Scan–rescan reproducibility of segmental aortic wall shear stress as assessed by phase-specific segmentation with 4D flow MRI in healthy volunteers

Four-dimensional flow magnetic resonance imaging (4D flow MRI) is a non-invasive imaging method to investigate in vivo cardiovascular flow and is used to better understand cardiovascular physiology and pathophysiology. Besides simple measures of flow [1‐3], this technique allows for quantification of more comprehensive hemodynamic parameters, such as wall shear stress (WSS) [4, 5]. WSS is defined as the viscous shear force of flowing blood acting tangentially to the vessel wall and can be estimated in both small and large vessels. Alterations in WSS within the aorta have been associated with vascular wall remodelling and dysfunction [6] and this hemodynamic parameter is therefore of interest in patients with aortopathy.

Aortic WSS can be calculated from 4D flow MRI data based on 2D cross-sectional planes at specific locations along the vessel wall [7] or by volumetric 3D WSS computational algorithms [8]. It is known that several acquisition and post-processing factors may influence the estimation of WSS, e.g., spatial resolution, settings of encoding velocity (VENC parameter), signal-to-noise ratio and segmentation inaccuracies [9, 10]. Estimation of WSS from 4D flow MRI data necessitates analysis of velocity data within a geometric representation of the 3D vascular structure of interest through segmentation (i.e., creating a cast of the vessel of interest) [11]. Currently, thoracic aorta segmentations in most studies are based on phase contrast MR angiograms averaged over all cardiac time frames or manually drawn for every cardiac time frame in 2D planes. Using these approaches, accurate WSS reproducibility has been proven in healthy volunteers [7, 12]. However, due to movement of the aorta during the cardiac cycle, aortic compliance and peak systolic time-differences of the propagating blood flow wave front along the thoracic aorta, calculations of WSS throughout the systolic cardiac cycle from a time frame averaged aortic cast could lead to an incorrect assessment of true aortic border velocities for aortic segments along the thoracic aorta.

Therefore, the aim of the study was to assess scan–rescan reproducibility and observer variability of segmental aortic 3D WSS based on semi-automatic, systolic phase-specific 3D aortic segmentation from 4D flow MRI in healthy volunteers. To put the reproducibility analysis of segmental WSS approach into clinical perspective, aortic WSS analyses of two patient cases with congenital aortic abnormalities were compared to the healthy volunteers.

Baseline characteristics of the volunteers are shown in Table 1. Average heart rate (HR) was similar in the volunteers for the scan and rescan (60.8 ± 7.7 vs 61.6 ± 6.0 bpm, P = 0.65). Average time-points of the five systolic phases (ms) throughout the cardiac cycle were not significantly different between the scan and rescan data from the volunteers (Table 1).

The results of this study demonstrate reproducibility of segmental aortic systolic 3D WSS measures in the thoracic aorta of healthy volunteers, by phase-specific 4D flow MRI segmentation. Scan–rescan reproducibility was good for WSSmean for all thoracic aortic regions but scan–rescan reproducibility for WSSmax was moderate with higher variability up to 31% in the proximal ascending aorta. The intraobserver and interobserver reproducibility for segmental systolic WSS analysis of WSSmax and WSSmean was good to excellent. In general, the ascending aortic segments showed more variability in WSSmax and WSSmean measurements compared to aortic arch or descending aortic segments for scan–rescan, intraobserver and interobserver comparison.

Deriving accurate WSS from 4D flow MR velocity data remains challenging and delineation of the aortic wall influences the accuracy of this WSS estimation [9, 10]. Most of the previously reported studies on 3D WSS assessment make use of segmentations based on phase contrast MR angiograms averaged over all cardiac time frames to assess aortic WSS over the entire systolic cardiac cycle [12, 15‐17]. In this study, we used a phase-specific segmentation approach for 3D WSS calculations from velocity data for five consecutive systolic cardiac phases. A major advantage of this phase-specific segmentation approach is that it will approximate the aortic wall of the thoracic aorta more accurate in order to better estimate true border WSS. Due to the aortic compliance and movement of the aorta, calculations from a segmentation from averaged phase contrast MR angiograms over all cardiac time frames could lead to an incorrect assessment of WSS along the thoracic aortic wall. Furthermore, the phase-specific segmentations enable identification of peak systolic WSS for each aortic segment along the thoracic aorta, which for every aortic segment is reached at a different time frame throughout systole.

The ability to measure advanced aortic hemodynamic parameters make 4D flow MRI potentially valuable for patients with different entities of aortopathy: to assess disease severity, to better anticipate disease progression and potentially stratify patients at risk for adverse events. However, knowledge of scan–rescan variability for regional WSS measures is essential to study interactions between hemodynamic parameters and aortic geometry and to judge whether hemodynamic changes in patients over time represent true (patho)physiological changes.

Few studies have investigated scan–rescan reproducibility and/or observer variability of aortic WSS measurements in vivo [7, 12, 18]. Similar to our findings, these studies reported good scan–rescan reproducibility for WSSmean measures with relatively higher scan–rescan variability for WSSmax measures. However, these WSS reproducibility studies used different approaches for WSS estimation varying from a time-resolved 2D planar WSS quantification method with manual 2D aortic segmentation [7] to a volumetric 3D WSS assessment from an aortic segmentation from phase contrast MRAs averaged over all cardiac time frames [12]. Furthermore, different time intervals between first and second scan in these studies were chosen compared to this study and varied from 2 to 4 weeks [12] to 1 year [7]. Moreover, in the study by van Ooij et al. [12] anisotropic voxels of different sizes for different subjects were used, that might have resulted in accuracy problems of WSS estimations between subjects. Our study extends the WSS reproducibility knowledge with its phase-specific, semi-automated 3D WSS segmentation approach with segmental aortic WSS assessment from a non-contrast enhanced 4D flow MRI data acquisition. The good to excellent intra- and interobserver reproducibility from this study is in accordance with these reported studies [7, 12] and a study by Bieging et al. [18], in which observer reproducibility was evaluated by a time-resolved volumetric 3D aortic WSS approach for contrast-enhanced 4D flow MRI.

In general, ascending aortic segments showed more variability in WSSmax and WSSmean compared to aortic arch or descending aortic segments for scan–rescan, intra- and interobserver comparison. Operator and subject dependent factors may have contributed to the differences found in WSS reproducibility for different aortic segments. First, the sub-optimal anatomic information within the 4D flow dataset hampers the exact manual determination of the aortic segments based on anatomic landmarks; especially identifying the sinotubular junction to determine the proximal ascending aortic segment proved to be challenging. Second, variability due to movement and systolic longitudinal stretch of the ascending aorta cannot entirely been ruled out as an influencing factor, despite the phase-specific segmentation has been applied. Heart-beat related motion and longitudinal stretch during systole has been reported to be more present in the ascending aorta compared to the aortic arch and descending aorta [19, 20]. Third, small individual variations in heart rate might have affected WSS differences between scan and rescan, although the averaged heart rate of each individual volunteer was not significantly different between the consecutive scans. Greater variability was found in WSSmax for both scan–rescan, but in general WSSmax values are more subject to noise than WSSmean values. Furthermore, the VENC setting affects the velocity-to-noise ratio and therefore may have influence on the WSS calculations in the low velocity range near the aortic wall. In this study, VENC was 200 cm/s, which was chosen with respect to the anticipated peak velocity in the full aorta, in order to avoid phase wrapping. However, the VENC setting was identical between the scan and rescan and differences due to the velocity sensitivity between both scans are therefore unlikely.

In patients with aortopathy, the aorta can be regionally affected or being entirely involved in the disease, depending on its expression. Aortic WSS disturbances have been shown to strongly correlate with molecular and architectural medial aortic wall alterations [6] or show a direct relation with its regional aortic geometry [16, 21]. The regional WSS analysis by phase-specific segmentation models in the presented patient cases provides its clinical applicability in locally diseased aortas, as the WSS values in patient 1 fall far beyond the confidence intervals of the healthy controls and the WSS values in patient 2 are considerably lower than these of the healthy controls with this WSS approach. Using this method, it shows that segment-specific aortic WSS estimation is discriminative and emphasizes the importance of accurate knowledge of WSS reproducibility and consistency across different aortic segments for each applied WSS method.

A limitation of this study is that the study consisted of only ten healthy volunteers with a relatively small age range. A larger number of volunteers with a larger variation of age could have provided more information about the robustness of this method over ages. The study did not include patients with aortopathy for a scan–rescan comparison, which could have provided more insight in the reproducibility of this method for clinical use in patients with aortic disease. The spatial and temporal resolution was similar for the scan-and rescan and both were performed without use of contrast agents. The latter could be considered as a limitation as the use of contrast agents might have increased our signal-to-noise ratio and therefore our reproducibility. However, in the light of the recent discussions on the use of contrast agents in cardiovascular MR, we tested the robustness of the WSS assessment method with 4D flow MRI without contrast [22]. The scan and rescan for every volunteer in this study was performed on the same day, which is the most ideal circumstance for a reproducibility analysis, as the volunteers were in the same cardiovascular, neurohormonal and mental status, at the same scanner, and at the similar moment of the day. Repeated scans on separate days would have been more comparable with clinical practice and may have resulted in a more realistic estimation of reproducibility. However, these assessments have already been performed in other WSS reproducibility studies with time intervals between first and second scan varying from 2 to 4 weeks [12] to 1 year [7].

In conclusion, reproducibility of phase-specific WSS assessment in this scan–rescan study in healthy volunteers was good for mean 3D systolic WSS for all thoracic aortic segments over multiple systolic phases. Maximum 3D systolic WSS showed more variability, up to 31% for the proximal ascending aortic region. Although intra- and interobserver reproducibility is good to excellent, these scan–rescan WSS variations should be considered to avoid misinterpretation by investigators in case of individual follow-up or in comparative rest–stress studies.