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Echocardiographic particle imaging velocimetry data assimilation with least square finite element methods. (English) Zbl 1365.92055

Summary: Recent developments in the field of echocardiography have introduced various noninvasive methods to image blood flow within the heart chambers. FDA-approved microbubbles can be used for intracardiac blood flow imaging and determining the velocity of the blood based on the displacement of the bubbles and the frame rate of the ultrasound scan. A limitation of this approach is that the velocity field information is only two-dimensional and inevitably contains noise. A weighted least square finite element method (WLSFEM) was developed to assimilate noisy, two-dimensional data from echocardiographic particle imaging velocimetry (echo-PIV) into a three-dimensional Navier-Stokes numerical model so that additional flow properties such as the stress and pressure gradient can be determined from the full velocity and pressure fields. The flexibility of the WLSFEM framework allows for matching the noisy echo-PIV data weakly and using the weighted least square functional as an indicator of how well the echo-PIV data are satisfying the numerical model. Results from the current framework demonstrate the ability of the approach to more closely match the more accurate echo-PIV data and less closely match the noisy data. The positive impact of assimilating the echo-PIV data is demonstrated: compared to a conventional computational fluid dynamic approach, echo-PIV data assimilation potentially enables a more accurate flow model.

MSC:

92C55 Biomedical imaging and signal processing
65M60 Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs
92C35 Physiological flow

Software:

PIVlab; hypre
Full Text: DOI

References:

[1] Borazjani, I., Left ventricular flow analysis: recent advances in numerical methods and applications in cardiac ultrasound, Comput. Math. Methods Med. (2013) · Zbl 1275.92040
[2] Wei, F., Weighted least-squares finite element method for cardiac blood flow simulation with echocardiographic data, Comput. Math. Methods Med. (2012) · Zbl 1233.92011
[3] Westerdale, J., Flow velocity vector fields by ultrasound particle imaging velocimetry in vitro comparison with optical flow velocimetry, J. Ultrasound Med., 30, 2, 187-195 (2011)
[4] Jiamsripong, P., Impact of acute moderate elevation in left ventricular afterload on diastolic transmitral flow efficiency: analysis by vortex formation time, J. Am. Soc. Echocardiogr., 22, 4, 427-431 (2009)
[5] Sengupta, P. P., Left ventricular form and function revisited: applied translational science to cardiovascular ultrasound imaging, J. Am. Soc. Echocardiogr., 20, 5, 539-551 (2007)
[6] Sengupta, P. P., Left ventricular structure and function—basic science for cardiac imaging, J. Am. Coll. Cardiol., 48, 10, 1988-2001 (2006)
[8] D’Elia, M.; Perego, M.; Veneziani, A., A variational data assimilation procedure for the incompressible Navier-Stokes equations in hemodynamics, J. Sci. Comput., 52, 2, 340-359 (2012) · Zbl 1264.76076
[9] Sengupta, P. P., Emerging trends in CV flow visualization, JACC: Cardiovasc. Imaging, 5, 3, 305-316 (2012)
[11] Gresho, P. M.; Sani, R. L.; Engelman, M. S., Incompressible Flow and the Finite Element Method (2000), Wiley: Wiley Chichester, England, New York · Zbl 0988.76005
[12] Donéa, J.; Huerta, A., Finite Element Methods for Flow Problems, xi (2003), Wiley: Wiley Chichester, Hoboken, NJ, p. 350
[13] Griffith, B. E., An adaptive, formally second order accurate version of the immersed boundary method, J. Comput. Phys., 223, 1, 10-49 (2007) · Zbl 1163.76041
[14] Heys, J. J., Modeling 3-D compliant blood flow with fosls, Biomed. Sci. Instrum., 40, 193-199 (2004), 449
[15] Bochev, P. B.; Gunzburger, M. D., Least-Squares Finite Element Methods, vol. 166, 1-660 (2009), Least-Squares Finite Element Methods · Zbl 1168.65067
[16] Jiang, B. N., A least-squares finite-element method for incompressible Navier-Stokes problems, Internat. J. Numer. Methods Fluids, 14, 7, 843-859 (1992) · Zbl 0753.76097
[17] Heys, J. J., First-order system least-squares (FOSLS) for modeling blood flow, Med. Eng. Phys., 28, 6, 495-503 (2006)
[18] Heys, J. J., An alternative least-squares formulation of the Navier-Stokes equations with improved mass conservation, J. Comput. Phys., 226, 1, 994-1006 (2007) · Zbl 1123.76032
[19] Heys, J. J., On mass-conserving least-squares methods, SIAM J. Sci. Comput., 28, 5, 1675-1693 (2006) · Zbl 1388.76052
[20] Heys, J. J., Enhanced mass conservation in least-squares methods for Navier-Stokes equations, SIAM J. Sci. Comput., 31, 3, 2303-2321 (2009) · Zbl 1188.76195
[21] Manteuffel, T., Further results on error estimators for local refinement with first-order system least squares (FOSLS), Numer. Linear Algebra Appl., 17, 2-3, 387-413 (2010) · Zbl 1240.65319
[22] Adler, J., An efficiency-based adaptive refinement scheme applied to incompressible, resistive magnetohydrodynamics, (Large-Scale Scientific Computing, vol. 5910 (2010)), 1-13 · Zbl 1280.76064
[23] Bochev, P. B., Analysis of least-squares finite element methods for the Navier-Stokes equations, SIAM J. Numer. Anal., 34, 5, 1817-1844 (1997) · Zbl 0901.76030
[24] Heys, J. J., Weighted least-squares finite elements based on particle imaging velocimetry data, J. Comput. Phys., 229, 1, 107-118 (2010) · Zbl 1381.76173
[25] Bazilevs, Y.; Takizawa, K.; Tezduyar, T. E., Challenges and directions in computational fluid-structure interaction, Math. Models Methods Appl. Sci., 23, 2 (2013) · Zbl 1261.76025
[26] Sackinger, P. A.; Schunk, P. R.; Rao, R. R., A Newton-raphson pseudo-solid domain mapping technique for free and moving boundary problems: a finite element implementation, J. Comput. Phys., 125, 1, 83-103 (1996) · Zbl 0853.65138
[27] Heys, J. J., First-order system least squares (FOSLS) for coupled fluid-elastic problems, J. Comput. Phys., 195, 2, 560-575 (2004) · Zbl 1115.74320
[28] Heys, J. J., First-order system least squares for elastohydrodynamics with application to flow in compliant blood vessels, Biomed. Sci. Instrum., 38, 277-282 (2002)
[29] Rajaraman, P.; Heys, J. J., Simulation of nanoparticle transport in airways using Petrov-Galerkin finite element methods, Int. J. Numer. Methods Biomed. Eng., 30, 1, 103-116 (2014)
[30] Karypis, G.; Kumar, V., A fast and high quality multilevel scheme for partitioning irregular graphs, SIAM J. Sci. Comput., 20, 1, 359-392 (1998) · Zbl 0915.68129
[32] Greenbaum, A., (Iterative Methods for Solving Linear Systems. Iterative Methods for Solving Linear Systems, Frontiers in Applied Mathematics (1997), Society for Industrial and Applied Mathematics: Society for Industrial and Applied Mathematics Philadelphia, PA), xiii, p. 220 · Zbl 0883.65022
[33] Cheng, Y. G.; Oertel, H.; Schenkel, T., Fluid-structure coupled CFD simulation of the left ventricular flow during filling phase, Ann. Biomed. Eng., 33, 5, 567-576 (2005)
[34] Niekrasz, M., The pig as organ donor for man, Transplant. Proc., 24, 2, 625-626 (1992)
[35] Griffith, B. E., Immersed boundary model of aortic heart valve dynamics with physiological driving and loading conditions, Int. J. Numer. Methods Biomed. Eng., 28, 3, 317-345 (2012) · Zbl 1243.92017
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