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
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)
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)
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)
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)
Bojar, R.M.: Cardiovascular management. In: Manual of Perioperative Care in Adult Cardiac Surgery. Wiley. ISBN 978-1-119-58255-7 (2021)
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)
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)
Qayyum, A., Kastrup, J.: Measuring myocardial perfusion: the role of PET, MRI and CT. Clin. Radiol. 70, 576–584 (2015)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
Zhou, H., Wu, L., Wu, Q.: Structural stability of novel composite heart valve prostheses—fatigue and wear performance. Biomed. Pharmacother. 136, 1–8 (2021)
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)
Pawlikowski, M., Nieroda, A.: Comparative analyses of blood flow through mechanical trileaflet and bileaflet aortic valves. Acta Bioeng. Biomech. 24, 141–152 (2022)
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)
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)
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)
Taylor, C.A., Figueroa, C.: Patient-specific modeling of cardiovascular mechanics. Ann. Rev. Biomed. Eng. 11, 109–134 (2009)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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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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