S Lang1, P Hoelter2, A I Birkhold3, M Schmidt2, J Endres2, C Strother4, A Doerfler2, H Luecking2. 1. From the Department of Neuroradiology (S.L., P.H., M.S., J.E., A.D., H.L.), University of Erlangen-Nuremberg, Erlangen, Germany Stefan.Lang3@uk-erlangen.de. 2. From the Department of Neuroradiology (S.L., P.H., M.S., J.E., A.D., H.L.), University of Erlangen-Nuremberg, Erlangen, Germany. 3. Siemens Healthcare GmbH (A.I.B.), Erlangen, Germany. 4. Department of Radiology (C.S.), Clinical Sciences Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.
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.
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.
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