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Disentangling the interplay between the brain and the cardiovascular system: a population-based quantitative whole-body MRI approach

Subject Area Radiology
Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Clinical Neurology; Neurosurgery and Neuroradiology
Human Cognitive and Systems Neuroscience
Term since 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 515278946
 
The brain plays a central role in the regulation of cardiovascular physiology through the so-called Central Autonomic Network (CAN). In turn, however, it is particularly vulnerable to circulatory disorders and dependents on the integrity of the circulatory system. This interplay is referred to as the brain-cardiovascular-axis. The overarching goal of the project is to analyze and broaden the knowledge of the interplay between the brain and the cardiovascular system. The UK Biobank is a well suited dataset to conduct this research, as high quality MRI scans with advanced diffusion-weighted techniques have been acquired in 45000 prospectively recruited subjects and health-related data including detailed cardiovascular risk factors are available. To detect alterations of the cardiovascular system, morphological changes of the aorta and cerebral white matter lesions will be quantified using artificial intelligence-based methods in a first work package. Diffusion-based MRI techniques will be used to examine the microstructure within the various components of the CAN. In the second work package, these imaging parameters of the cardiovascular system in addition with parameters of cardiac function and atherosclerosis and traditional cardiovascular risk factors will be related to the microstructure of the CAN. Furthermore, the predictive value of CAN features for cardiovascular events will be investigated. In a third work package, these results will be confirmed by means of exploratory analyses of cerebral microstructure. This project will be realized by a multidisciplinary team. It requires close interaction between the working groups to make the best use of existing expertise on cohort studies, epidemiology, advanced microstructure imaging of the brain, central nervous networks, deep learning-based structural segmentation, and MRI data extraction including Radiomics. This project has the potential to provide new metrics for identifying high-risk phenotypes associated with cardiovascular disease. This will provide the basis for several potential follow-on projects to validate these metrics in other cohorts and/or a clinical trial and extend them to other imaging modalities.
DFG Programme Priority Programmes
 
 

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