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In order for computational fluid dynamics to provide quantitative parameters to aid in the clinical assessment of type B aortic dissection, the results must accurately mimic the hemodynamic environment within the aorta. The choice of inlet velocity profile (IVP) therefore is crucial; however, idealised profiles are often adopted, and the effect of IVP on hemodynamics in a dissected aorta is unclear. This study examined two scenarios with respect to the influence of IVP—using (a) patient-specific data in the form of a three-directional (3D), through-plane (TP) or flat IVP; and (b) non-patient-specific flow waveform. The results obtained from nine simulations using patient-specific data showed that all forms of IVP were able to reproduce global flow patterns as observed with 4D flow magnetic resonance imaging. Differences in maximum velocity and time-averaged wall shear stress near the primary entry tear were up to 3% and 6%, respectively, while pressure differences across the true and false lumen differed by up to 6%. More notable variations were found in regions of low wall shear stress when the primary entry tear was close to the left subclavian artery. The results obtained with non-patient-specific waveforms were markedly different. Throughout the aorta, a 25% reduction in stroke volume resulted in up to 28% and 35% reduction in velocity and wall shear stress, respectively, while the shape of flow waveform had a profound influence on the predicted pressure. The results of this study suggest that 3D, TP and flat IVPs all yield reasonably similar velocity and time-averaged wall shear stress results, but TP IVPs should be used where possible for better prediction of pressure. In the absence of patient-specific velocity data, effort should be made to acquire patient’s stroke volume and adjust the applied IVP accordingly.

Severity of aortic coarctation (CoA) is currently assessed by estimating trans-coarctation pressure drops through cardiac catheterization or echocardiography. In principle, more detailed information could be obtained non-invasively based on space- and time-resolved magnetic resonance imaging (4D flow) data. Yet the limitations of this imaging technique require testing the accuracy of 4D flow-derived hemodynamic quantities against other methodologies. With the objective of assessing the feasibility and accuracy of this non-invasive method to support the clinical diagnosis of CoA, we developed an algorithm (4DF-FEPPE) to obtain relative pressure distributions from 4D flow data by solving the Poisson pressure equation. 4DF-FEPPE was tested against results from a patient-specific fluid-structure interaction (FSI) simulation, whose patient-specific boundary conditions were prescribed based on 4D flow data. Since numerical simulations provide noise-free pressure fields on fine spatial and temporal scales, our analysis allowed to assess the uncertainties related to 4D flow noise and limited resolution. 4DF-FEPPE and FSI results were compared on a series of cross-sections along the aorta. Bland-Altman analysis revealed very good agreement between the two methodologies in terms of instantaneous data at peak systole, end-diastole and time-averaged values: biases (means of differences) were +0.4 mmHg, −1.1 mmHg and +0.6 mmHg, respectively. Limits of agreement (2 SD) were ±0.978 mmHg, ±1.06 mmHg and ±1.97 mmHg, respectively. Peak-to-peak and maximum trans-coarctation pressure drops obtained with 4DF-FEPPE differed from FSI results by 0.75 mmHg and −1.34 mmHg respectively. The present study considers important validation aspects of non-invasive pressure difference estimation based on 4D flow MRI, showing the potential of this technology to be more broadly applied to the clinical practice.

Background: Blood flow patterns can alter material properties of ascending thoracic aortic aneurysms (ATAA) via vascular wall remodeling. This study examines the relationship between wall shear stress (WSS) obtained from image-based computational modelling with tissue-derived mechanical and microstructural properties of the ATAA wall using segmental analysis. Methods: Ten patients undergoing surgery for ATAA were recruited. Exclusions: bicuspid aortopathy, connective tissue disease. All patients had pre-operative 4-dimensional flow magnetic resonance imaging (4D-MRI), allowing for patient-specific computational fluid dynamics (CFD) analysis and anatomically precise WSS mapping of ATAA regions (6–12 segments per patient). ATAA samples were obtained from surgery and subjected to region-specific tensile and peel testing (matched to WSS segments). Computational pathology was used to characterize elastin/collagen abundance and smooth muscle cell (SMC) count. Results: Elevated values of WSS were predictive of: reduced wall thickness [coef −0.0489, 95% CI (−0.0905, −0.00727), p = 0.022] and dissection energy function (longitudinal) [−15,0, 95% CI (−33.00, −2.98), p = 0.048]. High WSS values also predicted higher ultimate tensile strength [coef 0.136, 95% CI (0 0.001, 0.270), p = 0.048]. Additionally, elevated WSS also predicted a reduction in elastin levels [coef −0.276, 95% (CI −0.531, −0.020), p = 0.035] and lower SMC count ([oef −6.19, 95% CI (−11.41, −0.98), p = 0.021]. WSS was found to have no effect on collagen abundance or circumferential mechanical properties. Conclusions: Our study suggests an association between elevated WSS values and aortic wall degradation in ATAA disease. Further studies might help identify threshold values to predict acute aortic events.

Background: Recent studies suggest that blood flow in main arteries is intrinsically disturbed, even under healthy conditions. Despite this, many computational fluid dynamics (CFD) analyses of aortic haemodynamics make the assumption of laminar flow, and best practices surrounding appropriate modelling choices are lacking. This study aims to address this gap by evaluating different modelling and post-processing approaches in simulations of a patient-specific aorta. Methods: Magnetic resonance imaging (MRI) and 4D flow MRI from a patient with aortic valve stenosis were used to reconstruct the aortic geometry and derive patient-specific inlet and outlet boundary conditions. Three different computational approaches were considered based on assumed laminar or assumed disturbed flow states including low-resolution laminar (LR-Laminar), high-resolution laminar (HR-Laminar) and large-eddy simulation (LES). Each simulation was ran for 30 cardiac cycles and post-processing was conducted on either the final cardiac cycle, or using a phase-averaged approach which utilised all 30 simulated cycles. Model capabilities were evaluated in terms of mean and turbulence-based parameters. Results: All simulation types, regardless of post-processing approach could correctly predict velocity values and flow patterns throughout the aorta. Lower resolution simulations could not accurately predict gradient-derived parameters including wall shear stress and viscous energy loss (largest differences up to 44.6% and 130.3%, respectively), although phase-averaging these parameters improved predictions. The HR-Laminar simulation produced more comparable results to LES with largest differences in wall shear stress and viscous energy loss parameters up to 5.1% and 11.6%, respectively. Laminar-based parameters were better estimated than turbulence-based parameters. Conclusion: Our findings suggest that well-resolved laminar simulations can accurately predict many laminar-based parameters in disturbed flows, but there is no clear benefit to running a HR-Laminar simulation over an LES simulation based on their comparable computational cost. Additionally, post-processing “typical” laminar simulation results with a phase-averaged approach is a simple and cost-effective way to improve accuracy of lower-resolution simulation results.

Objective: The interactions between aortic morphology and hemodynamics play a key role in determining type B aortic dissection (TBAD) progression and remodeling. The study aimed to provide qualitative and quantitative hemodynamic assessment in four different TBAD morphologies based on 4D flow MRI analysis. Materials and Methods: Four patients with different TBAD morphologies underwent CT and 4D flow MRI scans. Qualitative blood flow evaluation was performed by visualizing velocity streamlines and flow directionality near the tears. Quantitative analysis included flow rate, velocity and reverse flow index (RFI) measurements. Statistical analysis was performed to evaluate hemodynamic differences between the true lumen (TL) and false lumen (FL) of patients. Results: Qualitative analysis revealed blood flow splitting near the primary entry tears (PETs), often causing the formation of vortices in the FL. All patients exhibited clear hemodynamic differences between TL and FL, with the TL generally showing higher velocities and flow rates, and lower RFIs. Average velocity magnitude measurements were significantly different for Patient 1 ( t = 5.61, p = 0.001), Patient 2 ( t = 3.09, p = 0.02) and Patient 4 ( t = 2.81, p = 0.03). At follow-up, Patient three suffered from left renal ischemia because of FL collapse. This patient presented a complex morphology with two FLs and marked flow differences between TL and FLs. In Patient 4, left renal artery malperfusion was observed at the 32-months follow-up, due to FL thrombosis growing after PET repair. Conclusion: The study demonstrates the clinical feasibility of using 4D flow MRI in the context of TBAD. Detailed patient-specific hemodynamics assessment before treatment may provide useful insights to better understand this pathology in the future.

Bioprosthetic aortic valves (BPAV) have been increasingly used for surgical aortic valve replacement (SAVR), but long-term complications associated with structural valve deterioration remain a concern. The structural behaviour of the valve and its surrounding haemodynamics play a key role in the long-term outcome of SAVR, and these can be quantitively analysed by means of fluid-structure interaction (FSI) simulation. The aim of this study was to develop a fully coupled FSI model for patient-specific analysis of BPAV haemodynamics. Using the Edwards Magna Ease valve as an example, the workflow included reconstruction of the aortic root from CT images and the creation of valve geometric model based on available measurements made on the device. Two-way fully coupled FSI simulations were performed under patient-specific flow conditions derived from 4D flow magnetic resonance imaging (MRI), the latter also provided data for model validation. The simulation results were in good agreement with haemodynamic features extracted from 4D flow MRI and relevant data in the literature. Furthermore, the FSI model provided additional information that cannot be measured , including wall shear stress and its derivatives on the valve leaflets and in the aortic root. The FSI workflow presented in this study offers a promising tool for patient-specific assessment of aortic valve haemodynamics, and the results may help elucidate the role of haemodynamics in structural valve deterioration.

Background: Intracranial artery calcification detected on CT imaging is a recognized risk factor for ischemic cerebrovascular diseases, but the underlying etiology of this association remains unclear. Differences in objective morphometric characteristics of these calcifications may partially explain this association, yet these measurements are largely absent in the literature. We investigated intracranial artery calcification morphometry in patients with recent anterior ischemic stroke or TIA, assessing potential differences between calcifications in both intracranial carotid arteries (ICAs) located ipsilateral and contralateral to the cerebral ischemia. Methods: Among 100 patients (mean age 69.6 (SD 8.8) years) presenting to academic neurology departments, 3D reconstructions of both ICAs were based on clinical CT-angiography images. On these reconstructions, a luminal centerline and cross-sections perpendicular to this centerline were created, facilitating the assessment of calcification morphometry, spatial orientation and stenosis severity. Differences in calcification characteristics between ICAs were assessed using two-sided Wilcoxon signed-rank and χ2 tests. Results: Among 200 arteries, a median of four (IQR 2–6) individual calcifications were counted, with a mean area of 1.8 (IQR 1.2–2.7) mm2, a mean arc width of 43.5 (IQR 32.3–53.2) degrees, and median longitudinal extent of 15.4 (IQR 5.9–27.0) mm. Calcifications were most often present in the anatomical C4 section (56.0%), with predominantly posterosuperior orientation (38.5%) and 42.0% had a local stenosis severity > 70%. None of these aspects significantly differed between ICAs, and this remained after restricting analyses to patients with undetermined etiology. Conclusions: We found no differences in morphometrical or spatial aspects of calcifications between ICAs ipsilateral and contralateral to the cerebral ischemia.

End-to-side anastomoses are commonly utilised in peripheral arterial bypass surgery and are plagued by high rates of re-stenosis as a result of non-physiological blood flow impacting arterial and graft structures. Computational simulations can examine how patient-specific surgical decisions in bypass graft placement and material selection affect blood flow and future risk of graft restenosis. Despite graft geometry and compliance being key predictors of restenosis, current simulations do not consider the interaction of flowing blood with compliant vessel, graft, and suture structures. Utilising fluid-structure interaction simulations, this study examines the impact of surgical technique, such as anastomosis angle, graft material, and suture material, on blood flow and fluid-structure forces in patient-specific asymptomatic arterial tree versus side-to-end peripheral grafts for symptomatic atherosclerotic disease. To render these complex simulations numerically feasible, our pipeline uses regional suture mechanics and a pre-stress pipeline previously validated in small-scale idealised models. Our simulations found that higher anastomosis angles generate larger regions of slow and recirculating blood, characterised by non-physiologically low shear stress and high oscillatory shear index. The use of compliant graft materials reduces regions of non-physiologically high shear stress only when used in combination with compliant suture materials. Altogether, our fluid-structure interaction simulation provides patient-specific platforms for vascular surgery decisions concerning graft geometry and material.Competing Interest StatementDFF consults to the local Ansys distributors which gives him access to Ansys technical staff as needed. The remaining authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Big mechanically-active culture systems (BigMACS) are promising to stimulate, control, and pattern cell and tissue behaviours with less soluble factor requirements, however, it remains challenging to predict if and how distributed mechanical forces impact single-cell behaviours to pattern tissue. In this study, we introduce a centimetre, tissue-scale, finite element analysis (FEA) framework able to correlate sub-cellular quantitative histology with centimetre-scale biomechanics. Our framework is relevant to diverse bigMACS; media perfusion, tensile-stress, magnetic, and pneumatic tissue culture platforms. We apply our framework to understand how the design and operation of a multi-axial soft robotic bioreactor can spatially control mesenchymal stem cell (MSC) proliferation, orientation, differentiation to smooth muscle, and extracellular vascular matrix deposition. We find MSC proliferation and matrix deposition correlate positively with mechanical stimulation but cannot be locally patterned by soft robot mechanical stimulation within a centimetre scale tissue. In contrast, local stress distribution was able to locally pattern MSC orientation and differentiation to smooth muscle phenotypes, where MSCs aligned perpendicular to principal stress direction and expressed increased alpha-SMA with increasing 3D Von Mises Stresses from 0 to 15 kPa. Altogether, our new biomechanical-histological simulation framework is a promising technique to derive the future mechanical design equations to control cell behaviours and engineer patterned tissue generation.Competing Interest StatementThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. DFF consults to the local Ansys distributors which gives him access to Ansys technical staff as needed.

Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoracic aortic aneurysms (ATAA). To accurately reproduce hemodynamics, computational fluid dynamics (CFD) models must employ realistic inflow boundary conditions (BCs). However, the limited availability of in vivo velocity measurements still makes researchers resort to idealized BCs. In this study we generated and thoroughly characterized a large dataset of synthetic 4D aortic velocity profiles suitable to be used as BCs for CFD simulations. 4D flow MRI scans of 30 subjects with ATAA were processed to extract cross-sectional planes along the ascending aorta, ensuring spatial alignment among all planes and interpolating all velocity fields to a reference configuration. Velocity profiles of the clinical cohort were extensively characterized by computing flow morphology descriptors of both spatial and temporal features. By exploiting principal component analysis (PCA), a statistical shape model (SSM) of 4D aortic velocity profiles was built and a dataset of 437 synthetic cases with realistic properties was generated. Comparison between clinical and synthetic datasets showed that the synthetic data presented similar characteristics as the clinical population in terms of key morphological parameters. The average velocity profile qualitatively resembled a parabolic-shaped profile, but was quantitatively characterized by more complex flow patterns which an idealized profile would not replicate. Statistically significant correlations were found between PCA principal modes of variation and flow descriptors. We built a data-driven generative model of 4D aortic velocity profiles, suitable to be used in computational studies of blood flow. The proposed software system also allows to map any of the generated velocity profiles to the inlet plane of any virtual subject given its coordinate set.