Dataset Information

Effect of pannus formation on the prosthetic heart valve: In vitro demonstration using particle image velocimetry.

ABSTRACT: Although hemodynamic influence of the subprosthetic tissue, termed as pannus, may contribute to prosthetic aortic valve dysfunction, the relationship between pannus extent and hemodynamics in the prosthetic valve has rarely been reported. We investigated the fluid dynamics of pannus formation using in vitro experiments with particle image velocimetry. Subvalvular pannus formation caused substantial changes in prosthetic valve transvalvular peak velocity, transvalvular pressure gradient (TPG) and opening angle. Maximum flow velocity and corresponding TPG were mostly affected by pannus width. When the pannus width was 25% of the valve diameter, pannus formation elevated TPG to >2.5 times higher than that without pannus formation. Opening dysfunction was observed only for a pannus involvement angle of 360°. Although circumferential pannus with an involvement angle of 360° decreased the opening angle of the valve from approximately 82° to 58°, eccentric pannus with an involvement angle of 180° did not induce valve opening dysfunction. The pannus involvement angle largely influenced the velocity flow field at the aortic sinus and corresponding hemodynamic indices, including wall shear stress, principal shear stress and viscous energy loss distributions. Substantial discrepancy between the velocity-based TPG estimation and direct pressure measurements was observed for prosthetic valve flow with pannus formation.

SUBMITTER: Ha H

PROVIDER: S-EPMC6023143 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Effect of pannus formation on the prosthetic heart valve: In vitro demonstration using particle image velocimetry.

Ha Hojin H Koo Hyun Jung HJ Huh Hyung Kyu HK Kim Guk Bae GB Kweon Jihoon J Kim Namkug N Kim Young-Hak YH Kang Joon-Won JW Lim Tae-Hwan TH Song Jae-Kwan JK Lee Sang Joon SJ Yang Dong Hyun DH

PloS one 20180628 6

Although hemodynamic influence of the subprosthetic tissue, termed as pannus, may contribute to prosthetic aortic valve dysfunction, the relationship between pannus extent and hemodynamics in the prosthetic valve has rarely been reported. We investigated the fluid dynamics of pannus formation using in vitro experiments with particle image velocimetry. Subvalvular pannus formation caused substantial changes in prosthetic valve transvalvular peak velocity, transvalvular pressure gradient (TPG) and ...[more]

PMID: 29953485

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Project description:An experimental set-up is presented for the in vitro characterization of the fluid dynamics in personalized phantoms of healthy and stenosed coronary arteries. The proposed set-up was fine-tuned with the aim of obtaining a compact, flexible, low-cost test-bench for biomedical applications. Technically, velocity vector fields were measured adopting a so-called smart-PIV approach, consisting of a smartphone camera and a low-power continuous laser (30 mW). Experiments were conducted in realistic healthy and stenosed 3D-printed phantoms of left anterior descending coronary artery reconstructed from angiographic images. Time resolved image acquisition was made possible by the combination of the image acquisition frame rate of last generation commercial smartphones and the flow regimes characterizing coronary hemodynamics (velocities in the order of 10 cm/s). Different flow regimes (Reynolds numbers ranging from 20 to 200) were analyzed. The smart-PIV approach was able to provide both qualitative flow visualizations and quantitative results. A comparison between smart-PIV and conventional PIV (i.e., the gold-standard experimental technique for bioflows characterization) measurements showed a good agreement in the measured velocity vector fields for both the healthy and the stenosed coronary phantoms. Displacement errors and uncertainties, estimated by applying the particle disparity method, confirmed the soundness of the proposed smart-PIV approach, as their values fell within the same range for both smart and conventional PIV measured data (≈5% for the normalized estimated displacement error and below 1.2 pixels for displacement uncertainty). In conclusion, smart-PIV represents an easy-to-implement, low-cost methodology for obtaining an adequately robust experimental characterization of cardiovascular flows. The proposed approach, to be intended as a proof of concept, candidates to become an easy-to-handle test bench suitable for use also outside of research labs, e.g., for educational or industrial purposes, or as first-line investigation to direct and guide subsequent conventional PIV measurements.

Project description:BackgroundThe technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.ResultsQuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.ConclusionsThe presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

Dataset Information

Effect of pannus formation on the prosthetic heart valve: In vitro demonstration using particle image velocimetry.

Publications

Effect of pannus formation on the prosthetic heart valve: In vitro demonstration using particle image velocimetry.

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