Level set-based integration of segmentation and computational fluid dynamics for flow correction in phase contrast angiography.

RATIONALE AND OBJECTIVES: A novel method to correct flow data from magnetic resonance phase contrast (MR-PC) angiography, based on combining computational fluid dynamics and segmentation in a level set framework, was developed and tested in this study. MATERIALS AND METHODS: The MR-PC velocity data was used in a partial differential equation-based level set method for vessel segmentation. The results were supplied as the quantitative description of the vessel wall to the flow field solver using computational fluid dynamics, based on the level set method, to obtain a physically meaningful flow. The most significant characteristic of our novel approach is that it requires light computational loads, especially insofar as it avoids generation of complex computational grid system. The integration of segmentation and computational fluid dynamics in a level set framework is shown to be both robust and economic, and yet yields a physically correct velocity field and optimal vessel geometry. RESULTS: The application to the flow field in a straight tube with circular cross section of constant radius demonstrated the validity of out new approach, especially the treatment of the velocity boundary conditions on the solid wall. Simulation of the velocity field in both common carotid artery and bifurcation of basilar and vertebral arteries, based on clinical MR-PC data, provided with smooth and stable results. CONCLUSION: Applying this procedure to both synthetic and clinical data, significant improvement of the blood velocity field, such as a smooth velocity distribution aligned along the vessels and removal of burst or error vectors, could be observed. This procedure also offers possibilities for improved vessel segmentation.