RESUMEN
PURPOSE: Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts. THEORY AND METHODS: Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets. RESULTS: In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error 0 . 82 ± 0 . 07 $$ 0.82\pm 0.07 $$ is reduced to: 0 . 66 ± 0 . 04 $$ 0.66\pm 0.04 $$ (Sign Correction); 0 . 34 ± 0 . 04 $$ 0.34\pm 0.04 $$ and 0 . 32 ± 0 . 04 $$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value < 0 . 05 $$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data. CONCLUSION: The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.
RESUMEN
Background: Understanding the risk factors leading to intracranial aneurysm (IA) rupture have still not been fully clarified. They are vital for proper medical guidance of patients harboring unruptured IAs. Clarifying the hemodynamics associated with the point of rupture could help could provide useful information about some of the risk factors. Thus far, few studies have studied this issue with often diverging conclusions. Methods: We identified a point of rupture in patients operated for an IAs during surgery, using a combination of preoperative computed tomography (CT) and computed tomography angiography (CTA). Hemodynamic parameters were calculated both for the aneurysm sac as a whole and the point of rupture. In two cases, the results of CFD were compared with those of the experiment using particle image velocimetry (PIV). Results: We were able to identify 6 aneurysms with a well-demarcated point of rupture. In four aneurysms, the rupture point was near the vortex with low wall shear stress (WSS) and high oscillatory shear index (OSI). In one case, the rupture point was in the flow jet with high WSS. In the last case, the rupture point was in the significant bleb and no specific hemodynamic parameters were found. The CFD results were verified in the PIV part of the study. Conclusion: Our study shows that different hemodynamic scenarios are associated with the site of IA rupture. The numerical simulations were confirmed by laboratory models. This study further supports the hypothesis that various pathological pathways may lead to aneurysm wall damage resulting in its rupture.