# Aortic Hemodynamics with Accelerated Dual-Venc 4D Flow MRI in Type B Aortic Dissection
## 2 Materials and Methods
### Image Processing and Segmentation  
The offline post-processing steps of the 4D flow MRI data were identical for all acquisition types using an in-house tool programmed in Matlab (MATLAB; The MathWorks, Natick, MA) to correct eddy currents, aliasing and noise of the areas outside of the flow regions as described previously [31; 32; 33]. Time-averaged magnitude and 3D phase-contrast angiogram (PC-MRA) images were utilized to perform the manual segmentations using the designated software (Mimics Innovation Suite; Materialise, Leuven, Belgium). The entire aorta, excluding aortic arch branch vessels, was manually segmented on the time-averaged 4D flow MRI magnitude images and PC-MRA images were used to segment the TL by an observer ([PERSON]) with 3 years of experience in imaging research. The entire aorta was segmented on the PC-MRA images in volunteers and used to mask the 4D flow MRI data. The volunteer data covering the entire aorta were combined with the TL data of the patient group for the TL analysis. The LV and HV data were combined into DV data on the scanner without any additional preprocessing steps. Post-acquisition processing steps, DVacquisition volumetric map examples and the HV data for several TL and FL parameters in one dnTBAD case are displayed in Figure 1.  
**Parametric Hemodynamic Maps**  
The 3D parametric maps for each flow parameter were obtained using in-house analysis tools (MATLAB; The MathWorks, Natick, MA, USA) according to a previously described approach [6; 18]. The 4D flow velocity data were interpolated to 1 mm\({}^{3}\) voxels using spline interpolation. The 3D aortic centerline was calculated automatically based on the TL, and orthogonal planes were automatically placed every millimeter along the centerline. In the next step, each voxel was matched to the closest plane to determine the flow direction along the centerline compared with the normal vector, i.e., forward (ascending aorta to descending aorta) and reverse (descending aorta to ascending aorta). The kinetic energy (KE), forward flow (FF) and 5 th percentile peak velocity (PV) were calculated inside the TL and FL for each voxel in the patient group and in the entire aorta of the volunteers. Voxel-wise reverse flow (RF) and stasis were separately calculated in the FL of the patient group, as described in our previous study [31]. _Forward Flow and Reverse Flow:_ The FF and RF were calculated in each voxel through the cardiac cycle and summed. The mean FF and mean RF were reported averaging these sums over the entire volume. _Kinetic Energy:_ The voxel-wise KE was calculated using the following equation: _KE_ = 0.5 \(\times\)\(\rho\)\(\times\)\(dV\)\(\times\)\(\
u\)(t)\({}^{2}\), where the assumed blood density (\(\rho\)) was 1060 kg/m\({}^{3}\), dV the unit voxel volume (i.e., 1 mm\({}^{3}\)) and the velocity magnitude for each voxel at each cardiac timeframe [i.e., \(\
u\)(t)]. The reported KE was calculated as total KE by summing the values in each voxel over the cardiac cycle and then over the entire luminal volume. _Peak Velocity:_ The 3D PV volumetric maps were determined using the time point with the maximum 95 th percentile voxel-wise PV. The mean of the top 5% of velocities was reported as PV for the TL and FL. _Stasis:_ The voxel-wise flow stasis was defined as the percentage of the cardiac timeframes that the velocity in that voxel is \(<\)0.1 m/s. These percentages were averaged over the entire FL volume and reported as mean stasis.