# Aortic Hemodynamics with Accelerated Dual-Venc 4D Flow MRI in Type B Aortic Dissection
## 4 Discussion  
In this study we investigate the performance and reliability of compressed-sensing (CS)-accelerated dual-venc (DV) 4D flow magnetic resonance imaging (MRI) in type B aortic dissection (TBAD) compared with the traditional GRAPPA-accelerated 4D flow MRI. Key results include (1) significantly shorter scan times in CS-accelerated DV acquisition, (2) except for the false lumen (FL) reverse flow (RF), there is no significant difference for the true lumen (TL) or FL hemodynamic parameters between DV and single-venc (SV) acquisitions, (3) superior velocity-noise-ratio (VNR) with improved FL hemodynamic quantification using the DV protocol with CS acceleration relative to CS-accelerated high-venc (HV) alone and (4) excellent reproducibility of all three approaches. Our key takeaway is that the VNR gains with CS-accelerated DV acquisitions seem to improve the performance of CS-accelerated DV 4D flow MRI, especially for advanced hemodynamic characterization in regions more predisposed to effects of low VNR such as the FL in TBAD. This feature, combined with the substantial reduction in scan time makes CS-accelerated DV 4D flow MRI an attractive alternative to traditional and standard CS-accelerated 4D flow MRI in disease states with a high dynamic range of velocities such as aortic dissection. _Hemodynamic parameters in the true lumen and false lumen_  
It is interesting to note that our results demonstrate no significant difference in any of the hemodynamic TL parameters among three datasets including the conventional GRAPPA-accelerated 4D flow MRI and CS-accelerated DV 4D flow MRI and HV data acquired as a part of the DV acquisition. CS-based reconstruction has been previously used in various studies and underestimation of several 4D flow MRI-derived flow parameters has commonly been observed [13, 28, 29, 30, 35], differently from our study as we do not observe an underestimation of the PV in TL. In their study, [PERSON] et al. use three acceleration levels (R = 5.7, 7.7, and 10.2) of CS-accelerated 4D flow MRI protocol in a heterogenous cohort of patients with several aortic disease types and demonstrate an underestimation of several quantitative parameters by all CS based acquisitions. However, the number of TBAD cases is limited to four in their study and the FL analysis results in the dissection cases are not reported separately [13]. On the other hand, FL results demonstrate an overestimation of kinetic energy (KE) and flow parameters peak velocity (PV), forward flow (FF) and RF, and lower estimations of low flow parameter stasis in HV dataset compared with the DV acquisition. As the HV data is a subset of the DV acquisition, these effects are likely secondary to the higher VNR obtained in the DV reconstruction method. Among these hemodynamic parameters quantified, KE is the most unsteady parameter between two datasets with a 90% increase of the mean value from DV data to HV data. The percent change of the PV, FF, RF and stasis are 28.8, 23.5, 33.3 and 19.9%, respectively, which are relatively lower compared with KE. However, these results may still be considered as clinically significant. As KE calculation is directly proportional to the velocity squared, a small number of noisy voxels with a high velocity may be causing the higher average KE values and CS acceleration may be further contributing to the observed higher estimations by increasing the noise in the images. A similar trend for KE and stasis is also observed in the comparison between SV and HV datasets, which is likely secondary to the effects of the CS acceleration. Furthermore, these significant differences in KE and stasis support the idea of the impacts of the KE calculation method besides the impacts of the CS acceleration technique on the image noise. Additionally, the velocities are lower in FL compared with TL which leads to more susceptibility to image noise and velocity encoding (venc)-induced image noise limits the dynamic range of the measurable velocities, making the use of a DV approach in 4D flow MRI acquisitions more important.