Computational hemodynamics in intracranial vessels reconstructed from biplane angiograms

Recent works in neurology have explored ways to obtain a better understanding of blood flow circulation in the brain with the ultimate goal of improving the treatment of cerebrovascular diseases, such as strokes, stenosis, and aneurysms. In this paper, we propose a framework to reconstruct three-dimensional (3D) models of intracerebral vessels from biplane angiograms. The reconstructed vessel geometries are then used to perform simulations of computational fluid dynamic (CFD). A key component of our framework is to perform such a reconstruction by incorporating user interaction to identify the centerline of the vessels in each view. Then the vessel profile is estimated automatically at each point along the centerlines, and an optimization procedure refines the 3D model using epipolar constraints and back-projection in the original angiograms. Finally, the 3D model of the vessels is then used as the domain where the wall shear stress (WSS), and velocity vectors are estimated from a blood flow model that follows Navier-Stokes equations as an incompressible Newtonian fluid. Visualization of hemodynamic parameters are illustrated on two stroke patients.