Validation of Blood Flow Simulations in Intracranial Aneurysms Yue Yu Brown University Mid-Project Presentation.

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Presentation transcript:

Validation of Blood Flow Simulations in Intracranial Aneurysms Yue Yu Brown University Mid-Project Presentation

Objective –By comparing the concentration field in patient specific geometry and the MRI images from dye injection, we aim to validates our spectral element simulations for blood flow.

Data for Reconstructing Arterial Geometry *This set of data are static CT images taken from 173 different angles, and they will be used for structural reconstruction Slice set 128 Slice set 28 1.With contrast2.Without contrast3.Subtract 1 from 2

Get signal density information for every voxels by interpolation. Setting appropriate threshold for each 2D slice manually (because the sizes of arteries vary a lot, the threshold might vary slice by slice), then reconstruct the 3D arterial geometry by interpolating between these slices. Segmentation

Mesh generation Meshes are generated in GRIDGEN, 1d->2d->3d.

Concentration field from velocity fields Given the velocity fields u (solved beforehand from Navier Stokes equation in the given geometry), solve the relative concentration field c with the Peclet number Pe=UL/D. The actual Peclet number is about Pe=10000Re. But with that we have to use very small time steps to keep the stability. Pe=Re, t=0.2Cardiac Cycle Pe=Re/10, t=0.2Cardiac Cycle

Dye injection validation: with CT images Computational results: CT results: T=0.22 (sec)‏T=0.72 (sec)‏ T=1.22 (sec)‏T=1.72 (sec)‏ T=0.22 (sec)‏T=0.72 (sec)‏ T=1.22 (sec)‏T=1.72 (sec)‏

Conclusions and future work Conclusion: The concentration field calculated from simulated velocity field looks similar with the angiograms from dye injection. Next step: Quantitatively compare the computational results and the angiograms with 2D-3D image registration technique.