Effects of realistic vascular networks anisotropy on MR microvascular imaging

Background: MRI microvasculature imaging is a powerful tool for characterizing hemodynamic properties in vivo. Different approaches have been proposed for measuring vascular properties such as cerebral blood volume fraction (CBV), vessel size index (VSI), vessel density as well as vessel architecture, though all have used analytical expressions for modeling the imprint of the vasculature on the MR signal. To reduce the complexity of modeling, it was generally assumed that the vessels are straight cylinders isotropically distributed in space. However, the cerebral vasculature is highly structured and its complex architecture generally departs from an isotropic distribution. Here, we explore the impact of the structural complexity of the vasculature, summarized in terms of anisotropy, on CBV and VSI estimations using numerical simulations in conjunction with a realistic vascular network of a mouse brain.