Fully automatic mapping of cerebral perfusion territories using Magnetic Resonance Imaging

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This projects aims towards the complete development of an accelerated brain perfusion territory mapping method without the need for manually planning the individual acquisitions. Using Arterial Spin Labeling it is possible to perform perfusion imaging without the application of any external contrast material, thereby making this method attractive for recurrent acquisitions as well as for the application in healthy volunteers. Modifications of the method allow for imaging of whole brain perfusion (non-selective), territories supplied by the major arteries (carotid and vertebral arteries) as well as smaller, intracranial arteries. A major disadvantage of selective acquisitions is however the need for a time-consuming planning procedure prior to the acquisition. Naturally, methods to speed up this process are desired. These approaches exist, yet are limited due to the physical principles of MRI, which allow only for obtaining relative rather than quantitative gray values. Therefore, novel algorithms are needed, which are stringent enough to only detect the structures of interest, yet are flexible enough to adapt to individual patients anatomies. This projects aims not only for algorithm optimization, but uses a combined approach to optimize MR sequences to maximize the contrast of the tissues of interest, while the detection methods are improved regarding their reliability. Another major limitation to be dealt with during this project is the longer scan duration of selective Arterial Spin Labeling approaches. Using territorial methods, generally the image acquisition time increases linearly with the number of acquired territories. This increases the overall scan duration unnecessarily and potentially leads to more pronounced motion artifacts during scanning. This is especially critical in mapping the smaller intracranial arteries selectively. Therefore, a method to acquire the individual territories within a single scan without increasing the scan time is furthermore considered in this project. In conclusion, a method to automatically plan the selective perfusion acquisitions in combination with a reduced overall scan time will be the outcome of this project.