Quantitative and Qualitative Comparison of 4D-DSA with 3D-DSA Using Computational Fluid Dynamics Simulations in Cerebral Aneurysms

Abstract

BACKGROUND AND PURPOSE:

4D-DSA allows time-resolved 3D imaging of the cerebral vasculature. The aim of our study was to evaluate this method in comparison with the current criterion standard 3D-DSA by qualitative and quantitative means using computational fluid dynamics.

MATERIALS AND METHODS:

3D- and 4D-DSA datasets were acquired in patients with cerebral aneurysms. Computational fluid dynamics analysis was performed for all datasets. Using computational fluid dynamics, we compared 4D-DSA with 3D-DSA in terms of both aneurysmal geometry (quantitative: maximum diameter, ostium size [OZ1/2], volume) and hemodynamic parameters (qualitative: flow stability, flow complexity, inflow concentration; quantitative: average/maximum wall shear stress, impingement zone, low-stress zone, intra-aneurysmal pressure, and flow velocity). Qualitative parameters were descriptively analyzed. Correlation coefficients ( r, P value) were calculated for quantitative parameters.

RESULTS:

3D- and 4D-DSA datasets of 10 cerebral aneurysms in 10 patients were postprocessed. Evaluation of aneurysmal geometry with 4D-DSA ( r _{maximum diameter} = 0.98, P _{maximum diameter} <.001; r _OZ1/OZ2 = 0.98/0.86, P _OZ1/OZ2 < .001/.002; r _volume = 0.98, P _volume <.001) correlated highly with 3D-DSA. Evaluation of qualitative hemodynamic parameters (flow stability, flow complexity, inflow concentration) did show complete accordance, and evaluation of quantitative hemodynamic parameters ( r _{average/maximum wall shear stress diastole} = 0.92/0.88, P _{average/maximum wall shear stress diastole} < .001/.001; r _{average/maximum wall shear stress systole} = 0.94/0.93, P _{average/maximum wall shear stress systole} < .001/.001; r _{impingement zone} = 0.96, P _{impingement zone} < .001; r _{low-stress zone} = 1.00, P _{low-stress zone} = .01; r _{pressure diastole} = 0.84, P _{pressure diastole} = .002; r _{pressure systole} = 0.9, P _{pressure systole} < .001; r _{flow velocity diastole} = 0.95, P _{flow velocity diastole} < .001; r _{flow velocity systole} = 0.93, P _{flow velocity systole} < .001) did show nearly complete accordance between 4D- and 3D-DSA.

CONCLUSIONS:

Despite a different injection protocol, 4D-DSA is a reliable basis for computational fluid dynamics analysis of the intracranial vasculature and provides equivalent visualization of aneurysm geometry compared with 3D-DSA.