Calcific degeneration is the most frequent type of heart valve failure, with rising incidence due to the ageing population. The gold standard treatment to date is valve replacement. Unfortunately, calcification oftentimes re-occurs in bioprosthetic substitutes, with the governing processes remaining poorly understood. Here, we present a multiscale, multimodal analysis of disturbances and extensive mineralisation of the collagen network in failed bioprosthetic bovine pericardium valve explants with full histoanatomical context. In addition to highly abundant mineralized collagen fibres and fibrils, calcified micron-sized particles previously discovered in native valves were also prevalent on the aortic as well as the ventricular surface of bioprosthetic valves. The two mineral types (fibres and particles) were detectable even in early-stage mineralisation, prior to any macroscopic calcification. Based on multiscale multimodal characterisation and high-fidelity simulations, we demonstrate that mineral occurrence coincides with regions exposed to high haemodynamic and biomechanical indicators. These insights obtained by multiscale analysis of failed bioprosthetic valves may serve as groundwork for the evidence-based development of more durable alternatives. STATEMENT OF SIGNIFICANCE: Bioprosthetic valve calcification is a well-known clinically significant phenomenon, leading to valve failure. The nanoanalytical characterisation of bioprosthetic valves gives insights into the highly abundant, extensive calcification and disorganization of the collagen network and the presence of calcium phosphate particles previously reported in native cardiovascular tissues. While the collagen matrix mineralisation can be primarily attributed to a combination of chemical and mechanical alterations, the calcified particles are likely of host cellular origin. This work presents a straightforward route to mineral identification and characterization at high resolution and sensitivity, and with full histoanatomical context, hence providing design cues for improved bioprosthetic valve alternatives.

Internal carotid artery (ICA) stenoses are a major source of stroke. In addition to traditional cardiovascular risk factors, hemodynamic parameters such as wall shear stress (WSS) are recognized as critical contributors to the progression and rupture of ICA plaques. This study evaluates the ability of 4D flow MRI to predict the velocity and WSS fields in three models of carotid bifurcations representing stenosis ratios of 0% (healthy), 40% (mildly stenosed), and 80% (severely stenosed) in the ICA. The stenosis ratio significantly impacts hemodynamics, increasing peak velocity, WSS, and flow disturbances. Compared to the healthy model, peak velocity rises by 38% in severe stenosis, generating a high-velocity jet and post-stenotic recirculation. Spatially averaged WSS increases by 21.5% in the mildly stenosed model and 99% in the severely stenosed model. Additionally, flow separation and vortex formation intensify as stenosis severity increases. A robust experimental setup with carotid bifurcation phantoms has been developed to eliminate the major sources of uncertainty in the boundary conditions. This enables a detailed quantitative comparison of 4D flow MRI measurements (obtained with a 7T scanner) against results from a CFD simulation. Moreover, the CFD results were validated against results obtained from Direct Numerical Simulations (DNS). Therefore, the CFD data could be used as a reliable high-fidelity reference for the flow within the carotid models. The comparison indicates that 4D flow MRI on a 7T scanner captures the major flow patterns with reasonable accuracy, though quantitative discrepancies increase with the stenosis ratio. Specifically, the peak velocity error rises from 6.1% in healthy arteries to 11.9% in severely stenosed arteries. Similarly, the error in spatially averaged WSS magnitude in the bifurcation region increases from 18% in healthy cases to 38% in severely stenosed cases. These findings underscore the need for validated approaches to accurately analyze complex flow patterns within carotid arteries, especially as even high-quality 4D flow MRI measurements using a 7T scanner with 0.5 mm resolution show diminishing accuracy in such challenging cases.

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.

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 $\mu$ m, 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.