## 4 Discussion  
The present study constructed 12 healthy subject-specific carotid artery bifurcation geometrical models using 4D flow MRI and CFD. Bland-Altman plot analysis of velocity data at the carotid bifurcation plane showed good agreement between 4D flow MRI and CFD measurements. In addition, the shape of the velocity waveform, which indicated values of low and high blood flow speeds corresponding to each phase of the cardiac cycle, showed good consensus between these two methods. While none of these results reached statistical significance, velocity measurements in 4D flow MRI were higher compared to CFD for both the maximum and minimum blood flow velocities at the carotid bifurcation plane. This is because the arterial blood flow patterns strongly depend on both the vessel geometry and flow conditions. The accuracy of anatomical models generated from MR images depends on the resolution of the image and the algorithms for reconstruction. In particular, the construction of anatomical models from the 4D flow MRI can lead to a smaller vessel caliber estimation compared to CFD, which in turn can results in higher velocities of the blood flow in 4D flow MRI measurement [22]. There was a 6.12% difference in maximum velocity and a 25.46% difference of minimum velocity calculations between the 4D flow MRI and CFD measurements in our study. The greater error of minimum velocity may be related to the high-velocity encoding (100 cm/s) used for data acquisition, which resulted in higher velocity noise in low velocities, and thus reduced the accuracy of the minimum velocity calculation obtained through the 4D flow MRI technique [23]. Several factors resulted in errors in measuring the 4D flow MRI velocity. A limited spatial resolution of 4D flow MRI results in partial volume effects at the arterial wall and a limited number of velocity data points within the blood flow from which to estimate the parameters of the model and positions of the wall. In addition, phase-contrast pulse sequence may introduce displacement artifacts since the effective encoding times for positions and velocity do not coincide [18; 24]. Temporal resolution is an important factor as well. It is limited due to the trade-off between the temporal resolution and scan time in conventional 4D flow MRI sequences, and it has relatively low temporal resolution compared to CFD. This results in an average velocity though time, which reduces the ability to estimate transient  
Figure 6: Visualization of velocity streamlines in the carotid artery at peak systole using 4D flow MRI (**left**) and CFD (**right**). In the blood flow patterns derived from 4D flow MRI, the velocity streamlines were disconnected at the segment of an arterial wall within the carotid bifurcation domain (black arrow) and recirculation regions were not well captured (red arrow). events. To improve the accuracy of future MRI applications and to be able to measure the rapid variations in flow, it would be beneficial to increase spatial and temporal resolution [8; 23]. Besides, the 4D flow MRI measurement sensitivity to low velocities values is governed by the setting selected for the velocity encoding (VENC) level. It is common for the VENC to be set sufficiently high to avoid aliasing in those regions with the highest velocity, and there is a velocity-to-noise ratio for those affected in slow flow regions, which are generally at the lumen boundary. Methods to increase the velocity-to-noise ratio, e.g., using multiple VENCs or reduced VENCs with phase unwrapping, would help to increase sensitivity to the conditions of low-flow [25; 26]. The resolution, both spatial and temporal, is the main challenge to using 4D flow MRI. The primary effect of the limited spatial and temporal image resolution is the smoothing of the velocity pattern as a result of the average processes.