Vessel distance mapping: Quantification of subcortical arterial and venous vascular patterns to study their interdependency

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The integrity and function of the brain rely on the supply and draining of blood through the arterial and venous vasculature, respectively. Subcortical structures, involved in motor, sensory, cognitive and behavioral tasks, are perfused by the major cerebral arteries. The perfusion territories of these large arteries are spatially variable between subjects. This variability influences the organization of small, perforating arteries. We hypothesize that this variability in subcortical perfusion territories is propagated from the arterial side through the capillary bed into the organization of subcortical veins. Thus, we suspect that subcortical arterial and venous vasculatures are interdependent and that distinct vessel patterns exist. Therefore, if the trajectory of an individual, subcortical vessel is altered, this could induce changes within its surrounding arterial and venous network to maintain a specific pattern of local vessel-vessel-distances. To our best knowledge, this hypothesized interdependency of the arterial-venous patterns has not been studied comprehensively to date. To validate non-invasively this hypothesis in living humans, the following objectives have been identified:(1) Use ultra-high field MRI and prospective motion correction to achieve the required high resolutions (voxel size < 0.4mm) to depict the perforating arteries and veins(2) Segment the vasculature using a vesselness filter and apply distance transform to compute vascular distance maps(3) Find common, subcortical arterial-venous patterns using unsupervised clustering(4) Validate each processing step thoroughly by expertsBy addressing these objectives, a novel, fully automatic technique to analyze vascular distance patterns will be established. Further, proving the interdependency of the arterial and venous vasculature could have an impact on small vessel imaging, diagnose, and treatment in general, as an interdependency might render a joint assessment more promising that focusing on a single side of the vasculature. As the vascular component of neurodegenerative diseases and aging could induce specific vessel-vessel-pattern progressions, the proposed approach could be used as a new biomarker in future, longitudinal studies.