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Effect of Mechanical Aortic Valves on Coronary Artery Flow in a Patient Suffering from Ischemic Heart Disease

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Computational Biomechanics for Medicine (MICCAI 2021)

Abstract

Coronary artery disease is the most common cardiovascular condition and one of the leading causes of death worldwide. Coronary artery disease is caused by a narrowing or complete occlusion of the coronary artery lumen. Early diagnosis and correct assessment of the existing stenosis are essential. In our study, a pilot study in this regard, we present a method of non-invasive FFR estimation based on 3D numerical simulations of blood flow through coronary arteries in a 50-year-old man with coronary artery stenosis. Our study considered patient-specific coronary artery geometry. The study determined the effect of blood pressure gradient in flow across mechanical trileaflet (TRI) and bileaflet (BIL) and natural aortic valves on the fractional coronary flow reserve (FFR) value. The predicted value of the FFR ratio for the natural valve is 82% while the FFR value from coronarography is 83%. The predicted FFR values for BIL and TRI mechanical valves are 77% and 75%, respectively.

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References

  1. Fossan, F.E., Sturdy, J., Muller, L.O., et al.: Uncertainty quantification and sensitivity analysis for computational FFR estimation in stable coronary artery disease. Cardiovasc. Eng. Technol. 9(4), 597–622 (2018)

    Article  Google Scholar 

  2. Knuuti, J., Wijns, W., Saraste, A., et al.: 2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes. Eur. Heart J. 41, 407–477 (2020)

    Article  Google Scholar 

  3. Rezende, P.C., Scudeler, T.L., Alves da Costa, L.M., et al.: Conservative strategy for treatment of stable coronary artery disease. World J. Clin. Cases 3, 163–170 (2015)

    Google Scholar 

  4. Perera, D., Clayton, T., O’Kane, P.D., et al.: Percutaneous revascularization for ischemic left ventricular dysfunction. N. Engl. J. Med. 387, 1351–1360 (2022)

    Article  Google Scholar 

  5. Bojar, R.M.: Cardiovascular management. In: Manual of Perioperative Care in Adult Cardiac Surgery. Wiley. ISBN 978-1-119-58255-7 (2021)

    Google Scholar 

  6. Li, M., Zhou, T., Yang, L.-F., et al.: Diagnostic accuracy of myocardial magnetic resonance perfusion to diagnose ischemic stenosis with fractional flow reserve as reference: systematic review and meta-analysis. JACC Cardiovasc. Imaging 7, 1099–1105 (2014)

    Article  Google Scholar 

  7. Yang, Z., Zheng, H., Zhou, T., et al.: Diagnostic performance of myocaradial perfusion imaging with SPECT, CT and MRI compared to fractional flow reserve as reference standard. Int. J. Cardiol. 190, 103–105 (2015)

    Article  Google Scholar 

  8. Qayyum, A., Kastrup, J.: Measuring myocardial perfusion: the role of PET, MRI and CT. Clin. Radiol. 70, 576–584 (2015)

    Article  Google Scholar 

  9. Cook, C.M., Petraco, R., Shun-Shin, M.J., et al.: Diagnostic accuracy of computed tomography-derived fractional flow reserve. A systematic review. JAMA Cardiol. 2(11), 803–810 (2017)

    Article  Google Scholar 

  10. Sonck, J., Nagumo, S., Norgaard, B.L., et al.: Clinical validation of a virtual planner for coronary interventions based on coronary CT angiography. JACC Cardiovasc. Imaging 15, 1242–1255 (2022)

    Article  Google Scholar 

  11. Serruys, P.W., Hara, H., Garg, S., et al.: Coronary computed tomographic angiography for complete assessment of coronary artery disease. J. Am. Coll. Cardiol. 78, 713–736 (2021)

    Article  Google Scholar 

  12. Tanigaki, T., Emori, H., Kawase, Y., et al.: QFR versus FFR derived from computed tomography for functional assessment of coronary artery stenosis. JACC Cardiovasc. Interv. 12, 2050–2059 (2019)

    Article  Google Scholar 

  13. Peper, J., Becker, L.M., van den Berg, H., et al.: Diagnostic performance of CCTA and CT-FFR for the detection of CAD in TAVR work-up. JACC Cardiovasc. Interv. 15, 1140–1149 (2022)

    Article  Google Scholar 

  14. Costa, M.A., Shoemaker, S., Futamatsu, H., et al.: Quantitative magnetic resonance perfusion imaging detects anatomic and physiologic coronary artery disease as measured by coronary angiography and fractional flow reserve. J. Am. Coll. Cardiol. 50, 514–522 (2007)

    Article  Google Scholar 

  15. Siastała, P., Kądziela, J., Małek, ŁA., et al.: Do we need invasive confirmation of cardiac magnetic resonance results? Adv. Interv. Cardiol. 13(1), 26–31 (2017)

    Google Scholar 

  16. Patel, A.R., Salerno, M., Kwong, R.Y., et al.: Stress cardiac magnetic resonance myocardial perfusion imaging: JACC review topic of the week. J. Am. Coll. Cardiol. 78, 1655–1668 (2021)

    Article  Google Scholar 

  17. Scarsini, R., Lunardi, M., Venturi, G., et al.: Long-term variations of FFR and iFR after transcatheter aortic valve implantation. Int. J. Cardiol. 317, 37–41 (2020)

    Article  Google Scholar 

  18. Scarsini, R., Pesarini, G., Lunardi, M., et al.: Observations from a real-time, iFR-FFR “hybrid approach” in patients with severe aortic stenosis and coronary artery disease undergoing TAVI. Cardiovasc. Revasc. Med. 19, 355–359 (2018)

    Article  Google Scholar 

  19. Ahmad, Y., Götberg, M., Cook, C., et al.: Coronary hemodynamics in patients with severe aortic stenosis and coronary artery disease undergoing transcatheter aortic valve replacement: implications for clinical indices of coronary stenosis severity. JACC Cardiovasc. Interv. 11, 2019–2031 (2018)

    Article  Google Scholar 

  20. Nowak, M., Divo, E., Adamczyk, W.P.: Fluid-structure interaction methods for the progressive anatomical and artificial aortic valve stenosis. Int. J. Mech. Sci. 227, 1–20 (2022)

    Article  Google Scholar 

  21. Zhou, H., Wu, L., Wu, Q.: Structural stability of novel composite heart valve prostheses—fatigue and wear performance. Biomed. Pharmacother. 136, 1–8 (2021)

    Article  Google Scholar 

  22. Cavallo, A., Gasparotti, E., Losi, P., et al.: Fabrication and in-vitro characterization of a polymeric aortic valve for minimally invasive valve replacement. J. Mech. Behav. Biomed. Mater. 115, 1–9 (2021)

    Article  Google Scholar 

  23. Pawlikowski, M., Nieroda, A.: Comparative analyses of blood flow through mechanical trileaflet and bileaflet aortic valves. Acta Bioeng. Biomech. 24, 141–152 (2022)

    Article  Google Scholar 

  24. Vignon-Clementel, I.E., Figueroa, C.A., Jansen, K.E., et al.: Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries. Comput. Methods Biomech. Biomed. Eng. 13, 625–640 (2010)

    Article  Google Scholar 

  25. Ali, A., Kazmi, R.: High performance simulation of blood flow pattern and transportation of magnetic nanoparticles in capillaries. Intell. Technol. Appl. 1198, 222–236 (2020)

    Google Scholar 

  26. Hui, S., Mahmood, F., Matyal, R.: Aortic valve area-technical communication: continuity and Gorlin equations revisited. J. Cardiothorac. Vasc. Anesth. 32(6), 2599–2606 (2018)

    Article  Google Scholar 

  27. Taylor, C.A., Figueroa, C.: Patient-specific modeling of cardiovascular mechanics. Ann. Rev. Biomed. Eng. 11, 109–134 (2009)

    Article  Google Scholar 

  28. Morris, P.D, van de Vosse, F.N., Lawford, P.V., et. al.: “Virtual”(computed) fractional flow reserve: current challenges and limitations. JACC: Cardiovasc. Interv. 8(8), 1009–1017 (2015)

    Google Scholar 

  29. Xue, X., Liu, X., Gao, Z., et al.: Personalized coronary blood flow model based on CT perfusion to non-invasively calculate fractional flow reserve. Comput. Methods Appl. Mech. Eng. 404, 115789 (2023)

    Article  MathSciNet  MATH  Google Scholar 

  30. Carvalho, V., Rodrigues, N., Ribeiro, R., et al.: Hemodynamic study in 3D printed stenotic coronary artery models: experimental validation and transient simulation. Comput. Methods Biomech. Biomed. Eng. 24(6), 623–636 (2020)

    Article  Google Scholar 

  31. Lo, E.W.C., Menezes, L.J., Torii, R.: Impact of inflow boundary conditions on the calculation of CT-based FFR. Fluids 4(2), 60 (2019)

    Article  Google Scholar 

  32. Carvalho, V., Rodrigues, N., Ribeiro, R., et al.: 3D printed biomodels for flow visualization in stenotic vessels: an experimental and numerical study. Micromachines 11(6), 549 (2020)

    Article  Google Scholar 

  33. Kashyap, V., Arora, B.B., Bhattacharjee, S.: A computational study of branch-wise curvature in idealized coronary artery bifurcations. Appl. Eng. Sci. 4, 100027 (2020)

    Google Scholar 

  34. Pandey, R., Kumar, M., Srivastav, V.K.: Numerical computation of blood hemodynamic through constricted human left coronary artery: pulsatile simulations. Comput. Methods Program. Biomed. 197, 105661 (2020)

    Article  Google Scholar 

  35. Zhao, Y., Ping, J., Yu, X.: Fractional flow reserve-based 4D hemodynamic simulation of time-resolved blood flow in left anterior descending coronary artery. Clin. Biomech. 70, 164–169 (2019)

    Article  Google Scholar 

  36. de Tullio, M.D., Pedrizzetti, G., Verzicco, R.: On the effect of aortic root geometry on the coronary entry-flow after a bileaflet mechanical heart valve implant: a numerical study. Acta Mech. 216(1), 147–156 (2011)

    Article  MATH  Google Scholar 

  37. Belkhiri, K., Boumeddane, B.: A Cartesian grid generation technique for 2-D non-Newtonian blood flow through a bileaflet mechanical heart valve. Int. J. Comput. Methods Eng. 22(4), 297–315 (2021)

    MathSciNet  Google Scholar 

  38. Querzoli, G., Fortini, S., Espa, S., et al.: A laboratory model of the aortic root flow including the coronary arteries. Exp. Fluids 57(8), 1–9 (2016)

    Article  Google Scholar 

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Correspondence to Marek Pawlikowski .

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Nieroda, A., Jankowski, K., Pawlikowski, M. (2023). Effect of Mechanical Aortic Valves on Coronary Artery Flow in a Patient Suffering from Ischemic Heart Disease. In: Nash, M.P., Wittek, A., Nielsen, P.M.F., Kobielarz, M., Babu, A.R., Miller, K. (eds) Computational Biomechanics for Medicine. MICCAI 2021. Springer, Cham. https://doi.org/10.1007/978-3-031-34906-5_10

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  • DOI: https://doi.org/10.1007/978-3-031-34906-5_10

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