Enhancing MR vascular Fingerprinting with realistic microvascular geometries

Magnetic resonance (MR) vascular Fingerprinting proposes to use the MR Fingerprinting framework to quantitatively and simultaneously map several characteristics that emerge from vascular structure much smaller than voxel size. The initial implementation assessed the local blood oxygenation saturation (SO₂), blood volume fraction (BVf), and vessel averaged radius (R) in humans and rodent brains using simple 2D representations of the vascular network during dictionary generation. In order to improve the results and possibly extend the approach to pathological environments and other biomarkers, we propose in this study to use 3D realistic vascular geometries in the numerical simulations. 28,000 different synthetic voxels containing vascular networks segmented from whole-brain healthy mice microscopy images were created. A Bayesian-based regression model was used for map reconstruction. We show in 8 healthy and 9 tumor-bearing rats that realistic vascular representations yield microvascular estimates in better agreement with the literature than 2D or 3D cylindrical models. Furthermore, tumoral blood oxygenation variations observed with the proposed approach are the only ones correlating with in vivo optic-fiber measurements performed in the same animals.