocs.io/en/latest/cest.html |
Title | Quantiphyse - ASL Widget |
Description | A tool for the analysis of perfusion and associated haemodynamics from Arterial Spin Labelling MRI. This widget brings ASL analysis functionality to the Quantiphyse physiological image analysis environment, opening access to the methods to a wider audience. |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | Provides a graphical user interface to ASL analysis tools for use in clincally oriented research and applications inlcuding Oncology. |
URL | https://quantiphyse.readthedocs.io/en/latest/asl_overview.html |
Title | Toblerone - Partial Volume Estimation from Surface Reconstructions |
Description | Software implementing methods to convert between volumetric and surface-based medical imaging spaces, including tools for partial volume estimation on a voxel grid from surface representations. |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | This method has been used within the Arterial Spin Labelling perfusion MRI analysis pipeline for the Human Connectome Project Ageing and Development studies. |
URL | https://toblerone.readthedocs.io |
Description | BASIL Course 2020 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Interactive course on the analysis of Arterial Spin Labelling MRI data using the BASIL toolbox, organised and run by the team. |
Year(s) Of Engagement Activity | 2020 |
Description | FSL Course 2021 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Hands-on workshop on the use of Arterial Spin Labelling perfusion MRI using the BASIL toolbox, part of the FMRIB Software Library course. Increased users familiarity with the BASIL toolbox and enabled wider use of ASL in neuroimaging studies. |
Year(s) Of Engagement Activity | 2021 |
Description | MIT in Physiological Image Analysis |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Hands-on sessions on the analysis of Physiological MRI data using the Quantiphyse toolbox, run as part of the International Society of Magnetic Resonance in Imaging annual meeting. Workshop proposed, organised and run by the team. Resulted in increased usage of Quantiphyse in studies using physiological imaging. |
Year(s) Of Engagement Activity | 2021 |