Abstract
The treatment of coronary stenosis relies on invasive high risk surgical assessment to generate the fractional flow reserve, a ratio of distal to proximal pressures in respect of the stenosis. Non-invasive methods are therefore desirable. Non-invasive imaging-computational methodologies call for robust and calibrated mathematical descriptions of the coronary vasculature that can be personalized. In addition, it is important to understand extra-coronary co-morbidities that may affect fractional flow estimates. In this preliminary theoretical work, a 0D human coronary vasculature model was implemented, and used to demonstrate the distinct roles of focal and extended stenosis (intra-coronary), as well as microvascular disease and atrial fibrillation (extra-coronary) on fractional flow reserve estimation. It was found that the right coronary artery is maximally affected by diffuse stenosis and microvascular disease. The model predicts that the presence, rather than severity, of both microvascular disease and atrial fibrillation affect coronary flow deleteriously. The model provides a computationally inexpensive instrument for future in silico coronary blood flow investigations as well as clinical-imaging decision making. The framework provided is extensible as well as can be personalized. Furthermore, it provides a starting point and crucial boundary conditions for future 3D computational hemodynamics flow estimation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fearon, W.F., Tonino, P.A., De Bruyne, B., Siebert, U., Pijls, N.H.: Rationale and design of the fractional flow reserve versus angiography for multivessel evaluation (FAME) study. Am. Heart J. 154, 632–636 (2007)
Pijls, N.H., et al.: Percutaneous coronary intervention of functionally nonsignificant stenosis: 5-year follow-up of the DEFER study. J. Am. Coll. Cardiol. 49, 2105–2111 (2007)
Tonino, P.A., et al.: Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N. Engl. J. Med. 360, 213–224 (2009)
Odudu, A., Francis, S.T., McIntyre, C.W.: MRI for the assessment of organ perfusion in patients with chronic kidney disease. Curr. Opin. Nephrol. Hypertens. 21, 647–654 (2012)
McIntyre, C.W., et al.: Hemodialysis-induced cardiac dysfunction is associated with an acute reduction in global and segmental myocardial blood flow. Clin. J. Am. Soc. Nephrol.: CJASN 3, 19–26 (2008)
Altamirano-Diaz, L., Kassay, A.D., Serajelahi, B., McIntyre, C.W., Filler, G., Kharche, S.R.: Arterial hypertension and unusual ascending aortic dilatation in a neonate with acute kidney injury: mechanistic computer modeling. Front. Physiol. 10, 1391 (2019)
Kharche, S.R., So, A., Salerno, F., Lee, T.Y., Ellis, C., Goldman, D., McIntyre, C.W.: Computational assessment of blood flow heterogeneity in peritoneal dialysis patients’ cardiac ventricles. Front. Physiol. 9, 511 (2018)
Shi, Y., Korakianitis, T., Bowles, C.: Numerical simulation of cardiovascular dynamics with different types of VAD assistance. J. Biomech. 40, 2919–2933 (2007)
Anselmino, M., Scarsoglio, S., Saglietto, A., Gaita, F., Ridolfi, L.: A computational study on the relation between resting heart rate and atrial fibrillation hemodynamics under exercise. PLoS ONE 12, (2017)
Heldt, T., Mukkamala, R., Moody, G.B., Mark, R.G.: CVSim: an open-source cardiovascular simulator for teaching and research. Open Pacing Electrophysiol. Ther. J. 3, 45–54 (2010)
Heldt, T., Shim, E.B., Kamm, R.D., Mark, R.G.: Computational modeling of cardiovascular response to orthostatic stress. J. Appl. Physiol. 1985(92), 1239–1254 (2002)
Debbaut, C., Monbaliu, D.R., Segers, P.: Validation and calibration of an electrical analog model of human liver perfusion based on hypothermic machine perfusion experiments. Int. J. Artif. Organs 37, 486–498 (2014)
Coli, L., et al.: Evaluation of intradialytic solute and fluid kinetics. Setting up a predictive mathematical model. Blood Purif. 18, 37–49 (2000)
Ursino, M., Coli, L., Brighenti, C., Chiari, L., de Pascalis, A., Avanzolini, G.: Prediction of solute kinetics, acid-base status, and blood volume changes during profiled hemodialysis. Ann. Biomed. Eng. 28, 204–216 (2000)
Lim, K.M., Choi, S.W., Min, B.G., Shim, E.B.: Numerical simulation of the effect of sodium profile on cardiovascular response to hemodialysis. Yonsei Med. J. 49, 581–591 (2008)
Sankaran, S., Esmaily Moghadam, M., Kahn, A.M., Tseng, E.E., Guccione, J.M., Marsden, A.L.: Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery. Ann. Biomed. Eng. 40, 2228–2242 (2012)
Olufsen, M.S., Nadim, A.: On deriving lumped models for blood flow and pressure in the systemic arteries. Math. Biosci. Eng.: MBE 1, 61–80 (2004)
Olufsen, M.S., Peskin, C.S., Kim, W.Y., Pedersen, E.M., Nadim, A., Larsen, J.: Numerical simulation and experimental validation of blood flow in arteries with structured-tree outflow conditions. Ann. Biomed. Eng. 28, 1281–1299 (2000)
Olufsen, M.S.: A one-dimensional fluid dynamic model of the systemic arteries. Stud. Health Technol. Inform. 71, 79–97 (2000)
Kim, H.J., Vignon-Clementel, I.E., Coogan, J.S., Figueroa, C.A., Jansen, K.E., Taylor, C.A.: Patient-specific modeling of blood flow and pressure in human coronary arteries. Ann. Biomed. Eng. 38, 3195–3209 (2010)
Duanmu, Z., Yin, M., Fan, X., Yang, X., Luo, X.: A patient-specific lumped-parameter model of coronary circulation. Sci. Rep. 8, 874 (2018)
Olufsen, M.S.: Structured tree outflow condition for blood flow in larger systemic arteries. Am. J. Physiol.-Heart C 276, H257–H268 (1999)
Tange, O.: GNU parallel - the command-line power tool. USENIX Mag. 36(1), 42–47 (2011)
Marsden, A., Moghadam, M.E.: Multiscale modeling of cardiovascular flows for clinical decision support. Appl. Mech. Rev. 67(3), 030804, 11 p. (2015)
Crowley, L.E., McIntyre, C.W.: Remote ischaemic conditioning—therapeutic opportunities in renal medicine. Nat. Rev. Nephrol. 9, 739–746 (2013)
Acknowledgements
This work was supported by Canada Canarie Inc. (RS-111), Canada Heart and Stroke Foundation grant (G-20-0028717), Canada NSERC operational grant (R4081A03), and NSERC graduate scholarship. We thank Compute Canada for high performance computing resources. We thank Dr. Kapiraj Chandrabalan for editing support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Joseph, J.J., Lee, TY., Goldman, D., McIntyre, C.W., Kharche, S.R. (2021). The Role of Extra-Coronary Vascular Conditions that Affect Coronary Fractional Flow Reserve Estimation. In: Ennis, D.B., Perotti, L.E., Wang, V.Y. (eds) Functional Imaging and Modeling of the Heart. FIMH 2021. Lecture Notes in Computer Science(), vol 12738. Springer, Cham. https://doi.org/10.1007/978-3-030-78710-3_57
Download citation
DOI: https://doi.org/10.1007/978-3-030-78710-3_57
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-78709-7
Online ISBN: 978-3-030-78710-3
eBook Packages: Computer ScienceComputer Science (R0)