Abstract
Pericardiectomy is recommended therapy for pericarditis, an inflammation of the pericardial layers that surround the heart and play a central role in maintaining cardiac performance. In some cases, the pericardium can be repaired or patched. However, the impact of changes in the pericardium on cardiac function is not clear. The objective of this study is to analyze the effect of the pericardium on whole-heart function by varying normal Robin boundary conditions (BCs) applied on the ventricular epicardium. A piece-wise linear penalty function was defined using two parameters that were varied to describe the regional scaling of normal spring stiffness from apex to base. Gaussian process emulators were used to perform a global sensitivity analysis on how the varying pericardial BCs affect cardiac biomechanics in four-chamber heart models. Our results have shown that pressure- and volume-derived biomarkers change by less than 25% due to variations in the pericardium, with more variation in the right ventricle compared to the left ventricle. On the other hand, measurements for systolic motion exhibited a range of variability greater than 100% of the baseline mean. We predict that the pericardium has limited impact on measures of global function but impacts measures of local cardiac biomechanics.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Afanasyeva, M., Georgakopoulos, D., Fairweather, D., Caturegli, P., Kass, D., Rose, N.: Novel model of constrictive pericarditis associated with autoimmune heart disease in interferon-\(\gamma \)-knockout mice. Circulation 110(18), 2910–2917 (2004)
Alter, P., Figiel, J., Rupp, R., Bachmann, G., Maisch, B., Rominger, M.: MR, CT, and PET imaging in pericardial disease. Heart Fail. Rev. 18(3), 289–306 (2013)
Augustin, C., et al.: A computationally efficient physiologically comprehensive 3D–0D closed-loop model of the heart and circulation. Comput. Methods Appl. Mech. Eng. 386, 114092 (2021)
Augustin, C., et al.: Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation. J. Comput. Phys. 305, 622–646 (2016)
Barrows, R., et al.: The effect of heart rate and atrial contraction on left ventricular function. Comput. Cardiol. 498, 1–4 (2022)
Bayer, J., et al.: Universal ventricular coordinates: a generic framework for describing position within the heart and transferring data. Med. Image Anal. 45, 83–93 (2018)
Bayer, J., Blake, R., Plank, G., Trayanova, N.: A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann. Biomed. Eng. 40(10), 2243–2254 (2012)
Bitcon, C., Tousignant, C.: The effect of pericardial incision on right ventricular systolic function: a prospective observational study. Can. J. Anesth./J. Can. d’anesthésie 64(12), 1194–1201 (2017)
Bols, J., Degroote, J., Trachet, B., Verhegghe, B., Segers, P., Vierendeels, J.: A computational method to assess the in vivo stresses and unloaded configuration of patient-specific blood vessels. J. Comput. Appl. Math. 246, 10–17 (2013)
Chang, S., Kim, H., Kim, Y., Cho, G., Oh, S., Sohn, D.: Role of pericardium in the maintenance of left ventricular twist. Heart 96(10), 785–790 (2010)
Daughters, G., Frist, W., Alderman, E., Derby, G., Ingels, N., Jr., Miller, D.: Effects of the pericardium on left ventricular diastolic filling and systolic performance early after cardiac operations. J. Thorac. Cardiovasc. Surg. 104(4), 1084–1091 (1992)
Gerach, T., et al.: Electro-mechanical whole-heart digital twins: a fully coupled multi-physics approach. Mathematics 9(11), 1247 (2021)
Guccione, J., McCulloch, A., Waldman, L.: Passive material properties of intact ventricular myocardium determined from a cylindrical model (1991)
Herman, J., Usher, W.: SALib: an open-source python library for sensitivity analysis. J. Open Source Softw. 2(9), 97 (2017)
Longobardi, S., et al.: Predicting left ventricular contractile function via gaussian process emulation in aortic-banded rats. Phil. Trans. R. Soc. A 378(2173), 20190334 (2020)
Mangano, D.: The effect of the pericardium on ventricular systolic function in man. Circulation 61(2), 352–357 (1980)
Marsh, K., et al.: Anti-inflammatory properties of amniotic membrane patch following pericardiectomy for constrictive pericarditis. J. Cardiothorac. Surg. 12(1), 1–4 (2017)
Melo, D., et al.: Impact of pericardiectomy on exercise capacity and sleep of patients with chronic constrictive pericarditis. PLoS ONE 14(10), e0223838 (2019)
Neic, A., et al.: Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model. J. Comput. Phys. 346, 191–211 (2017)
Niederer, S., et al.: Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. Cardiovasc. Res. 89(2), 336–343 (2011)
Plank, G., et al.: The openCARP simulation environment for cardiac electrophysiology. Comput. Methods Programs Biomed. 208, 106223 (2021)
Rodero, C., et al.: Calibration of cohorts of virtual patient heart models using Bayesian history matching. Ann. Biomed. Eng. 51, 1–12 (2022)
Rodero, C., et al.: Linking statistical shape models and simulated function in the healthy adult human heart. PLoS Comput. Biol. 17(4), e1008851 (2021)
Roney, C., et al.: Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes. Med. Image Anal. 55, 65–75 (2019)
Rösner, A., et al.: Changes in right ventricular shape and deformation following coronary artery bypass surgery-insights from echocardiography with strain rate and magnetic resonance imaging. Echocardiography 32(12), 1809–1820 (2015)
Saltelli, A., Annoni, P., Azzini, I., Campolongo, F., Ratto, M., Tarantola, S.: Variance based sensitivity analysis of model output. design and estimator for the total sensitivity index. Comput. Phys. Commun. 181(2), 259–270 (2010)
Santiago, A., et al.: Fully coupled fluid-electro-mechanical model of the human heart for supercomputers. Int. J. Numer. Methods Biomed. Eng. 34(12), e3140 (2018)
Sobol, I.: Global sensitivity indices for nonlinear mathematical models and their monte Carlo estimates. Math. Comput. Simul. 55(1–3), 271–280 (2001)
Simulating ventricular systolic motion in a four-chamber heart model with spatially varying robin boundary conditions to model the effect of the pericardium. J. Biomech. 101, 109645 (2020)
Vigmond, E., Hughes, M., Plank, G., Leon, L.: Computational tools for modeling electrical activity in cardiac tissue. J. Electrocardiol. 36, 69–74 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ghebryal, J. et al. (2023). Effect of Varying Pericardial Boundary Conditions on Whole Heart Function: A Computational Study. In: Bernard, O., Clarysse, P., Duchateau, N., Ohayon, J., Viallon, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2023. Lecture Notes in Computer Science, vol 13958. Springer, Cham. https://doi.org/10.1007/978-3-031-35302-4_56
Download citation
DOI: https://doi.org/10.1007/978-3-031-35302-4_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-35301-7
Online ISBN: 978-3-031-35302-4
eBook Packages: Computer ScienceComputer Science (R0)