ABSTRACT
The aim of this study was to conduct a flow experiment using a cerebrovascular phantom and investigate whether magnetic resonance angiography (MRA) could replace three-dimensional rotational angiography (RA) and computed tomography angiography (CTA) to construct vascular models for computational fluid dynamics (CFD). We performed MRA and 3D cine phase-contrast (PC) MR imaging with a silicone cerebrovascular phantom of an internal carotid artery-posterior communicating artery aneurysm with blood-mimicking fluid, and controlled flow with a flowmeter. We also obtained RA and CTA data for the phantom. Four analysts constructed vascular models based on the three different modalities. These 12 constructed models used flow information based on 3D cine PC MR imaging for CFD. We compared RA-, CTA-, MRA-based CFD results using the micro-CT-based CFD result as the criterion standard to investigate whether MRA-based CFD was not inferior to RA- or CTA-based CFD. We also analyzed the inter-analyst variability. Wall shear stress (WSS) distributions and streamlines of RA- or MRA-based CFD and those of micro-CT-based CFD were similar, but the vascular models and WSS values were different. Accuracy in measurements of blood vessel diameter, cross-sectional maximum velocity, and spatially averaged WSS was the highest for RA-based CFD, followed by MRA-based and CTA-based CFD using micro-CT-based CFD result as the reference. Except maximum velocity from CTA, all other parameters had good inter-analyst agreement using different modalities. The results demonstrated that non-invasive MRA can be used for cerebrovascular CFD models with good inter-analyst agreements.
Subject(s)
Intracranial Aneurysm , Magnetic Resonance Angiography , Computed Tomography Angiography , Cross-Sectional Studies , Humans , HydrodynamicsABSTRACT
PURPOSE: Evaluate in vivo hemodynamic and morphological biomarkers of intracranial aneurysms, using magnetic resonance fluid dynamics (MRFD) and MR-based patient specific computational fluid dynamics (CFD) in order to assess the risk of rupture. METHODS: Forty-eight intracranial aneurysms (10 ruptured, 38 unruptured) were scrutinized for six morphological and 10 hemodynamic biomarkers. Morphological biomarkers were calculated based on 3D time-of-flight magnetic resonance angiography (3D TOF MRA) in MRFD analysis. Hemodynamic biomarkers were assessed using both MRFD and CFD analyses. MRFD was performed using 3D TOF MRA and 3D cine phase-contrast magnetic resonance imaging (3D cine PC MRI). CFD was performed utilizing patient specific inflow-outflow boundary conditions derived from 3D cine PC MRI. Univariate analysis was carried out to identify statistically significant biomarkers for aneurysm rupture and receiver operating characteristic (ROC) analysis was performed for the significant biomarkers. Binary logistic regression was performed to identify independent predictive biomarkers. RESULTS: Morphological biomarker analysis revealed that aneurysm size [P = 0.021], volume [P = 0.035] and size ratio [P = 0.039] were statistically significantly different between the two groups. In hemodynamic biomarker analysis, MRFD results indicated that ruptured aneurysms had higher oscillatory shear index (OSI) [OSI.max, P = 0.037] and higher relative residence time (RRT) [RRT.ave, P = 0.035] compared with unruptured aneurysms. Correspondingly CFD analysis demonstrated significant differences for both average and maximum OSI [OSI.ave, P = 0.008; OSI.max, P = 0.01] and maximum RRT [RRT.max, P = 0.045]. ROC analysis revealed AUC values greater than 0.7 for all significant biomarkers. Aneurysm volume [AUC, 0.718; 95% CI, 0.491-0.946] and average OSI obtained from CFD [AUC, 0.774; 95% CI, 0.586-0.961] were retained in the respective logistic regression models. CONCLUSION: Both morphological and hemodynamic biomarkers have significant influence on intracranial aneurysm rupture. Aneurysm size, volume, size ratio, OSI and RRT could be potential biomarkers to assess aneurysm rupture risk.
