PhD candidate Radiology
Small vessel disease (SVD) causes 25% of all cerebral strokes and is a major cause of cognitive decline, dementia and functional disability in the elderly. Two important challenges hamper the development of effective treatments. First, little is known about the mechanism by which SVD leads to ischemic brain damage and, thus, to cognitive decline. Second, the current clinical markers and image-based markers of SVD do not reflect SVD itself, but macroscopic brain damage secondary to SVD. Unlike large vessels, small vessels are not visible with current imaging techniques, which leave, thus, a ‘terra incognita’ of small vessel pathology between large vessels on the one hand, and macroscopic brain damage on the other.
The aim of this research is to discover the ‘terra incognita’ by developing innovative magnetic resonance imaging (MRI) techniques that yield non-invasive markers of small vessel (dys)function in the human brain. An example of such a functional marker is the change in blood flow in response to a breathing challenge in which CO2 is administered. There is a PhD-project available, in which you will develop new imaging strategies on an ultra-high-field strength (7 Tesla) MRI scanner. 7 Tesla MRI offers more signal-to-noise than standard clinical MRI scanners, and has also changed contrasts. You will exploit the benefits of 7T MRI to develop new imaging methods (MRI pulse programming and image processing), and test these methods in validation studies in healthy humans. An important part of the project will be the translation of these techniques to patient studies that aim to study the role of SVD in the development of cognitive decline and dementia. This translational work will be done in close collaboration with clinical researchers from the department of Neurology (and the Brain Center Rudolf Magnus).
We are looking for an excellent candidate with an M.Sc. degree in preferably (bio-)physics or applied physics, with a strong interest in magnetic resonance imaging methods. The candidate must have a good scientific background, should be highly motivated and independent, and able to work in an interdisciplinary team of scientists, engineers and medical doctors. Programing experience is required, and knowledge of C/C++ is an advantage.
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