Quantifying and predicting cognitive impact of cerebral small vessel disease lesions

Brief description of the context of the research including potential impact

Hallmarks of cerebral small vessel disease (CSVD) are white matter neurovascular lesions commonly observed on brain MRI of the ageing population. These markers have been associated with a wide range of cognitive changes including problems with executive function, attention, memory, processing speed and verbal ability. A hypothesis for this wide range of cognitive phenotypes is that size, severity and location of the lesions play an important role in the impact on the white matter tracts. However, little is known about the quantification of the damage to the tracts and how much the lesion locations can be predictive of cognitive decline. It is thus crucial to be able to predict how the pattern of lesion severity and location affects cognitive function.

Being able to predict risks of such cognitive decline from imaging could be applied as inclusion criteria for clinical trials but also be used for improved personalised care. The scope of the project thus starts with the quantification of damage on white matter tracts in age-related CSVD to ultimately develop a method for predicting the impact of CSVD lesions on cognition.

Aims and Objectives

The aim of the project is to develop a method to improve cognitive lesion mapping in CSVD.
The specific objectives are to:

1. Quantify CSVD tissue damage severity on white matter tracts from brain MRI images to later assess the possible impact on cognition
2. Model the local and distant impact of lesions on cognition since lesions represent local tissue damage, but the associated function may depend on the compromised links between brain regions
3. Assess the impact of CSVD lesions on the brain structural network as a whole
4. Develop a graph deep learning model to predict the possible impact of CSVD on cognition

Novelty of Research Methodology

This is a highly challenging topic that will address open research questions related to:

- white matter lesion mapping in CSVD including accounting for different types and severity
- linking image analysis and statistical methods to study the bi-directional association between cognition and CSVD, where cognitive development predicts CSVD, which in turn predicts cognitive impairment
- the local and global impact of small lesions on the brain's structural network and its connectivity
- adaptation of image analysis methods for CSVD
- lesion location patterns and their effect on cognitive function and impairment

Alignment to EPSRC's strategies and research areas

This project lies within the healthcare technology strategy aligning with the grand challenges of 'Optimising Treatment' and 'Transforming Community and Healthcare'. Hereby the essential cross-cutting areas of research are 'Novel computational and mathematical sciences' and 'Novel imaging technologies'.

Any companies or collaborators involved

none

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.