Regional variation of wall shear stress in ascending thoracic aortic aneurysms.

Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine http://pih.sagepub.com/

Regional variation of wall shear stress in ascending thoracic aortic aneurysms Antonino Rinaudo and Salvatore Pasta Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine published online 18 June 2014 DOI: 10.1177/0954411914540877 The online version of this article can be found at: http://pih.sagepub.com/content/early/2014/06/18/0954411914540877

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Original Article

Regional variation of wall shear stress in ascending thoracic aortic aneurysms

Proc IMechE Part H: J Engineering in Medicine 1–12 Ó IMechE 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0954411914540877 pih.sagepub.com

Antonino Rinaudo1 and Salvatore Pasta2

Abstract The development of an ascending thoracic aortic aneurysm is likely caused by excessive hemodynamic loads exerted on the aneurysmal wall. Computational fluid-dynamic analyses were performed on patient-specific ascending thoracic aortic aneurysms obtained from patients with either bicuspid aortic valve or tricuspid aortic valve to evaluate hemodynamic and wall shear parameters, imparting aneurysm enlargement. Results showed an accelerated flow along the outer aortic wall with helical flow in the aneurysm center for bicuspid aortic valve ascending thoracic aortic aneurysms. In a different way, tricuspid aortic valve ascending thoracic aortic aneurysms exhibited normal systolic flow without substantial secondary pattern. Analysis of wall shear parameters evinced a high and locally varying wall shear stress on the outer aortic wall and high temporal oscillations in wall shear stress (oscillatory shear index) on either left or right side of aneurysmal aorta. These findings may explain the asymmetric dilatation typically observed in ascending thoracic aortic aneurysms. Simulations of a hypertensive scenario revealed an increase in wall shear stress upon 44% compared to normal systemic pressure models. Computational fluid-dynamics–based analysis may allow identification of wall shear parameters portending aneurysm dilatation and hence guide preventative intervention.

Keywords Computational fluid dynamics, ascending thoracic aortic aneurysm, bicuspid aortic valve, wall shear stress, hypertension

Date received: 15 December 2013; accepted: 30 May 2014

Introduction An ascending thoracic aortic aneurysm (ATAA) is a life-threatening cardiovascular emergency with remarkable morbidity and mortality. The incidence of ATAAs is estimated at 6 people/100,000/year, occurring most commonly in the sixth and seventh decades of life and in males more frequently than females (ratio 3:1).1 Fatal complications such as aortic rupture or dissection are most commonly associated with ATAA development, and these can be prevented by rapid surgical repair. Davies et al.2 reported that rupture rates in patients not treated surgically range from 21% to 74%, and that the risk of operation is relevant as well. Indeed, elective surgery carries a mortality rate of approximately 5%–9%, whereas mortality rate may be as high as 57% for emergency surgery. There are several risk factors predisposing patients to aortic dilatation. Individuals with bicuspid aortic valve (BAV) develop ATAA more frequently than the healthy subjects with tricuspid aortic valve (TAV), even when matched for the degree of aortic-valve stenosis.3 BAV patients with ATAA have a ninefold increased risk of aneurysm rupture compared with those with a

morphologically normal TAV.2 Moreover, severe hypertension accelerates disease progression due to an aggressive blood pressure increase. In fact, Juvonen et al.4 illustrated that patients who experienced ATAA rupture had significantly higher mean arterial pressure and diastolic blood pressure than patients without rupture. Therefore, continued surveillance is strongly recommended to monitor aneurysm progression. In medical imaging, the four-dimensional (4D) flow magnetic resonance imaging (MRI) is able to provide not only morphological information as the aneurysm diameter, but also the non-invasive measurement of all three-directional components of the blood flow velocity.5 Applications of 4D flow MRI revealed abnormally pronounced helical or vortical flow features in

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Dipartimento di Ingegneria Chimica, Gestionale, Informatica e Meccanica (DICGIM), Universita’ di Palermo, Palermo, Italy 2 Fondazione Ri.MED, Palermo, Italy Corresponding author: Salvatore Pasta, Fondazione Ri.MED, Via Bandiera n.11, 90133 Palermo, Italy. Email: [email protected]


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Proc IMechE Part H: J Engineering in Medicine

patients with ATAAs as well as a link between BAV and aortic dilatation.6–8 Flow characterization, especially in BAV, may help to identify patients at high risk for aneurysm development as suggested by Hope et al.9 However, the cause of the relationship between BAVrelated flow abnormalities and ATAA dilatation is an ongoing debate. It can be speculated that abnormal flow patterns may contribute to increase local aortic shear forces, which in turn inhibit vascular remodeling. Several in vitro studies suggest that changes in both wall shear stress (WSS) and temporal WSS oscillations (i.e. the oscillatory shear index (OSI)) have an impact on the endothelial cell function, including migration, proliferation and activation of transcription factors.10,11 This may ultimately determine a proximal dilatation of the ascending aorta. The objective of this study was therefore to evaluate the relevant hemodynamic and WSS distribution in ATAAs, which are associated with different valve morphology (BAV vs TAV). This was achieved by performing computational fluid-dynamic (CFD) analyses on patient-specific ATAA models. Hypertension was also simulated to assess changes of wall shear parameters.

Materials and methods ATAA reconstruction and grid generation Electrocardiogram (ECG)-gated computed tomography angiography (CTA) scans were used to reconstruct ATAA models identified from radiologic records of our hospital as performed in similar studies.12,13 Specifically, we segmented ATAAs of three patients with TAV and two patients with BAV. For each patient, Table 1 summarizes the demographic data, BAV type, history of hypertension and presence of aortic stenosis or aortic insufficiency. The study was approved by our ethics committee, and informed consent was obtained from the patients. ECG-gated CTA scans were retro-reconstructed to obtain images at cardiac phase with the largest orifice area of the aortic valve, which frequently occurs at 50– 100 ms after the R peak. Specifically, the phase with the largest orifice area was extrapolated from the multiphase CTA data set consisting of 10 phases at 10% intervals ranging from 0% to 90% of the cardiac cycle.

Image resolution was 512 3 512 pixels to keep size of CTA data set manageable. The data processing was performed by experienced radiology technicians using dedicated software provided with our computed tomography (CT) scanner (VCT 64; GE Medical Systems, WI, USA) in an offline post-processing workstation. ATAA geometries were reconstructed using the vascular modeling toolkit (VMTK) (http://www.vmtk.org). Images were segmented from the aortic valve, through the ascending aorta, the aortic arch and supra-aortic vessels and the descending aorta, ending at the level of the diaphragm. Aortic valve was reconstructed at fully opened shape. To achieve good convergence in CFD simulations, mesh quality checks were performed using grid convergence index (GCI).14 ATAA models were meshed with unstructured tetrahedral elements using GAMBIT 2.3.6 (ANSYS Inc., Canonsburg, PA, USA) with different refinement levels. The average element size near the aortic wall was 0.49 mm for the highest mesh refinement. The calculations of discretization error for WSS as well as the grid parameters are summarized in Table 2, while representative mesh for a BAV ATAA is shown in Figure 1. For time independency, several time steps were tested: 0.001, 0.002, 0.0025 and 0.003 s. The optimal solution was found for a time step of 0.0025 s (i.e. 400 steps for cardiac cycle).

CFD simulation Fluid dynamic was evaluated by steady and unsteady CFD simulations, which were performed using FLUENT v13.0.0 (ANSYS Inc.). The approach was based on an experimentally validated secondorder algorithm, which was developed to resolve specifically high-frequency, time-dependent flow instabilities encountered in complex cardiovascular anatomies.15,16 The blood flow was assumed incompressible and Newtonian with a density of 1060 kg/m3 and viscosity of 3.71 3 1023 Pa s. The assumption of Newtonian fluid for blood with a constant viscosity is feasible in large vessels.17 Although several works such as Khanafer et al.18 showed that the non-Newtonian assumption of blood affects the blood flow in the thoracic aorta, their simulations did not display significant differences in WSS calculated from Newtonian and non-Newtonian

Table 1. Clinical data of patients with ATAAs. Type 1 R/N BAV indicates fusion of right and non-coronary aortic leaflets while Type 0 BAV indicates a purely bicuspid with two symmetric leaflets. Patient ID

Valve

Leaflet fusion

Aneurysm diameter (mm)

Age (year)

Sex

History of hypertension

(A) (B) (C) (D) (E)

BAV BAV TAV TAV TAV

Type 0 Type 1 R/N

41 57 39 44 45

68 48 62 68 76

Male Male Male Female Female

Yes

BAV: bicuspid aortic valve; TAV: tricuspid aortic valve.


Aortic stenosis

Aortic insufficiency

Severe

Severe

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Table 2. Mesh size, approximate relative error e21 a , 21 extrapolated relative error eext , and fine-grid convergence index GCI21 fine for mesh independence analysis. Calculations were performed using the average values of WSS over each plane.

Cell number Element size (mm) Cell volume (mm3) e21 a (%) e21 ext (%) GCI21 fine (%)

Coarse

Medium

Fine

530,964 0.98 0.0640

819,560 0.71 0.0207

1,017,314 0.49 0.0123 3.1 8.4 11.5

Figure 2. Representative inlet flow waveform for patient (A) with BAV ATAA showing base inflow profile (to obtain a cardiac output of 5 L/min) and hypertensive scenario (i.e. scaled version of base profile to obtain inlet pressure of 180 mm Hg). The base inflow profile is extracted by Pasta et al.20

Figure 1. Representative mesh of patient (B) with BAV ATAA showing outflow and inflow extensions as well as valve opening. BAV: bicuspid aortic valve.

simulations. Pressure-implicit with splitting of operators (PISO) and skewness correction was used as pressure–velocity coupling algorithm to improve the convergence of the transient calculations in close vicinity of distorted cells. Second-order upwind scheme was applied to discretize the convective terms in momentum equations in order to eliminate numerical diffusion in calculations. Pressure staggering option (PRESTO) scheme as pressure interpolation method was set with second-order accurate discretization. Convergence was enforced reducing the residual of the continuity equation by 1027 at all time steps. The total cardiac output (i.e. inlet flow to aortic root) was assumed at 5 L/min, and this flow was split between the supra-aortic vessels and the descending aorta with a

ratio of 20/80 (corresponding to in-vivo patient measurements) using resistance boundary conditions.15 Specifically, the flow entering into supra-aortic vessels was 10% at brachiocephalic trunk, 4% at left common carotid artery and 6% at left subclavian artery as it was used in a similar study.19 Steady-state solutions were used to initialize the flow field prior to the transient analyses. To address the numerical stability problems due to the high systemic resistances of multi-outlet aortic anatomy (i.e. since even the minute flow rate adjustments are transferred as large pressure oscillations in 3D domain), an iterative under-relaxationbased resistance boundary condition was coupled to each outlet.16 At each inner iteration, the pressure gradient calculated at the outlets was attenuated 10 times to ensure smoother convergence. Each downstream resistance was coupled to the solver iteratively to prevent divergence due to multiple outlets. A pulsatile aortic flow waveform was set as inlet condition for the unsteady CFD simulations. All outlets were extended four diameters normal to the vessel cross section. Specifically, the inflow aortic profile presented a fundamental frequency of 1 Hz as we performed in previous works20,21 (Figure 2). To simulate hypertension, the aortic flow waveform was scaled to obtain an inlet pressure of 180 mmHg at the aortic valve. Simulations were continued through three cardiac cycles to eliminate nonlinear start-up effects, and results presented here were obtained at the last cycle. Computations were performed on a Dell Workstation equipped with two quad-core 3.2-GHz processors using eight parallel processes. The total time of computation for each model was approximately 3 days. Post-processing was performed using EnSight (v9.0, CEI, Apex, NC, USA) for the calculation of wall shear parameters. Specifically, the time-averaged WSS (TAWSS) magnitude was defined as22


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ðT 1 ! ð1Þ tw = tW dt T 0 ! ! where tW is the magnitude of WSS vector, tW and T is the duration of one cardiac cycle. The OSI was defined as22 1 0 ÐT ! tW dtC B C 0 1B C ð2Þ 1 OSI = B ÐT ! C 2B A @ tW dt 0

This takes values in the range of 0–0.5, with 0 corresponding to unidirectional flow and 0.5 to purely oscillatory flow.

revealed marked flow deflection (i.e. high OSI) on either left or right side of the aorta, whereas both outer and inner curvatures of ATAAs exhibited unidirectional flow over cardiac cycle (i.e. low OSI). Figure 6 shows the comparison of TAWSS and OSI between BAV ATAAs and TAV ATAAs. Although aneurysm diameters differ among patients, BAV ATAAs had lower values of TAWSS and higher values of OSI compared to those of TAV ATAAs. This is likely caused by the low peripheral and highly skewed flow occurring along the ascending aortic wall of BAV ATAAs. Systolic WSS distributions for simulated scenarios of hypertension increased drastically (see Table 3). Although WSS distribution did not change markedly, the mid-ascending aortic region exhibited WSS values as high as 44%. This increase was pronounced at sinotubular junction with a WSS value up to 56%.

Results Flow structure in ATAAs

Plane-wise analysis of WSS and OSI

Vectorial analysis was performed at systole by means of orthogonal planes extrapolated at four different levels along ATAA circumference (Figure 3). BAV ATAAs displayed left-handed, nested, helical flows within the ascending aorta in which streamlines accelerated along the outer curvature of the aortic wall to form large recirculating vortexes in the aneurysm center (i.e. planes 2, 3 and 4). At sinotubular junction, flow wrapped back toward the aortic valve (i.e. plane 1). For both patients (C) and (D) with non-stenotic TAV, parallel streamlines spanned the ATAA with minimal deviance from the initial direction of the aortic-valve flow and slight degree of flow skewing close to the outer curvature of ascending aorta (AoA). However, patient (E) exhibited abnormal secondary flow pattern likely induced by the severe aortic valve stenosis and regurgitation of TAV. Flow velocity was found higher for TAV ATAAs compared to that of BAV ATAAs (e.g. velocity of 3.2 m/s for patient (A) and 5.3 m/s for patient (C) at plane 2).

For each of the analysis plane location, wall shear parameters of ATAAs were represented by polar plots. For all patients, systolic WSS increased from the aortic valve (i.e. plane 1) to the distal ascending aorta (i.e. plane 4), with the outer curvature exposed to higher magnitudes than those of inner aortic wall (Figure 7). This effect is markedly evinced by TAV ATAAs with normal function of aortic valve leaflets (i.e. patients (C) and (D)). In contrast, BAV ATAAs and TAV ATAAs with severe aortic stenosis and regurgitation manifested a slight deviation of maximum WSS value as shown by planes 3 and 4. Indeed, maximum systolic WSS occurred at 150° for both patient (B) and (E). It should also be noted that plane analysis illustrated positive WSS gradient from the aortic valve to the distal aorta for all patients with ATAAs. OSI was very pronounced in the left and inner walls of the aneurysmal aorta at mid-ascending aortic region (Figure 8). These areas corresponded well to regions of low systolic WSS as shown by planes 3 and 4. At sinotubular junction (i.e. plane 1), TAV ATAAs presented low values of OSI at aortic wall compared to that of BAV ATAAs since flow was slightly deviated by aorticvalve leaflets. Patient (B) with fusion of the right and non-coronary aortic leaflets has shown a remarkable flow deflection (i.e. high OSI) compared to patient (A) with a purely BAV morphology. This suggests that flow patterns may differ among every patient as it is influenced by the aortic-valve geometry.

WSS and OSI distribution Flow instability resulted in fluctuations of systolic WSS on the ATAA wall as shown by wall shear distribution (Figure 4). The sites of marked systolic WSS were observed in the outer curvature of the ascending aortic wall where flow was moving rapidly. Specifically, high WSS regions of BAV ATAAs appeared more extended than those of patients with TAV due to the pathological valve function. Additionally, patients with large aneurysm diameter displayed elevated systolic WSS compared to small-sized ATAAs. These hemodynamic disturbances suggest that the outer region of ATAAs is critical for aneurysm development and enlargement. We also evaluated the temporal oscillations in the WSS as described by OSI, which is a marker of blood flow–predominant direction during cardiac cycle. For all ATAAs, distributions of OSI parameter (Figure 5)

Discussion This research demonstrates clearly that the aortic valve morphology induces a regional variation of shear loads exerted on the aortic wall of ATAAs. Our results suggest that BAV ATAAs have an abnormal, highly skewed flow pattern characterized by both high systolic WSS and low OSI on the outer curvature of the aortic


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Figure 3. Vectorial analysis of systolic flow (t = 0.2 s) at four planes for patients with BAV (top two models) and TAV (bottom three models). Flow streamlines within ATAAs (right) show the level of each analysis plane taken from the STJ (column 1) to the distal aneurysmal aorta (column 4). Analysis planes were positioned in a standardized fashion to ensure comparability. BAV ATAA: bicuspid aortic valve ascending thoracic aortic aneurysm; TAV ATAA: tricuspid aortic valve ascending thoracic aortic aneurysm; Out: outer curvature, InC: inner curvature, L: left side of aortic wall, R: right side of aortic wall.

wall when compared to TAV ATAAs. Information on the hemodynamic forces exerted on the ATAA wall as described in this study may help to complement the clinical information given by the aneurysm diameter and facilitate a more individualized patient management. The 4D flow MRI is emerging as a novel, noninvasive technique for retrospective quantification of altered blood flow features within an acquired volume. This technique has been recently used to investigate

cardiovascular diseases as the flow pattern arising in ATAAs.6–9 Specifically, BAV ATAAs highlighted a localized flow acceleration along the outer wall of the ascending aorta, which developed into helical flow in the aneurysm center.9 In a different way, TAV ATAAs experience normal systolic flow without substantial secondary pattern. Moreover, Hope et al.8,9,23 showed that eccentric systolic blood flow in the context of BAV is correlated with increased aortic growth rate. These flow


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Figure 4. Comparison of systolic WSS for ATAA patients with BAV (top two models) and TAV (bottom three models). BAV ATAA: bicuspid aortic valve ascending thoracic aortic aneurysm; TAV ATAA: tricuspid aortic valve ascending thoracic aortic aneurysm.

features are similar to those reported by our study on the onset of the aortic dissection in ATAAs, suggesting that intrinsic flow abnormalities associated with BAV are directly implicated in the development of aortic enlargement.12 For TAV ATAAs, the slight flow deviation toward the outer aneurysmal wall was expected on the basis of the axis offset between the left ventricle and aortic root. On the contrary, the flow pattern of the stenotic TAV (i.e. patient (E)) was similar to that of BAV ATAAs, suggesting a negative effect of the impaired opening of aortic-valve leaflets.

Using 4D flow MRI, hemodynamic-derived parameters such as the WSS can be potentially estimated by the measurements of the three-directional velocity field. Recent studies9,24 reported that patients with BAV have focally elevated systolic WSS on outer aneurysmal wall as reported by our computational data (see Figure 5). However, the accuracy of 4D flow MRI is limited by a low spatial and temporal resolution of the order of 2 mm3 and 40 ms, respectively. This results in an averaging of the measured velocity field, which negatively impacts the calculated values of the velocity gradient at


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Figure 5. Comparison of OSI for ATAA patients with BAV (top two models) and TAV (bottom three models). BAV ATAA: bicuspid aortic valve ascending thoracic aortic aneurysm; TAV ATAA: tricuspid aortic valve ascending thoracic aortic aneurysm.

vessel edge. Several studies have shown that absolute values of MRI-derived WSS are not trustworthy and that CFD modeling is clearly advantageous for such analysis.25,26 In ATAAs, WSSs determined by 4D MRI imaging were underestimated (i.e. 0.9–2.3 N/m2) when compared to those determined by CFD simulations. The prolonged exposure to altered WSSs on the outer aneurysmal curvature may be one of the main factors underlying the aortic degeneration, indicating the structural fragility of the aneurysmal wall. Indeed, WSS is an important regulator of vascular homeostasis by influencing directly the endothelial cell function.27 A recent research has shown that very high WSS values (;28.4 N/m2), which were recreated in a cell culture

chamber, increased apoptosis compared to lower WSS (;3.5 N/m2) conditions.28 This suggests a detrimental effect on the endothelial cell layer, which determines a mechanical damage to cell–cell junctions or cell surface integrity. In our study, both BAV ATAAs and TAV ATAAs presented systolic WSSs comparable to those measured in cell culture by Dolan et al.,28 suggesting aneurysm growth and vessel weakening. This is also supported by clinical evidence of asymmetric ATAA dilatations, which likely occur in regions of elevated WSS values. Even higher shear forces, upward of 30 N/m2, have been found by Alnaes et al.29 in locations where cerebral aneurysms tend to form preferentially. Specifically, flow impinges in the bifurcation


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Figure 6. Comparison of both TAWSS (i.e. time-averaged WSS over the cardiac cycle) and OSI (mean 6 standard error of the mean) for ATAAs with either BAV or TAV. BAV: bicuspid aortic valve; ATAA: ascending thoracic aortic aneurysm; TAV: tricuspid aortic valve; OSI: oscillatory shear index.

Table 3. Maximum values (and percent variation) of systolic WSS at each analysis plane for ATAAs with simulated hypertension. Units are in N/m2. Valve

Patient (ID)

Plane 1

Plane 2

Plane 3

Plane 4

BAV BAV TAV TAV TAV

(A) (B) (C) (D) (E)

33.7 (44) 7.3 (52) 5.8 (56) 19.2 (42) 39.2 (56)

49.6 (35) 21.7 (38) 23.1 (40) 29.0 (38) 64.7 (29)

69.5 (25) 38.2 (42) 68.3 (27) 38.8 (21) 73.2 (31)

57.7 (30) 32.3 (44) 52.5 (38) 46.8 (24) 77.8 (33)

BAV: bicuspid aortic valve; TAV: tricuspid aortic valve.

apices, accelerates into branches, then slows again distally, creating high WSS magnitude near aneurysm sac. Furthermore, a high WSS combined with a positive WSS gradient along the longitudinal aorta might be more important than the WSS alone. Endothelial dysfunction under high WSS in conjunction with positive WSS gradient conditions has been highlighted in the initiation of an aneurysm in a rabbit model.30 In our study, plane-wise analysis of ATAAs revealed effectively a positive WSS gradient from the aortic root to the distal ascending aorta, which varies between ATAA groups (i.e. BAV vs TAV). Furthermore, BAV ATAAs and TAV ATAAs with severe aortic stenosis and regurgitation appeared to show a slight deviation of WSSs toward the left side of ATAA wall (see plane 4 of patients (A) and (E) in Figure 7). Interestingly, we observed that focally elevated WSSs at the outer ATAA curvature are well associated to regions of low OSI, suggesting an inverse relationship between these wall shear parameters. This remarkable condition (i.e. low WSS and high OSI) was correlated to the development of atherosclerosis or ulcerating lesions in the thoracic aorta as shown by several studies.19,31,32 Therefore, we suggest that abnormal flow patterns in ATAAs induce elevated and locally varying WSS,

which may ultimately cause a mechanism of destructive vascular remodeling and promote aneurysm dilatation. This detrimental effect is further improved in hypertension for which systolic WSS may increase upon 44% at mid-ascending aneurysmal wall as simulated by our high blood pressure scenario (Table 3). Indeed, an increase in the systolic ejection is directly reflected on shear forces exerted by the accelerated fluid on the intimal surface of the aneurysmal wall. Experimental testing on tissue specimens can disclose whether altered WSS distribution affects the biomechanical strength of the aneurysmal wall. Iliopoulos et al.33 investigated the regional and directional variations of mechanical properties in freshly excised ATAA tissue specimens using tensile testing. Although uniform ATAA tissue strength occurred circumferentially, specimens extracted longitudinally from the outer aneurysmal wall were weaker and stiffer than those from posterior and lateral sides. This can be caused by the altered WSS and OSI distributions as suggested in this study. Similar to any other computational study, our work made several simplifications and assumptions. The motion of aortic-valve leaflets over cardiac cycle was not simulated. Similarly, the aortic wall dynamics, which are highly dependent on the elasticity of the aortic wall, was not considered. The elastic ATAA wall and valve leaflets experience rapid deformation, and this likely changes aneurysm hemodynamic over cardiac cycle. Although the effect of the aortic wall dynamic can be considered of secondary order,34 flow changes induced by valve motion may be prominent for cardiac phases different from which ATAA models were reconstructed in our simulations. This study made this assumption of rigid valve leaflets since the incorporation of valve dynamics poses technical challenges in simulating spatial and temporal deformation. Indeed, the motion of the aortic valve can be simulated by fluid-structure iteration finite element analysis. As compared to our tetrahedral-based mesh, prismatic elements near the aortic wall are recommended to improve the accuracy of shear parameters as suggested by Wang et al.35 Indeed, the fine-grid convergence index of our tetrahedral-based mesh was GCI21 fine = 11:5%, and this likely determines an error on WSS prediction. Another assumption would be non-patient-specific boundary conditions even though outflows were based on in-vivo measurements of flow splits between the supra-aortic vessels and descending aorta. This aspect could be overcome using flow data from MRI.25,26 The data presented here are based on observations in a restricted group of ATAA patients; therefore, our hypothesis needs to be addressed on a larger cohort of patients.

Conclusion We conclude that BAV ATAAs experience distinct, altered hemodynamic characterized by accelerated


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Figure 7. Distribution of systolic WSS (N/m2) at four analysis planes along the ATAA circumference for patients with BAV (top two models) and TAV (bottom three models). Positions of analysis planes are shown in the scheme at top and standardized to ensure comparability. BAV ATAA: bicuspid aortic valve ascending thoracic aortic aneurysm; TAV ATAA: tricuspid aortic valve ascending thoracic aortic aneurysm; Out: outer curvature, InC: inner curvature, L: left side of aortic wall, R: right side of aortic wall.

peripheral flow at aneurysm wall with formation of helical flow at aortic center. The study of wall shear parameters revealed an elevated and locally varying

WSS at the outer aneurysmal wall with the lateral regions undergoing a marked flow deflection (i.e. high OSI values). Therefore, CFD-based WSS and OSI


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Figure 8. Distribution of OSI at four analysis planes along the ATAA circumference for patients with BAV (top two models) and TAV (bottom three models). Positions of analysis planes are shown in the scheme at the top and standardized to ensure comparability. BAV ATAA: bicuspid aortic valve ascending thoracic aortic aneurysm; TAV ATAA: tricuspid aortic valve ascending thoracic aortic aneurysm; Out: outer curvature, InC: inner curvature, L: left side of aortic wall, R: right side of aortic wall.

estimations presented here provide valuable biomarkers for the description of the hemodynamic in ATAAs and

could be used someday to identify patients at high risk for aneurysm development.


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Acknowledgements Mr Rinaudo thanks the Italian Ministry of Education, University and Research for supporting his research. Declaration of conflicting interests The authors declare that there is no conflict of interest. Funding This study was funded by a grant from Fondazione Ri.MED provided to Dr Pasta. References 1. Ince H and Nienaber CA. Etiology, pathogenesis and management of thoracic aortic aneurysm. Nat Clin Pract Cardiovasc Med 2007; 4: 418–427. 2. Davies RR, Goldstein LJ, Coady MA, et al. Yearly rupture or dissection rates for thoracic aortic aneurysms: simple prediction based on size. Ann Thorac Surg 2002; 73: 17–28. 3. Cripe L, Andelfinger G, Martin LJ, et al. Bicuspid aortic valve is heritable. J Am Coll Cardiol 2004; 44: 138–143. 4. Juvonen T, Ergin MA, Galla JD, et al. Risk factors for rupture of chronic type B dissections. J Thorac Cardiovasc Surg 1999; 117: 776–786. 5. Markl M, Kilner PJ and Ebbers T. Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2011; 13: 7. 6. Den Reijer PM, Sallee D 3rd, van der Velden P, et al. Hemodynamic predictors of aortic dilatation in bicuspid aortic valve by velocity-encoded cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2010; 12: 4. 7. Weigang E, Kari FA, Beyersdorf F, et al. Flow-sensitive four-dimensional magnetic resonance imaging: flow patterns in ascending aortic aneurysms. Eur J Cardiothorac Surg 2008; 34: 11–16. 8. Hope MD, Hope TA, Crook SE, et al. 4D flow CMR in assessment of valve-related ascending aortic disease. JACC Cardiovasc Imaging 2011; 4: 781–787. 9. Hope MD, Hope TA, Meadows AK, et al. Bicuspid aortic valve: four-dimensional MR evaluation of ascending aortic systolic flow patterns. Radiology 2010; 255: 53–61. 10. Shaaban AM and Duerinckx AJ. Wall shear stress and early atherosclerosis: a review. AJR Am J Roentgenol 2000; 174: 1657–1665. 11. Sakamoto N, Saito N, Han X, et al. Effect of spatial gradient in fluid shear stress on morphological changes in endothelial cells in response to flow. Biochem Biophys Res Commun 2010; 395: 264–269. 12. Pasta S, Rinaudo A, Luca A, et al. Difference in hemodynamic and wall stress of ascending thoracic aortic aneurysms with bicuspid and tricuspid aortic valve. J Biomech 2013; 46: 1729–1738. 13. Rinaudo A, D’Ancona G, Baglini R, et al. Computational fluid dynamics simulation to evaluate aortic coarctation gradient with contrast-enhanced CT. Comput Method Biomech 2014; 1–6. 14. Celik IB, Ghia U, Roache PJ, et al. Procedure for estimation and reporting of uncertainty due to discretization in CFD applications. J Fluid Eng: T ASME 2008; 130: 1–4.

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Identification of vessel wall degradation in ascending thoracic aortic aneurysms with OCT.

Constitutive modeling of ascending thoracic aortic aneurysms using microstructural parameters.

Ascending thoracic aortic aneurysms protect against myocardial infarctions.

Patient specific stress and rupture analysis of ascending thoracic aneurysms.

Proximal stenosis may induce initiation of cerebral aneurysms by increasing wall shear stress and wall shear stress gradient.

Familial thoracic aortic aneurysms.

Biomechanical evaluation of ascending aortic aneurysms.

inhibitors expression in female ascending thoracic aortic aneurysms.

Metabolomic profiling of ascending thoracic aortic aneurysms and dissections - Implications for pathophysiology and biomarker discovery.

Coronary artery aneurysms associated with ascending aortic aneurysms and abdominal aortic aneurysms: pathophysiologic implications.

Hybrid thoracic endovascular aortic repair of ascending aortic pseudoaneurysm.

Optical coherence tomography assessment of vessel wall degradation in thoracic aortic aneurysms.

Natural history of arteriosclerotic thoracic aortic aneurysms.

Retrograde ascending aortic dissection after thoracic endovascular aortic repair.

Dispersive aortic cannulas reduce aortic wall shear stress affecting atherosclerotic plaque embolization.

Regional variation exists in patient selection and treatment of abdominal aortic aneurysms.

MMP-2 Isoforms in Aortic Tissue and Serum of Patients with Ascending Aortic Aneurysms and Aortic Root Aneurysms.

Asymmetric Dimethylarginine in Patients with Ascending Aortic Aneurysms.

[Aneurysms of the ascending aorta and aortic arch].

Variation in maximum diameter measurements of descending thoracic aortic aneurysms using unformatted planes versus images corrected to aortic centerline.

Measurements of wall shear stress and aortic pulse wave velocity in swine with familial hypercholesterolemia.

Comparative assessment of ascending aortic aneurysms in Marfan patients using ECG-gated computerized tomographic angiography versus trans-thoracic echocardiography.

Commentary: Hybrid Repair for Ascending Aortic Dissections and Aneurysms.

Bicuspid aortic valves and thoracic aortic aneurysms in patients with intracranial aneurysms.