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Quantifying and predicting cognitive impact of cerebral small vessel disease lesions

Quantifying and predicting cognitive impact of cerebral small vessel disease lesions
量化和预测脑小血管疾病病变的认知影响
批准号:
2407568
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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英文摘要
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 cognition2. 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 regions3. Assess the impact of CSVD lesions on the brain structural network as a whole4. Develop a graph deep learning model to predict the possible impact of CSVD on cognitionNovelty of Research MethodologyThis 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 impairmentAlignment to EPSRC's strategies and research areasThis 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
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