Precision Medicine Doctoral Training Programme

Multimodal MRI methods to quantify blood-brain barrier dysfunction in the ageing brain (iCase)

Project Details - Multimodal MRI methods to quantify blood-brain barrier dysfunction in the ageing brain (iCase)

Supervisor(s): Dr MJ Thrippleton, Prof JM Wardlaw & Prof I Marshall
Centre/Institute:  Centre for Clinical Brain Sciences
Industrial Partner: Siemens

Background

Cognitive impairment and dementia affect over 45 million people worldwide and cost over £26 billion per year in the UK alone.  Currently, there are no disease modifying treatments, and the number of people with the disease is rapidly increasing as our population ages.  A clearer understanding of the pathophysiology is needed to guide the development of effective therapeutics. Vascular dysfunction including blood-brain barrier dysfunction, is an important but poorly understood component of ageing that appears to be accelerated in Vascular, Alzheimer’s and mixed dementias.[1] It includes impaired vasoreactivity (CVR) and interstitial fluid (ISF) drainage. The relative contribution of each to brain injury and symptom development and the sequence of pathology is unknown.

Aims

The project will develop methods to improve detection of subtle BBB leakage through traditional use of intravenous contrast agents (DCE)[2] in parallel with novel approaches such as arterial spin labeling, which can also provide information on regional cerebral blood flow (CBF).  The project will address limitations of DCE methods to detect BBB dysfunction in cerebral small vessel disease ageing stroke and dementia, identified by an international expert working group funded by the MRC JPND and led by Thrippleton. Specifically, the project will address crucial aspects of the acquisition, such as optimal contrast injection rate, the importance of measuring and correcting for RF field inhomogeneity and pre-contrast T1, temporal resolution and the influence of instrumental artifact, some of which were identified in previous work by Thrippleton.[3] Assumptions behind signal processing strategies will be addressed, including the influence of water exchange and the use of population-averaged blood concentration functions versus individual patient measurements. Finally, the project will address the lack of validation by developing alternative methods of assessing permeability, such as relaxation- or diffusion-weighted arterial spin labeling.

Approach and Environment

MRI methods will be developed in collaboration with healthcare technologist Siemens with the intention of incorporating BBB function measurement into rapid multi-contrast scanning to efficiently quantify CBF, CVR, diffusion, relaxation and other vascular and tissue properties for mapping tissue damage and lesion change. Siemens are a major supplier of research MRI equipment in Edinburgh, supported the University’s iCASE application, and are enthusiastic supporters of this project. The interest in integrating complex brain structural and vascular imaging is highly relevant to their ‘Healthineers’ mission to increase efficiency, precision and stratification of common brain disorders including risk of stroke and dementia.

The project benefits from well-resourced clinical studies providing well characterized patient populations in which the techniques can be assessed funded by EU H2020, Fondation LeDucq, UK Dementia Research Institute, Row Fogo Trust, the Stroke Association, CSO, and others. In addition to working on an important problem with cutting edge MRI and clinical research techniques, with access to international expert networks focused on MRI methods to assess brain changes with ageing, small vessel disease, stroke or dementia, the student will join the newly formed UK Dementia Research Institute Centre at the University of Edinburgh, part of a £250 million vibrant local and national research community for dementia research across 6 centers in the UK. Extensive international collaborations with expert centers in Europe, North America and Asia Pacific Region are also provided through EU Horizon 2020, Foundation Leducq and JPND funding.

Training Outcomes

The student will learn novel quantitative MRI acquisition techniques,  scanner operation, Siemens IDEA pulse sequence programming environment, the handling of large data sets, quantitative computational image analysis programming and application (Matlab, SPM, FSL, R statistics) for the brain. They will gain a comprehensive understanding of clinical research including ethical, clinical and practical issues and implications for imaging study design. Partnership with Siemens will provide industrial site visits, placements, access to state-of-the-art MRI technology and collaboration with experienced commercial-sector MRI scientists.

References

  1. Wardlaw JM, Makin S, Valdés Hernández MC, Armitage P, Heye AK, Chappell FM, Muñoz-Maniega S, Sakka E, Shuler K, Dennis MS, Thrippleton MJ. Blood-brain barrier failure as a core mechanism in cerebral small vessel disease and dementia: evidence from a cohort study. Alzheimers Dement 2017;13:634-643
  2. Heye AK, Culling RD, Valdés Hernández MC, Thrippleton MJ, Wardlaw JM. Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review. Neuroimage Clin 2014;6: 262–274.
  3. Heye AK, Thrippleton MJ, Armitage PA, Valdés Hernández MC, Makin SD, Glatz A, Sakka E, Wardlaw JM. Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability. Neuroimage 2016;125:446–455.

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  • The deadline for 18/19 applications is 5pm on Wednesday 10th January 2018.
  • Please note all applications for the Precision Medicine DTP should be submitted to University of Edinburgh, even those applying for a project at the University of Glasgow.
  • Applicants must apply to a specific project, ensure you include details of the project you are applying to in Section 4 of your application. We encourage you to contact the primary supervisor prior to making your application.  
  • As you are applying to a specific project, you are not required to submit a Research Proposal as part of your application. 
  • Please ensure you upload as many of the requested documents as possible at the time of submitting your application.