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Background In patients with bicuspid valve (BAV), ascending aorta (AAo) dilatation may be caused by altered flow patterns and wall shear stress (WSS). These differences may explain different aortic dilatation morphotypes. Using 4D-flow cardiovascular magnetic resonance (CMR), we aimed to analyze differences in flow patterns and regional axial and circumferential WSS maps between BAV phenotypes and their correlation with ascending aorta dilatation morphotype. Methods One hundred and one BAV patients (aortic diameter ≤ 45 mm, no severe valvular disease) and 20 healthy subjects were studied by 4D-flow CMR. Peak velocity, flow jet angle, flow displacement, in-plane rotational flow (IRF) and systolic flow reversal ratio (SFRR) were assessed at different levels of the AAo. Peak-systolic axial and circumferential regional WSS maps were also estimated. Unadjusted and multivariable adjusted linear regression analyses were used to identify independent correlates of aortic root or ascending dilatation. Age, sex, valve morphotype, body surface area, flow derived variables and WSS components were included in the multivariable models. Results The AAo was non-dilated in 24 BAV patients and dilated in 77 (root morphotype in 11 and ascending in 66). BAV phenotype was right-left (RL-) in 78 patients and right-non-coronary (RN-) in 23. Both BAV phenotypes presented different outflow jet direction and velocity profiles that matched the location of maximum systolic axial WSS. RL-BAV velocity profiles and maximum axial WSS were homogeneously distributed right-anteriorly, however, RN-BAV showed higher variable profiles with a main proximal-posterior distribution shifting anteriorly at mid-distal AAo. Compared to controls, BAV patients presented similar WSS magnitude at proximal, mid and distal AAo ( p  = 0.764, 0.516 and 0.053, respectively) but lower axial and higher circumferential WSS components ( p  < 0.001 for both, at all aortic levels). Among BAV patients, RN-BAV presented higher IRF at all levels ( p  = 0.024 proximal, 0.046 mid and 0.002 distal AAo) and higher circumferential WSS at mid and distal AAo ( p  = 0.038 and 0.046, respectively) than RL-BAV. However, axial WSS was higher in RL-BAV compared to RN-BAV at proximal and mid AAo ( p  = 0.046, 0.019, respectively). Displacement and axial WSS were independently associated with the root-morphotype, and circumferential WSS and SFRR with the ascending-morphotype. Conclusions Different BAV-phenotypes present different flow patterns with an anterior distribution in RL-BAV, whereas, RN-BAV patients present a predominant posterior outflow jet at the sinotubular junction that shifts to anterior or right anterior in mid and distal AAo. Thus, RL-BAV patients present a higher axial WSS at the aortic root while RN-BAV present a higher circumferential WSS in mid and distal AAo. These results may explain different AAo dilatation morphotypes in the BAV population.

Blood flow dynamics make it possible to better understand the development of aortopathy and cardiovascular events in patients with Marfan syndrome (MFS). Aortic 3D blood flow characteristics were investigated in relation to aortic geometry in children and adolescents with MFS. Twenty-five MFS patients (age 15.6 ± 4.0 years; 11 females) and 21 healthy controls (age 16.0 ± 2.6 years; 12 females) underwent magnetic resonance angiography and 4D flow CMR for assessment of thoracic aortic size and 3D blood flow velocities. Data analysis included calculation of aortic diameter and BSA-indexed aortic dimensions (Z-score) along the thoracic aorta, 3D mean systolic wall shear stress (WSSmean) in ten aortic segments and assessment of aortic blood flow patterns. Aortic root (root), ascending (AAo) and descending (DAo) aortic size was significantly larger in MFS patients than healthy controls (Root Z-score: 3.56 ± 1.45 vs 0.49 ± 0.78, p < 0.001; AAo Z-score 0.21 ± 0.95 vs −0.54 ± 0.64, p = 0.004; proximal DAo Z-score 2.02 ± 1.60 vs 0.56 ± 0.66, p < 0.001). A regional variation in prevalence and severity of flow patterns (vortex and helix flow patterns) was observed, with the aortic root and the proximal DAo (pDAo) being more frequently affected in MFS. MFS patients had significantly reduced WSSmean in the proximal AAo (pAAo) outer segment (0.65 ± 0.12 vs. 0.73 ± 0.14 Pa, p = 0.029) and pDAo inner segment (0.74 ± 0.17 vs. 0.87 ± 0.21 Pa, p = 0.021), as well as higher WSSmean in the inner segment of the distal AAo (0.94 ± 0.14 vs. 0.84 ± 0.15 Pa, p = 0.036) compared to healthy subjects. An inverse relationship existed between pDAo WSSmean and both pDAo diameter (R = −0.53, p < 0.001) and % diameter change along the pDAo segment (R = −0.64, p < 0.001). MFS children and young adults have altered aortic flow patterns and differences in aortic WSS that were most pronounced in the pAAo and pDAo, segments where aortic dissection or rupture often originate. The presence of vortex flow patterns and abnormal WSS correlated with regional size of the pDAo and are potentially valuable additional markers of disease severity.

Cardiovascular diseases represent one of the leading causes of mortality worldwide, underscoring the need for accurate simulations of blood flow to improve diagnosis and treatment. This study examines blood flow dynamics in two different vascular structures—the aorta and the right coronary artery (RCA)—using Computational Fluid Dynamics (CFD). Utilizing COMSOL Multiphysics®, various mathematical models were applied to simulate blood flow under physiological conditions, assuming a steady-flow regime. These models include both Newtonian and non-Newtonian approaches, such as the Carreau and Casson models, as well as viscoelastic frameworks like Oldroyd-B, Giesekus, and FENE-P. Key metrics—such as velocity fields, pressure distributions, and error analysis—were evaluated to determine which model most accurately describes hemodynamic behavior in large vessels like the aorta and in smaller and more complex vessels like the RCA. The results highlight the importance of shear-thinning and viscoelastic properties in small vessels like the RCA, which contrasts with the predominantly Newtonian behavior observed in the aorta. While computational challenges remain, this study contributes to a deeper understanding of blood rheology, enhancing the accuracy of cardiovascular simulations and offering valuable insights for diagnosing and managing vascular diseases.

(1) Background: The realization of appropriate aortic replicas for in vitro experiments requires a suitable choice of both the material and geometry. The matching between the grade of details of the geometry and the mechanical response of the materials is an open issue that deserves attention. (2) Methods: To explore this issue, we performed a series of Fluid–Structure Interaction simulations, which compared the dynamics of three aortic models. Specifically, we reproduced a patient-specific geometry with a wall of biological tissue or silicone, and a parametric geometry based on in vivo data made in silicone. The biological tissue and the silicone were modeled with a fiber-oriented anisotropic and isotropic hyperelastic model, respectively. (3) Results: Clearly, both the aorta’s geometry and its constitutive material contribute to the determination of the aortic arch deformation; specifically, the parametric aorta exhibits a strain field similar to the patient-specific model with biological tissue. On the contrary, the local geometry affects the flow velocity distribution quite a lot, although it plays a minor role in the helicity along the arch. (4) Conclusions: The use of a patient-specific prototype in silicone does not a priori ensure a satisfactory reproducibility of the real aorta dynamics. Furthermore, the present simulations suggest that the realization of a simplified replica with the same compliance of the real aorta is able to mimic the overall behavior of the vessel.

Analysis of the data of morphometry of aortic casts, aortography at different pressures, and multispiral computer tomography of the aorta with contrast and normal pulse pressure showed that geometric configuration of the flow channel of the aorta during the whole cardiac cycle corresponded to the conditions of self-organization of tornado-like quasipotential flow described by exact solutions of the Navier—Stokes equation and continuity of viscous fluid typical for this type of fluid flows. Increasing pressure in the aorta leads to a decrease in the degree of approximation of the channel geometry to the ratio of exact solution and increases the risk of distortions in the structure of the flow. A mechanism of evolution of tornado-like flow in the aorta was proposed.

BACKGROUND Experimental and clinical data suggest that statins exert anti-inflammatory and antiproliferative actions on vasculature beyond their lipid-lowering properties. Whether these pleiotropic effects of statins translate into a beneficial effect on arterial stiffness is not clear. This study aimed to evaluate the potential effects of low-dose atorvastatin treatment on arterial stiffness and central arterial pressure waveforms in patients with mild hypertension and hypercholesterolemia. METHODS In a double-blind, randomized, placebo-controlled fashion, 50 hypertensive and hypercholesterolemic patients were allocated to receive 10mg of atorvastatin or placebo for 26 weeks. Arterial stiffness was assessed by aortic pulse-wave velocity (PWV) using a Sphygmocor device. Central arterial pressure waveform parameters were estimated by radial artery applanation tonometry. Heart rate-adjusted augmentation index (AIx(75)) was used as measure of wave reflections. RESULTS At study end, aortic PWV (9.0±1.5 vs. 10.9±2.6 m/sec; P<0.001) and AIx(75) (24.9% ± 9.7% vs 28.8% ± 11.8%; P < 0.001) were significantly lower in the atorvastatin group than that placebo group. Furthermore, decreases in central aortic systolic blood pressure and pulse pressure were evident at study-end with atorvastatin but not with placebo (130±8 vs. 138±6mm Hg, P < 0.001; 48±7 vs. 53±6mm Hg, P < 0.05, respectively). Atorvastatin-induced reductions in aortic PWV during follow-up showed significant associations with changes in AIx(75) and central aortic systolic blood pressure and pulse pressure. CONCLUSIONS This study shows that low-dose atorvastatin treatment improves arterial stiffness and exerts a reduction on central aortic pressures. These effects may represent a potential mechanism of cardiovascular risk reduction observed with statin use. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov Database Identifier Number: NCT01126684

In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.

We introduce a new computational framework that utilises Pulse Wave Velocity (PWV) extracted directly from 4D flow MRI (4DMRI) to inform patient-specific compliant computational fluid dynamics (CFD) simulations of a Type-B aortic dissection (TBAD), post-thoracic endovascular aortic repair (TEVAR). The thoracic aortic geometry, a 3D inlet velocity profile (IVP) and dynamic outlet boundary conditions are derived from 4DMRI and brachial pressure patient data. A moving boundary method (MBM) is applied to simulate aortic wall displacement. The aortic wall stiffness is estimated through two methods: one relying on area-based distensibility and the other utilising regional pulse wave velocity (RPWV) distensibility, further fine-tuned to align with in vivo values. Predicted pressures and outlet flow rates were within 2.3 % of target values. RPWV-based simulations were more accurate in replicating in vivo hemodynamics than the area-based ones. RPWVs were closely predicted in most regions, except the endograft. Systolic flow reversal ratios (SFRR) were accurately captured, while differences above 60 % in in-plane rotational flow (IRF) between the simulations were observed. Significant disparities in predicted wall shear stress (WSS)-based indices were observed between the two approaches, especially the endothelial cell activation potential (ECAP). At the isthmus, the RPWV-driven simulation indicated a mean ECAP>1.4 Pa-1 (critical threshold), indicating areas potentially prone to thrombosis, not captured by the area-based simulation. RPWV-driven simulation results agree well with 4DMRI measurements, validating the proposed pipeline and facilitating a comprehensive assessment of surgical decision-making scenarios and potential complications, such as thrombosis and aortic growth.

This study conducts hemodynamic simulations for a total of 20 patients with Type B aortic intramural hematoma (TBIMH) and aims to develop hemodynamic criteria for possible development of intimal tear and indicator for tearing location. The patients are divided into Group A without intimal tear and Group B with progression into tear. The mean oscillatory shear index OSI¯ is calculated based on the wall shear stress (WSS¯) distribution. The blood pressure drop along the main aortic vessel is calculated and the high pressure drop time fraction over one cardiac cycle Td/T is determined, with high pressure drop being defined as the pressure drop larger than half the maximal value. By combining OSI¯ and Td/T at low heart rates 60bpm and 75bpm, we reveal statistically significant correlation between no progression to tear and both low OSI¯<0.121 and low Td/T<0.067, with a pvalue of p=8.7e−5. We also propose a new parameter, namely the magnitude of tangential pressure gradient at aortic wall |∇τp| at the time when the pressure drop is maximal during one cardiac cycle. Comparison with CT imaging reveals that nine out of ten patients in Group B develop intimal tear at the location with elevated |∇τp|. Therefore, the current study provides a two-step procedure for the hemodynamic diagnosis of TBIMH. First, by combining OSI¯ and Td/T those patients with low risk of intimal tear can be excluded. Then, the location of elevated |∇τp| can be adopted as the indicator for possible intimal tear locations.

Noninvasive measurement of the central aortic blood pressure has become an important technique that has generated a lot of interest around the medicine industry because it can estimate the central aortic blood pressure waveform without inserting a pressure-sensing catheter into the ascending aorta. The accuracy of noninvasive estimation of aortic hemodynamics and cardiac contractility is still debatable in noninvasive measurement of the central aortic blood methods. The objective of this project is to investigate the transfer functions available for converting radial blood pressure waveforms to central aortic blood pressure waveforms. In this project, three different transfer functions will be investigated which are The Generalized Transfer Function, N-Point Moving Average and Adaptive Transfer Function in order to recommend the effective method in terms of accuracy. The study methodology will be conducted through the software MATLAB R2021b. The investigation of these three methods will be conducted with data collected from virtual subjects from the HaeMod database. The Generalized transfer function, N-Point Moving Average and Adaptive Transfer Function will be coded, evaluated, and analyzed as part of the methodology. The determination of the most effective method among the three transfer functions will be attributed according to output comparison of Systolic peak differences, the RMSE and the MAPE between the estimated central aortic blood pressure and the measured central aortic blood pressure.