For several years, the dynamics of cerebrospinal fluid (CSF) in the subarachnoid and perivascular space (SAS and PVS) have been a topic of controversy. Both the SAS and PVS are part of the glymphatic system, a network of CSF-filled regions crucial to waste disposal in the brain. The CSF in this system transports the waste, which is why fluid dynamics are a point of interest when trying to promote brain clearance and keep neurodegeneration at bay. The reason why CSF-dynamics remain unclear, originates in the difficulty to image and visualize them with adequate blood suppression and resolution to ensure that the motion observed is not coming from slow blood flow. For this purpose, a high resolution, CSF-specific magnetic resonance imaging sequence (CSF-STREAM) has been developed, for which a DTI-like metric called CSF-mobility has been derived to quantify fluid dynamics. CSF-mobility is a metric describing the amount of movement that CSF undergoes within a voxel, as a function of intra-voxel dephasing due to bipolar gradients. The metric is derived from the eigenvalues from the tensor information in each voxel (volumetric / 3D pixel) that describes this dephasing along different axes. The orientation of CSF-mobility can also be retrieved from CSF-STREAM data, but has not been characterized yet in detail. This report analyzes the eigenvector orientations of the CSF-mobility tensor in various CSF f illed spaces that are wrapped aronund blood vessels: the subarachnoid space (SAS) around the middle cerebral artery (MCA) and PVS around arteries in the basal ganglia and centrum semiovale (CSO). In a first experiment, the assessment of local alignment of the SAS and PVS vector field is described. In a second experiment, the first eigenvector (e1) orientation of each voxel within the SAS and PVS is compared to the local vessel orientation. Three metrics, describing the orientation of the principal CSF mobility orientation compared to the vessel orientation, are derived: Daxial, Dradial and Dspiral. For each parameter, variations in orientation over the cardiac cycle are analyzed and compared to a random binned signal in order to assess the influence of cardiac pulsatility on each parameter. Results show a clear preference for axial orientations in the SAS, with significant differences when comparing to a negative control ROI(p < 0.001), suggesting a difference in orientation patterns or displacement speeds between ROIs. The PVS ROIs indicate only small variations in orientation values from the negative control, with the basal ganglia ROI showing a significant difference from the negative control (p < 0.05), but not the CSO ROI. For all ROIs, the influence of cardiac pulsatility on the three parameters is significant when comparing to the random binned signal (p < 0.05). Further research on combinations with scalar f ield approaches and secondary and tertiary eigenvectors and values are advised to further assess what could cause certain directional patterns and reveal more underlying information about the CSF-mobility tensor. Also, data acquisition with multiple b-values could better characterize any possible variations in displacement speeds in different CSF-filled regions.