Flow resistances exerted in the coronary arteries are the key parameters for the image-based computer simulation of coronary hemodynamics. The resistances depend on the anatomical characteristics of the coronary system. A simple and reliable estimation of the resistances is a compulsory procedure to compute the fractional flow reserve (FFR) of stenosed coronary arteries, an important clinical index of coronary artery disease. The cardiac muscle volume reconstructed from computed tomography (CT) images has been used to assess the resistance of the feeding coronary artery (muscle volume-based method). In this study, we estimate the flow resistances exerted in coronary arteries by using a novel method. Based on a physiological observation that longer coronary arteries have more daughter branches feeding a larger mass of cardiac muscle, the method measures the vessel lengths from coronary angiogram or CT images (vessel length-based method) and predicts the coronary flow resistances. The underlying equations are derived from the physiological relation among flow rate, resistance, and vessel length. To validate the present estimation method, we calculate the coronary flow division over coronary major arteries for 50 patients using the vessel length-based method as well as the muscle volume-based one. These results are compared with the direct measurements in a clinical study. Further proving the usefulness of the present method, we compute the coronary FFR from the images of optical coherence tomography.
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Abuchaim DCS, Spera CA, Faraco DL, Ribas Filho JM, Malafaia O (2009) Coronary dominance patterns in the human heart investigated by corrosion casting. Rev Bras Cir Cardiovasc 24(4):514–518. doi:10.1590/S0102-76382009000500013
Antiga L, Ene-Iordache B, Remuzzi A (2003) Computational geometry for patient specific reconstruction and meshing of blood vessels from MR and CT angiography. IEEE Trans Med Imaging. 22(5):674–684. doi:10.1109/TMI.2003.812261
Chen X, Niu P, Niu X, Shen W, Duan F, Ding L, Wei X, Gong Y, Huo Y, Kassab GS, Tan W, Huo Y (2015) Growth, ageing and scaling laws of coronary arterial trees. J R Soc Interface 12(113):20150830
Fukumoto Y, Hiro T, Fujii T, Hashimoto G, Fujimura T, Yamada J, Okamura T, Matsuzaki M (2008) Localized elevation of shear stress is related to coronary plaque rupture: a 3-dimensional intravascular ultrasound study with in-vivo color mapping of shear stress distribution. J Am Coll Cardiol 51(6):645–650. doi:10.1016/j.jacc.2007.10.030
Hall JE (2015) Guyton and Hall textbook of medical physiology. Elsevier Health Sciences. Chapter 21: 245-246
Kai-Pin T (2014) Coronary segmentation in intravascular optical coherence tomography. PhD thesis of Imperial College London; 2014 Chapter 2 and 3: 23–61
Kaimovitz B, Lanir Y, Kassab GS (2010) A full 3-D reconstruction of the entire porcine coronary vasculature. Am J Physiol Heart Circ Physiol 299(4):H1064–76. doi:10.1152/ajpheart.00151.2010
Kim HJ, Vignon-Clementel IE, Coogan JS, Figueroa CA, Jansen KE, Taylor CA (2010) Patient-specific modeling of blood flow and pressure in human coronary arteries. Annals of Biomedical Engineering 38(10):3195–3209. doi:10.1007/s10439-010-0083-6
Koo BK, Erglis A, Doh JH, Daniels DV, Jegere S, Kim HS, Dunning A, DeFrance T, Lansky A, Leipsic J, Min JK (2011) Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms: results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol 58(19):1989–1997. doi:10.1016/j.jacc.2011.06.066
Kwon SS, Chung EC, Park JS, Kim GT, Kim JW, Kim KH, Shin ES, Shim EB (2014) A novel patient-specific model to compute coronary fractional flow reserve. Prog Biophys Mol Biol 116(1):48–55. doi:10.1016/j.pbiomolbio.2014.09.003
Lorenz CH, Walker ES, Morgan VL, Klein SS, Graham TP (1998) Normal human right and left ventricular mass, systolic function, and gender differences by cine magnetic resonance imaging. J Cardiovasc Magn Reson 1(1):7–21. doi:10.3109/10976649909080829
Nakazato R, Park HB, Berman DS, Gransar H, Koo BK, Erglis A, Lin FY, Dunning AM, Budoff MJ, Malpeso J (2013) Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study. Circulation Cardiovascular Imaging 6(6):881–889. doi:10.1161/CIRCIMAGING.113.000297
Nørgaard BL, Leipsic J, Gaur S, Seneviratne S, Ko BS, Ito H, Jensen JM, Mauri L, De Bruyne B, Bezerra H (2014) Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am College of Cardiology 63(12):1145–1155. doi:10.1016/j.jacc.2013.11.043
Renker M, Schoepf US, Wang R, Meinel FG, Rier JD, Bayer RR, Möllmann H, Hamm CW, Steinberg DH, Baumann S (2014) Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol 114(9):1303–1308. doi:10.1016/j.amjcard.2014.07.064
Sakamoto S, Takahashi S, Coskun AU, Papafaklis MI, Takahashi A, Saito S, Stone PH, Feldman CL (2013) Relation of distribution of coronary blood flow volume to coronary artery dominance. Am J Cardiol 111(10):1420–1424. doi:10.1016/j.amjcard.2013.01.290
Samady H, Eshtehardi P, McDaniel MC, Suo J, Dhawan SS, Maynard C, Timmins LH, Quyyumi AA, Giddens DP (2011) Coronary artery wall shear stress is associated with progression and transformation of atherosclerotic plaque and arterial remodeling in patients with coronary artery disease. Circulation 124(7):779–788. doi:10.1161/CIRCULATIONAHA.111.021.824
Sankaran S, Moghadam ME, Kahn AM, Tseng EE, Guccione JM, Marsden AL (2014) Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery. Annals of Biomedical Engineering 40(10):2228–2242. doi:10.1007/s10439-012-0579-3
Taylor CA, Fonte TA, Min JK (2013) Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol 61(22):2233–2241. doi:10.1016/j.jacc.2012.11.083
Yang B, Gogas B, Esposite G, Hung O, Arzrumly ER, Piccinelli M, King S, Giddens D, Veneziani A, Samady H (2015) Novel in-human four dimensional wall shear stress calculation of a coronary bioresorbable scaffold using optical coherence tomography images and blood flow simulations. J Am College of Cardiology 65(10_S):10. doi:10.1016/S0735-1097(15)61832-0
This research was supported by the R&D program of MSIP/COMPA (2015K000245, Development of high-level simulation model of stenosed coronary artery) and the National Research Foundation of Korea (NRF) grants (NRF-2015R1A2A1A0100774).
All the human data used in this study were from Ulsan University Hospital, and their use was approved by the IRB of the institution
The authors declared that they have no competing interests.
Kyung Eun Lee and Soon-Sung Kwon contributed equally to this work.
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Lee, K.E., Kwon, SS., Ji, Y.C. et al. Estimation of the flow resistances exerted in coronary arteries using a vessel length-based method. Pflugers Arch - Eur J Physiol 468, 1449–1458 (2016). https://doi.org/10.1007/s00424-016-1831-8
- Estimation of coronary resistances
- Vessel length-based method
- Coronary fractional flow reserve