Controlling structure induced variations in non-invasive perfusion MRI of neurodegeneration
Lead Research Organisation:
University of Nottingham
Department Name: School of Medicine
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.
Publications
Arzanforoosh F
(2021)
Effect of Applying Leakage Correction on rCBV Measurement Derived From DSC-MRI in Enhancing and Nonenhancing Glioma.
in Frontiers in oncology
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
Kirk TF
(2020)
Toblerone: Surface-Based Partial Volume Estimation.
in IEEE transactions on medical imaging
Knight SP
(2021)
Obesity is associated with reduced cerebral blood flow - modified by physical activity.
in Neurobiology of aging
Leidhin CN
(2021)
Age-related normative changes in cerebral perfusion: Data from The Irish Longitudinal Study on Ageing (TILDA).
in NeuroImage
Description | We have expanded our understanding of the consequences of partial volume effects on the measurement of brain blood flow using the non-invasive Arterial Spin Labelling (ASL) MRI technique. This has implications for the use of this technique by researchers, industry and clinicians when conducting studies of the brain, evaluating changes in brain blood flow in response to treatments and interpreting brain blood flow images in disease. We have developed methods to correct for partial volume effects in ASL MRI making these available to the community via software tools and supporting their use through publications, training and secondments. We have addressed various sources of variability on the measurement of brain blood flow between and within individuals when using ASL MRI beyond those caused by partial volume effects, expanding our existing software tools, used by the research community, to make more robust measurements. We have explored the applications of our methods to accurately and repeatably measure blood flow in the brain in applications to clinical trials and in clinical applications and as a result have started a company to explore commercial applications in healthcare. |
Exploitation Route | The methods we have generated and software tools we have produced are already being used by researchers worldwide in studies of human brain function, the effects of disease on the brain and of various treatments for brain diseases. Future use of our methods could improve the use of blood flow imaging for patients and lead to wider adoption of non-invasive ASL MRI in clinical applications. In the near term, measurements of blood flow in the brain may be useful in detecting early signs of dementia and distinguishing between different types of dementia allowing for earlier access for patients to emerging therapies. |
Sectors | Healthcare |
Description | Please see the impact summary of EPSRC grant EP/P012361/1 |
Sector | Healthcare |
Impact Types | Societal |
Description | BBSRC Innovation to Commercialisation of University Research (ICURe) |
Amount | £45,000 (GBP) |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 06/2022 |
End | 02/2023 |
Description | Confidence in Concept |
Amount | £70,000 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2022 |
End | 12/2022 |
Description | Hermes Award |
Amount | £38,500 (GBP) |
Organisation | University of Nottingham |
Sector | Academic/University |
Country | United Kingdom |
Start | 03/2023 |
End | 07/2023 |
Description | ICure Follow-on Funding |
Amount | £300,000 (GBP) |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 11/2023 |
End | 10/2024 |
Description | Impact Acceleration Account: Impact Exploration Grant |
Amount | £11,000 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 11/2021 |
End | 03/2022 |
Description | Precision Imaging Beacon Studentship |
Amount | £45,000 (GBP) |
Organisation | University of Nottingham |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2020 |
End | 08/2024 |
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 | Invicro |
Organisation | Invicro |
Country | United States |
Sector | Private |
PI Contribution | Insight and advice on the use of quantitive algorithms for the analysis of Arterial Spin Labelling MRI in pharmacological trials. |
Collaborator Contribution | Development of their own internal analysis tools using outputs developed by our research, publication of a joint paper on recommendations for the use of ASL MRI in clinical trials. |
Impact | https://doi.org/10.1016/j.drudis.2023.103506 |
Start Year | 2020 |
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 |
Company Name | Quantified Imaging |
Description | Quantified Imaging develops diagnostic tools that aim to use non-invasive MRI in oncology and neurodegeneration diagnoses. |
Year Established | 2023 |
Impact | Development of a software product for the use of Arterial Spin Labelling in clinical trials for dementia (InnovateUK SBRI grant Feb 2024 - Jan 2025). |
Website | https://www.quantified-imaging.com/ |
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 |