Objective: To evaluate if knowledge of patient-specific inflow data in computational fluid dynamics simulations is required for the accurate calculation of intra-aneurysmal flow patterns and wall shear stress in an aneurysm of the anterior communicating artery (AcomA). Materials and methods: 3D digital subtraction angiography (3D-DSA) and phase contrast magnetic resonance (pcMRI) images were obtained in a 71-year old patient with an unruptured aneurysm of the anterior communicating artery (AcomA). A baseline computational flow dynamics simulation was performed using inflow boundary conditions measured with pcMRI. Intra-aneurysmal flow patterns, maximum, minimum and average values of wall shear stress and wall shear stress histograms were calculated. Five additional computational flow dynamics simulations were performed, in which simulated inflow from the right and left A1 segment was varied, while keeping the total inflow constant. Intra-aneurysmal flow patterns measured with pcMRI were qualitatively compared to intra-aneurysmal flow patterns derived from the simulations. Results: Intra-aneurysmal flow patterns calculated in the baseline simulation were in good qualitative agreement with pcMRI measurements. Intra-aneurysmal flow patterns and wall shear stress changed considerably when inflow conditions were altered. Changes in the flow distribution between right and left A1 segments caused variations of the averaged wall shear stress as high as 43%. Conclusion: Intra-aneurysmal flow patterns and wall shear stress in an AcomA aneurysm calculated with computational flow dynamics depended strongly on the flow distribution between A1 segments. Patient-specific flow data measured with pcMRI obtained prior to computational flow dynamics are necessary for an accurate simulation of intra-aneurysmal flow patterns and calculation of wall shear stress in AcomA aneurysms. Further studies may indicate if wall shear stress calculated with computational flow dynamics can predict aneurysm growth and/or rupture.
ASJC Scopus subject areas
- Clinical Neurology