Normal patterns of thoracic aortic wall shear stress measured using four-dimensional flow MRI in a large population

Abstract

Wall shear stress (WSS) plays a governing role in vascular remodeling and a pathogenic role in vessel wall diseases. However, little is known of the normal WSS patterns in the aorta as there is currently no practical means to routinely measure WSS and no normal ranges derived from population data exist. WSS measurements were made on the aorta of 224 subjects with normal anatomy using four-dimensional flow MRI with multiple encoding velocities and an optimized postprocessing routine. The spatial and temporal variation in WSS and oscillatory shear index was analyzed using a flat map representation of the unfolded aorta. The influence of aortic shape and velocity on WSS was evaluated using regression analysis. WSS in the thoracic aorta is dominated by axial flow. Average peak systolic WSS was 1.79 ± 0.71 Pa in the aortic arch and was significantly higher at 2.23 ± 1.04 Pa in the descending aorta, with a strong negative correlation with advancing age. The spatial distribution of WSS is highly heterogeneous, with a localized region of elevated WSS along the length of the anterior wall seen across all individuals. Our data demonstrate that accurate four-dimensional flow-derived WSS measurement is feasible, and we further provide a standardized parametric approach for presentation and analysis. We present a normal range for WSS across the lifespan, demonstrating a decrease in WSS with advancing age as well as illustrating the high degree of spatial and temporal variation. NEW & NOTEWORTHY With the use of four-dimensional flow MRI and postprocessing, accurate direct measurement of wall shear stress (WSS) was performed in a population of normal thoracic aortas ( n = 224). WSS was higher in the descending aorta compared with the aortic arch and decreased with age. A heterogeneous pattern of elevated WSS along the length of the aorta anterior wall was consistent across the population. This work provides normal data across the adult age range, permitting comparison with pathology.

The impact of 4D flow displacement artifacts on wall shear stress estimation

“…[4][5][6] For this reason, several studies have determined WSS in the human aorta in patients with aortic stenosis 30 and aortic valve stenosis, 31,32 as well as in populations without aortic pathology. 33 Previous studies, however, have shown that the accuracy of the estimated WSS is susceptible to various imaging and postprocessing parameters, in particular the spatial resolution. [7][8][9] As demonstrated in numerical simulations, for example, by Petersson et al, 7 the WSS bias is reduced when reducing the voxel size.…”

“…The WSS, which is derived from the measured 4D flow data, is a potentially clinically relevant parameter because it describes the tangential force exerted per area on the vessel wall and is related to various pathologies 4‐6 . For this reason, several studies have determined WSS in the human aorta in patients with aortic stenosis 30 and aortic valve stenosis, 31,32 as well as in populations without aortic pathology 33 …”

Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses

“…Magnetic resonance velocity mapping in the infrarenal aorta found the mean wall shear stress in six healthy volunteers to be 0.28 ± 0.01 Pa, 23 while 4D flow measurement of the thoracic aorta of 224 patients found TAWSS values of 0.87 ± 0.31 Pa and 0.90 ± 0.37 Pa in the ascending and descending aorta respectively. 4 When considering the effect of TAWSS on the risk of thrombus formation, Myerson 18 proposed that a wall shear stress of < 0.2 Pa stimulated smooth muscle cell proliferation in venous bypass grafts and was therefore a critical threshold for the occurrence of neointimal thickening. Therefore, in this study a threshold value of 0.2 Pa for TAWSS is adopted when considering the increased risk of thrombus formation.…”

Análise Computacional da Dinâmica dos Fluídos na Substituição da Valva Aórtica Transcateter

“…In the absence of a readily applicable means to directly measure WSS, CFD has been applied in CT and MRI images to understand both the spatial and temporal patterns of WSS and the influence of aortic flow dynamics on this parameter. [7][8][9] Using CT images as the input of a CFD model, Celis et al 10 demonstrated that small variations of the aortic valve tilt angle could modify the nature of the flow and produce changes in the distribution of the WSS over the aorta wall.…”