Comprehensive In Vitro Study of the Flow Past Two Transcatheter Aortic Valves: Comparison with a Severe Stenotic Case

Pathophysiology of the ascending aorta: Impact of dilation and valve phenotype on large-scale blood flow coherence detected by 4D flow MRI

BACKGROUND AND OBJECTIVE

The evidence on the role of hemodynamics in aorta pathophysiology has yet to be robustly translated into clinical applications, to improve risk stratification of aortic diseases. Motivated by the need to enrich the current understanding of the pathophysiology of the ascending aorta (AAo), this study evaluates in vivo how large-scale aortic flow coherence is affected by AAo dilation and aortic valve phenotype.

METHODS

A complex networks-based approach is applied to 4D flow MRI data to quantify subject-specific AAo flow coherence in terms of correlation between axial velocity waveforms and the aortic flow rate waveform along the cardiac cycle. The anatomical length of persistence of such correlation is quantified using the recently proposed network metric average weighted curvilinear distance (AWCD). The analysis considers 107 subjects selected to allow an ample stratification in terms of aortic valve morphology, absence/presence of AAo dilation and of aortic valve stenosis.

RESULTS

The analysis highlights that the presence of AAo dilation as well as of bicuspid aortic valve phenotype breaks the physiological AAo flow coherence, quantified in terms of AWCD. Of notice, it emerges that cycle-average blood flow rate and relative AAo dilation are main determinants of AWCD, playing opposite roles in promoting and hampering the persistence of large-scale flow coherence in AAo, respectively.

CONCLUSIONS

The findings of this study can contribute to broaden the current mechanistic link between large-scale blood flow coherence and aortic pathophysiology, with the prospect of enriching the existing tools for the in vivo non-invasive hemodynamic risk assessment for aortic diseases onset and progression.

On the role of aortic valve architecture for physiological hemodynamics and valve replacement, Part I: Flow configuration and vortex dynamics

Aortic valve replacement has become an increasing concern due to the rising prevalence of aortic stenosis in an ageing population. Existing replacement options have limitations, necessitating the development of improved prosthetic aortic valves. In this study, flow characteristics during systole in a stenotic aortic valve case are compared with those downstream of two newly designed surgical bioprosthetic aortic valves (BioAVs). To do so, advanced three-dimensional fluid-structure interaction simulations are conducted and dedicated analysis methods to investigate jet flow configuration and vortex dynamics are developed. Our findings reveal that the stenotic case maintains a high jet flow eccentricity due to a fixed orifice geometry, resulting in flow separation and increased vortex stretching and tilting in the commissural low-flow regions. One BioAV design introduces non-axisymmetric leaflet motion, which reduces the maximum jet velocity and forms more vortical structures. The other BioAV design produces a fixed symmetric triangular jet shape due to non-moving leaflets and exhibits favourable vorticity attenuation, revealed by negative temporally and spatially averaged projected vortex stretching values, and significantly reduced drag. Therefore, this study highlights the benefits of custom-designed aortic valves in the context of their replacement through comprehensive and novel flow analyses. The results emphasise the importance of analysing jet flow, vortical structures, momentum balance and vorticity transport for thoroughly evaluating aortic valve performance.

On the role of aortic valve architecture for physiological hemodynamics and valve replacement, Part II: Spectral analysis and anisotropy

Severe aortic valve stenosis can lead to heart failure and aortic valve replacement (AVR) is the primary treatment. However, increasing prevalence of aortic stenosis cases reveal limitations in current replacement options, necessitating improved prosthetic aortic valves. We investigate flow disturbances downstream of severe aortic stenosis and two bioprosthetic aortic valve (BioAV) designs using advanced energy-based analyses. Three-dimensional high-fidelity fluid-structure interaction simulations have been conducted and a dedicated and novel spectral analysis has been developed to characterise the kinetic energy (KE) carried by eddies in the wavenumber space. In addition, new field quantities, i.e. modal KE anisotropy intensity as well as normalised helicity intensity, are introduced. Spectral analysis shows kinetic energy (KE) decay variations, with the stenotic case aligning with Kolmogorov's theory, while BioAV cases differing. We explore the impact of flow helicity on KE transfer and decay in BioAVs. Probability distributions of modal KE anisotropy unveil flow asymmetries in the stenotic and one BioAV cases. Moreover, an inverse correlation between temporally averaged modal KE anisotropy and normalised instantaneous helicity intensity is noted, with the coefficient of determination varying among the valve configurations. Leaflet dynamics analysis highlights a stronger correlation between flow and biomechanical KE anisotropy in one BioAV due to higher leaflet displacement magnitude. These findings emphasise the role of valve architecture in aortic turbulence as well as its importance for BioAV performance and energy-based design enhancement.

In vitro investigation of the blood flow downstream of a 3D-printed aortic valve

The hemodynamics in the aorta as well as the durability of aortic valve prostheses vary greatly between different types of devices. Although placement and sizing of surgical aortic valve prostheses are excellent, the valve geometry of common devices cannot be customized to fit the patient's anatomy perfectly. Similarly, transcatheter aortic valve implantation (TAVI) devices are not customizable and may be orientated unfavorably during implantation. Imperfect fit of an aortic valve prosthesis may result in suboptimal performance and in some cases the need for additional surgery. Leveraging the advent of precision, multi-material 3D-printing, a bioinspired silicone aortic valve was developed. The manufacturing technique makes it fully customizable and significantly cheaper to develop and produce than common prostheses. In this study, we assess the hemodynamic performance of such a 3D-printed aortic valve and compare it to two TAVI devices as well as to a severely stenosed valve. We investigate the blood flow distal to the valve in an anatomically accurate, compliant aorta model via three-dimensional particle tracking velocimetry measurements. Our results demonstrate that the 3D-printed aortic valve induces flow patterns and topology compatible with the TAVI valves and showing similarity to healthy aortic blood flow. Compared to the stenosis, the 3D-printed aortic valve reduces turbulent kinetic energy levels and irreversible energy losses by over 75%, reaching values compatible with healthy subjects and conventional TAVIs. Our study substantiates that the 3D-printed heart valve displays a hemodynamic performance similar to established devices and underscores its potential for driving innovation towards patient specific valve prostheses.

An In-Vitro Study of the Flow Past a Transcatheter Aortic Valve Using Time-Resolved 3D Particle Tracking

The performance of a transcatheter aortic valve (TAV) can be evaluated by analyzing the flow field downstream of the valve. However, three dimensional flow and pressure fields, and particle residence time, a quantity closely related to thrombosis risk, are challenging to obtain. This experimental study aims to provide a comprehensive 3D measurement of the flow field downstream of an Edwards SAPIEN 3 using time-resolved 3D particle tracking velocimetry (3D PTV) with Shake-the-Box (STB) algorithm. The valve was deployed in an idealized aorta model and tested in a left heart simulator under physiological conditions. Detailed 3D vortical structures, pressure distributions, and particle residence time were obtained by analyzing the 3D particle tracks. Results have shown large-scale retrograde flow entering the sinuses of the TAV at systole, reducing flow stasis there. However, the 3D particle tracks reveal that the retrograde flow has a high residence time and might have already experienced high shear stress near the main jet. Thus by only focusing on the flow in the sinus region is not sufficient to evaluate the leaflet thrombosis risk, and the flow downstream of the valve should be taken into consideration. The unique perspectives offered by 3D PTV are important when evaluating the performance of the TAVs.

Toward an accurate estimation of wall shear stress from 4D flow magnetic resonance downstream of a severe stenosis

PURPOSE

First, to investigate the agreement between velocity, velocity gradient, and Reynolds stress obtained from four-dimensional flow magnetic resonance (4D flow MRI) measurements and direct numerical simulation (DNS). Second, to propose and optimize based on DNS, 2 alternative methods for the accurate estimation of wall shear stress (WSS) when the resolution of the flow measurements is limited. Thirdly, to validate the 2 methods based on 4D flow MRI data.

METHODS

In vitro 4D MRI has been conducted in a realistic rigid stenosed aorta model under a constant flow rate of 12 L/min. A DNS of transitional stenotic flow has been performed using the same geometry and boundary conditions.

RESULTS

Time-averaged velocity and Reynolds stresses are in good agreement between in vitro 4D MRI data and DNS (errors between 2% and 8% of the reference downsampled data). WSS estimation based on the 2 proposed methods applied to MRI data provide good agreement with DNS for slice-averaged values (maximum error is less than 15% of the mean reference WSS for the first method and 25% for the second method). The performance of both models is not strongly sensitive to spatial resolution up to 1.5 mm voxel size. While the performance of model 1 deteriorates appreciably at low signal-to-noise ratios, model 2 remains robust.

CONCLUSIONS

The 2 methods for WSS magnitude give an overall better agreement than the standard approach used in the literature based on direct calculation of the velocity gradient close to the wall (relative error of 84%).

A Novel Estimation Approach of Pressure Gradient and Haemodynamic Stresses as Indicators of Pathological Aortic Flow Using Subvoxel Modelling

OBJECTIVE

The flow downstream from aortic stenoses is characterised by the onset of shear-induced turbulence that leads to irreversible pressure losses. These extra losses represent an increased resistance that impacts cardiac efficiency. A novel approach is suggested in this study to accurately evaluate the pressure gradient profile along the aorta centreline using modelling of haemodynamic stress at scales that are smaller than the typical resolution achieved in experiments.

METHODS

We use benchmark data obtained from direct numerical simulation (DNS) along with results from in silico and in vitro three-dimensional particle tracking velocimetry (3D-PTV) at three voxel sizes, namely 750  μm, 1 mm and 1.5 mm. A differential equation is derived for the pressure gradient, and the subvoxel-scale (SVS) stresses are closed using the Smagorinsky and a new refined model. Model constants are optimised using DNS and in silico PTV data and validated based on pulsatile in vitro 3D-PTV data and pressure catheter measurements.

RESULTS

The Smagorinsky-based model was found to be more accurate for SVS stress estimation but also more sensitive to errors especially at lower resolution, whereas the new model was found to more accurately estimate the projected pressure gradient even for larger voxel size of 1.5 mm albeit at the cost of increased sensitivity at this voxel size. A comparison with other methods in the literature shows that the new approach applied to in vitro PTV measurements estimates the irreversible pressure drop by decreasing the errors by at least 20%.

CONCLUSION

Our novel approach based on the modelling of subvoxel stress offers a validated and more accurate way to estimate pressure gradient, irreversible pressure loss and SVS stress.

SIGNIFICANCE

We anticipate that the approach may potentially be applied to image-based in vivo, in vitro 4D flow data or in silico data with limited spatial resolution to assess pressure loss and SVS stresses in disturbed aortic blood flow.