Visualizing the CSF flow orientation in perivascular spaces
R.R. Schreuder (TU Delft - Electrical Engineering, Mathematics and Computer Science)
T. Höllt – Mentor (TU Delft - Computer Graphics and Visualisation)
Joana P. Gonçalves – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
The brain and central nervous system handle waste transport differently from the rest of the body. The pathways through which waste in the brain is transported is still a debated topic. The glymphatic system describes a pathway from the perivascular spaces around veins and arteries to the subarachnoid space. This pathway is filled with Cerebrospinal Fluid (CSF) and exploring this fluid and the orientation of the flow relative to the blood vessels is essential to get new insight into the waste transport and related neurological issues.
We analyze this system using a non-invasive diffusion weighted MRI sequencing technique called CSF-STREAM, which generates a DTI-like tensor field called CSF-Mobility, allowing us to track the CSF. The tensor data can be used to analyze the flow of the CSF by applying eigen-decomposition on the tensor matrix. We derive a vector field from the tensors' principal eigenvectors that represents the general flow of CSF.
We introduce a workflow aimed at analysis, comparison and interpretation of the CSF data. It begins by selecting a region that includes a vessel and the surrounding CSF. The vessel is segmented from the region of interest (ROI) and its centerline is extracted to represent the vessel's orientation. The vector field then visualized using a hedgehog plot with a color mapping that indicates the relative orientation, as well as with a streamlines visualization. The streamlines are restricted to the vicinity of the vessel by generating seed points within a spherical radius surrounding the centerline. To make the visualizations easier to interpret, we apply two different transformations on the vector field. A straightening transformation is applied to the vector field by using straightened Curved Planar Reformation (CPR) on the vessel centerline. An additional unfolding transformation is introduced in which the vectors are rotated around the straightened centerline, creating a cross-sectional view of the vector field. We conduct a user study to evaluate the workflow and compare the visualization methods and to to see which methods work best for interpreting the relation between the flow orientation and the vessels. Results show that the workflow and visualizations are indeed suitable techniques and that the straightening of the vector field along the vessel makes it easier to interpret the data, while the unfolding transformation makes the context too complex to understand with limited time and explanation. Overall, the workflow and tool set have the capability to give researchers more insight into the waste transport in the brain.