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New imaging tools in cardiovascular medicine: computational fluid dynamics and 4D flow MRI

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Abstract

Blood flow imaging is a novel technology in cardiovascular medicine and surgery. Today, two types of blood flow imaging tools are available: measurement-based flow visualization including 4D flow MRI (or 3D cine phase-contrast magnetic resonance imaging), or echocardiography flow visualization software, and computer flow simulation modeling based on computational fluid dynamics (CFD). MRI and echocardiography flow visualization provide measured blood flow but have limitations in temporal and spatial resolution, whereas CFD flow calculates the flow according to assumptions instead of flow measurement, and it has sufficiently fine resolution up to the computer memory limit, and it enables even virtual surgery when combined with computer graphics. Blood flow imaging provides profound insight into the pathophysiology of cardiovascular diseases, because it quantifies and visualizes mechanical stress on the vessel walls or heart ventricle. Wall shear stress (WSS) is a stress on the endothelial wall caused by the near wall blood flow, and it is thought to be a predictor of atherosclerosis progression in coronary or aortic diseases. Flow energy loss (EL) is the loss of blood flow energy caused by viscous friction of turbulent diseased flow, and it is expected to be a predictor of ventricular workload on various heart diseases including heart valve disease, cardiomyopathy, and congenital heart diseases. Blood flow imaging can provide useful information for developing predictive medicine in cardiovascular diseases, and may lead to breakthroughs in cardiovascular surgery, especially in the decision-making process.

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Abbreviations

CFD:

Computational fluid dynamics

CT:

Computed tomography

DCM:

Dilated cardiomyopathy

EL:

Energy loss

FFR:

Frictional flow reserve

LV:

Left ventricle

MRI:

Magnetic resonance imaging

OSI:

Oscillatory shear index

PC MRI:

Phase-contrast magnetic resonance imaging

SSFP:

Steady-state free procession

VFM:

Vector flow mapping

WSS:

Wall shear stress

References

  1. Itatani K. Advances in hemodynamics research. Nova Science Publisher. 2015.

  2. Richter Y, Edelman ER. Cardiology is flow. Circulation. 2006;113(23):2679–82.

    Article  PubMed  Google Scholar 

  3. Landau LD, Lifshitz EM. Course of theoretical physics. Fluid mechanics. 2nd edn. Butterworth Heinemann: 1987.

  4. Pedrizzetti G, La Canna G, Alfieri O, Tonti G. The vortex—an early predictor of cardiovascular outcome? Nat Rev Cardiol. 2014;11(9):545–53.

    Article  PubMed  Google Scholar 

  5. Whitehead KK, Pekkan K, Kitajima HD, Paridon SM, Yoganathan AP, Fogel MA. Nonlinear power loss during exercise in single-ventricle patients after the Fontan: insights from computational fluid dynamics. Circulation. 2007;116(11 Suppl):I165-I171.

    Google Scholar 

  6. Dasi LP, Rema RK, Kitajima HD, Pekkan K, Sundareswaran KS, Fogel M, Sharma S, Whitehead K, Kanter K, Yoganathan AP. Fontan hemodynamics: importance of artery diameter. J Thorac Cardiovasc Surg. 2009;137:560–4.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Honda T, Itatani K, Takanashi M, Mineo E, Kitagawa A, Ando H, Kimura S, Nakahata Y, Oka N, Miyaji K, Ishii M. Quantitative evaluation of hemodynamics in the Fontan circulation: a cross-sectional study measuring energy loss in vivo. Pediatr Cardiol. 2014;35(2):361–7.

    Article  PubMed  Google Scholar 

  8. Itatani K, Ono M. Blood flow visualiziong diagnostic device. Patent WO2013077013 A1 PCT/JP2012/063484 2013-05-30.

  9. Itatani K, Okada T, Uejima T, Tanaka T, Ono M, Miyaji K, Takenaka K. Intraventricular flow velocity vector visualization based on the continuity equation and measurements of vorticity and wall shear stress. Jpn J Appl Phys. 2013;52:07HF16.

    Article  Google Scholar 

  10. Honda T, Itatani K, Miyaji K, Ishii M. Assessment of the vortex flow in the post-stenotic dilatation above the pulmonary valve stenosis in an infant using echocardiography vector flow mapping. Eur Heart J. 2014;35(5):306.

    Article  PubMed  Google Scholar 

  11. Stugaard M, Koriyama H, Katsuki K, Masuda K, Asanuma T, Takeda Y, Sakata Y, Itatani K, Nakatani S. Energy loss in the left ventricle obtained by vector flow mapping as a new quantitative measure of severity of aortic regurgitation: a combined experimental and clinical study. Eur Heart J Cardiovasc Imaging. 2015;16(7):723–30.

    Article  PubMed  Google Scholar 

  12. Fukuda N, Itatani K, Kimura K, Ebihara A, Negishi K, Uno K, Miyaji K, Kurabayashi M, Takenaka K. An inefficient vortex remains during the ejection period in the left ventricle with a low ejection fraction—a study by vector flow mapping-. J Med Ultrasonic. 2014;41(3):301–10.

    Article  Google Scholar 

  13. Nabeta T, Itatani K, Miyaji K, Ako J. Vortex flow energy loss reflects therapeutic effect in dilated cardiomyopathy. Eur Heart J. 2015;36(11):637.

    Article  PubMed  Google Scholar 

  14. Hwang J, Saha A, Boo YC, Sorescu GP, McNally JS, Holland SM, Dikalov S, Giddens DP, Griendling KK, Harrison DG, Jo H. Oscillatory shear stress stimulates endothelial production of O2—from p47phox-dependent NAD(P)H oxidases, leading to monocyte adhesion. J Biol Chem. 2003;278(47):47291–8.

    Article  CAS  PubMed  Google Scholar 

  15. Fukumoto Y, Hiro T, Fujii T, Hashimoto G, Fujimura T, Yamada J, Okamura T, Matsuzaki M. 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. 2008;51(6):645–50.

    Article  PubMed  Google Scholar 

  16. Chatzizisis YS, Jonas M, Coskun AU, Beigel R, Stone BV, Maynard C, Gerrity RG, Daley W, Rogers C, Edelman ER, Feldman CL, Stone PH. Prediction of the localization of high-risk coronary atherosclerotic plaques on the basis of low endothelial shear stress: an intravascular ultrasound and histopathology natural history study. Circulation. 2008;117(8):993–1002.

    Article  PubMed  Google Scholar 

  17. Numata S, Itatani K, Kanda K, Doi K, Yamazaki S, Morimoto K, Manabe K, Ikemoto K, Yaku H. Blood flow analysis of the aortic arch using computational fluid dynamics. Eur J Cardiothorac Surg. 2016;49(6):1578–85.

    Article  PubMed  Google Scholar 

  18. Yiannis S, Ahmet UC, Michael J, Elazer RE, Charles LF, Peter HS. Role of endothelial shear stress in the natural history of coronary atherosclerosis and vascular remodeling. J Am Coll cardiol. 2007;49:2379–93.

    Article  Google Scholar 

  19. Chatzizisis YS, Coskun AU, Jonas M, Edelman ER, Feldman CL, Stone PH. Role of endotherial shear stress in the natural history of coronary atherosclerosis and vascular remodeling: molecular, cellular and vascular behavior. J Am Coll Cardiol. 2007;49:2379–93.

    Article  CAS  PubMed  Google Scholar 

  20. Jones L, Pressdee DJ, Lamont PM, Baird RN, Murphy KP. A phase contrast (PC) rephase/dephase sequence of magnetic resonance angiography (MRA): a new technique for imaging distal run-off in the pre-operative evaluation of peripheral vascular disease. Clin Radiol. 1998;53(5):333–7.

    Article  CAS  PubMed  Google Scholar 

  21. Bogren HG, Mohiaddin RH, Kilner PJ, Jimenez-Borreguero LJ, Yang GZ, Firmin DN. Blood flow patterns in the thoracic aorta studied with three-directional MR velocity mapping: the effects of age and coronary artery disease. J Magn Reson Imaging. 1997;7(5):784–93.

    Article  CAS  PubMed  Google Scholar 

  22. Stadlbauer A, van der Riet W, Crelier G, Salomonowitz E. Accelerated time-resolved three-dimensional MR velocity mapping of blood flow patterns in the aorta using SENSE and k-t BLAST. Eur J Radiol. 2010;75(1):e15-21.

    Article  PubMed  Google Scholar 

  23. Vasanawala SS, Hanneman K, Alley MT, Hsiao A. Congenital heart disease assessment with 4D flow MRI. J Magn Reson Imaging. 2015;42:870–86.

    Article  PubMed  Google Scholar 

  24. Semaan E, Markl M, Malaisrie SC, Barker A, Allen B, McCarthy P, Carr JC, Collins JD. Haemodynamic outcome at four-dimensional flow magnetic resonance imaging following valve-sparing aortic root replacement with tricuspid and bicuspid valve morphology. Eur J Cardiothorac Surg. 2014;45(5):818–25.

    Article  PubMed  Google Scholar 

  25. Collins JD, Semaan E, Barker A, McCarthy PM, Carr JC, Markl M, Malaisrie SC. Comparison of hemodynamics after aortic root replacement using valve-sparing or bioprosthetic valved conduit. Ann Thorac Surg. 2015;100(5):1556–62.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Keller EJ, Malaisrie SC, Kruse J, McCarthy PM, Carr JC, Markl M, Barker AJ, Collins JD. Reduction of aberrant aortic haemodynamics following aortic root replacement with a mechanical valved conduit. Interact Cardiovasc Thorac Surg. 2016;23(3):416–23.

    Article  PubMed  Google Scholar 

  27. Kilner PJ, Yang GZ, Mohiaddin RH, Firmin DN, Longmore DB. Helical and retrograde secondary flow patterns in the aortic arch studied by three-directional magnetic resonance velocity mapping. Circulation. 1993;88:2235–47.

    Article  CAS  PubMed  Google Scholar 

  28. Oechtering TH, Hons CF, Sieren M, Hunold P, Hennemuth A, Huellebrand M, Drexl J, Scharfschwerdt M, Richardt D, Sievers HH, Barkhausen J, Frydrychowicz A. Time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI) analysis of hemodynamics in valve-sparing aortic root repair with an anatomically shaped sinus prosthesis. J Thorac Cardiovasc Surg. 2016;152(2):418–27.

    Article  PubMed  Google Scholar 

  29. Clough RE, Waltham M, Giese D, Taylor PR, Schaeffter T. A new imaging method for assessment of aortic dissection using four-dimensional phase contrast magnetic resonance imaging. J Vasc Surg. 2012;55(4):914–23.

    Article  PubMed  Google Scholar 

  30. Eriksson J, Carlhäll CJ, Dyverfeldt P, Engvall J, Bolger AF, Ebbers T. Semi-automatic quantification of 4D left ventricular blood flow. J Cardiovasc Magn Reson. 2010;12:9.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Silber HA, Bluemke DA, Ouyang P, Du Y. P. P., Post WS, Lima JAC. The relationship between vascular wall shear stress and flow-mediated dilation: endothelial function assessed by phase-contrast magnetic resonance angiography. J Am Coll Cardiol. 2001;38:1859–65.

    Article  CAS  PubMed  Google Scholar 

  32. Barker AJ, Lanning C, Shandas R. Quantification of hemodynamic wall shear stress in patients with bicuspid aortic valve using phase-contrast MRI. Ann Biomed Eng. 2010;38(3):788–800.

    Article  PubMed  Google Scholar 

  33. Harloff A, Nussbaumer A, Bauer S, Stalder AF, Frydrychowicz A, Weiller C, Hennig J, Markl M. In vivo assessment of wall shear stress in the atherosclerotic aorta using flow-sensitive 4D MRI. Magn Reson Med. 2010;63(6):1529–36.

    Article  PubMed  Google Scholar 

  34. Prakash S, Ethier CR. Requirements for mesh resolution in 3D computational hemodynamics. J Biomech Eng. 2001;123(2):134–44.

    Article  CAS  PubMed  Google Scholar 

  35. Barker AJ, van Ooij P, Bandi K, Garcia J, Albaghdadi M, McCarthy P, Bonow RO, Carr J, Collins J, Malaisrie SC, Markl M. Viscous energy loss in the presence of abnormal aortic flow. Magn Reson Med. 2014;72(3):620–8.

    Article  PubMed  Google Scholar 

  36. Frauenfelder T, Lotfey M, Boehm T, Wildermuth S. Computational fluid dynamics: hemodynamic changes in abdominal aortic aneurysm after stent-graft implantation. Cardiovasc Interv Radiol. 2006;29:613–23.

    Article  Google Scholar 

  37. Kim HB, Hertzberg JR, Shandas R. Development and validation of echo PIV. Exp Fluid. 2004;36:455–62.

    Article  Google Scholar 

  38. Hong GR, Pedrizzetti G, Tonti G, Li P, Wei Z, Kim JK, Baweja A, Liu S, Chung N, Houle H, Narula J, Vannan MA. Characterization and quantification of vortex flow in the human left ventricle by contrast echocardiography using vector particle image velocimetry. JACC Cardiovasc Imaging. 2008;1(6):705 – 17.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Faludi R, Szulik M, D’hooge J, Herijgers P, Rademakers F, Pedrizzetti G, Voigt JU. Left ventricular flow patterns in healthy subjects and patients with prosthetic mitral valves: an in vivo study using echocardiographic particle image velocimetry. J Thorac Cardiovasc Surg. 2010;139(6):1501–10.

    Article  PubMed  Google Scholar 

  40. Sengupta PP, Pedrizetti G, Narula J. Multiplanar visualization of blood flow using echocardiographic particle imaging velocimetry. JACC Cardiovasc Imaging. 2012;5(5):566–9.

    Article  PubMed  Google Scholar 

  41. Prinz C, Faludi R, Walker A, Amzulescu M, Gao H, Uejima T, Fraser AG, Voigt JU. Can echocardiographic particle image velocimetry correctly detect motion patterns as they occur in blood inside heart chambers? A validation study using moving phantoms. Cardiovasc Ultrasound. 2012;10:24.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Agati L, Cimino S, Tonti G, Cicogna F, Petronilli V, De Luca L, Iacoboni C, Pedrizzetti G. Quantitative analysis of intraventricular blood flow dynamics by echocardiographic particle image velocimetry in patients with acute myocardial infarction at different stages of left ventricular dysfunction. Eur Heart J Cardiovasc Imaging. 2014;15(11):1203–12.

    Article  CAS  PubMed  Google Scholar 

  43. Adrian RJ. Particle-image technique for experimental fluid mechanics. Annu Rev Fluid Mech. 1991;23:261–304.

    Article  Google Scholar 

  44. Ohtsuki S, Tanaka M. The flow velocity distribution from the Doppler information on a plane in three-dimensional flow. J Visual. 2006;9:69–82.

    Article  Google Scholar 

  45. Uejima T, Koike A, Sawada H, Aizawa T, Ohtsuki S, Tanaka M, Furukawa T, Fraser AG. A new echocardiography method for identifying vortex flow in the left ventricle: numerical study. Ultrasound Med Biol. 2010;36(5):772 – 88.

    Article  PubMed  Google Scholar 

  46. Garcia D, Del Almano JC, Tanne D, Yotti R, Cortina C, Bertrand E, Antoranz JC, Perez-David E, Rieu R, Fernandez-Aviles F, Bermejo J. Two-dimensional intraventricular flow mapping by digital processing conventional color-Doppler echocardiography images. IEEE Trans Med Imaging. 2010;29(10):1701–13.

    Article  PubMed  Google Scholar 

  47. Honda T, Itatani K, Miyaji K, Ishii M. Assessment of the vortex flow in the post-stenotic dilatation above the pulmonary valve stenosis in an infant using echocardiography vector flow mapping. Eur Heart J. 2014 Feb;35(5):306.

    Article  PubMed  Google Scholar 

  48. Nogami Y, Ishizu T, Atsumi A, Yamamoto M, Kawamura R, Seo Y, Aonuma K. Abnormal early diastolic intraventricular flow ‘kinetic energy index’ assessed by vector flow mapping in patients with elevated filling pressure. Eur Heart J Cardiovasc Imaging. 2013;14(3):253 – 60.

    Article  PubMed  Google Scholar 

  49. Nakashima K, Itatani K, Kitamura T, Oka N, Horai T, Miyazaki S, Nie M, Miyaji K. Energy dynamics of the intraventricular vortex after mitral valve surgery. Heart Vessels. 2017. doi:10.1007/s00380-017-0967-6 (in press).

    PubMed  Google Scholar 

  50. Akiyama K, Nakamura N, Itatani K, Naito Y, Kinoshita M, Shimizu M, Hamaoka S, Kato H, Yasumoto H, Nakajima Y, Mizobe T, Numata S, Yaku H, Sawa T. Flow-dynamics assessment of mitral-valve surgery by intraoperative vector flow mapping. Interact Cardiovasc Thorac Surg. 2017;24(6):869–75.

    Article  PubMed  Google Scholar 

  51. Akiyama K, Itatani K, Naito Y, Kinoshita M, Shimizu M, Hamaoka S, Yasumoto H, Kato H, Nakajima Y, Numata S, Yaku H, Sawa T. Vector flow mapping and impaired left ventricular flow after the alfieri stitch. J Cardiothorac Vasc Anesth. 2017;31(1):211–4.

    Article  PubMed  Google Scholar 

  52. Chung TJ. Computational fluid dynamics. 2nd edn. Cambridge: Cambridge University. 2010.

    Book  Google Scholar 

  53. Itatani K, Miyaji K, Tomoyasu T, Nakahata Y, Ohara K, Takamoto S, Ishii M. Optimal conduit size of the extracardiac Fontan operation based on energy loss and flow stagnation. Ann Thorac Surg 2009;88(2):565–72.

    Article  Google Scholar 

  54. Vignon-Clementel IE, Figueroa CA, Jansen KE, Taylor CA. Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries. Comput Methods Biomech Biomed Eng. 2010;13(5):625–40.

    Article  CAS  Google Scholar 

  55. Hsia TY, Cosentino D, Corsini C, Pennati G, Dubini G, Migliavacca F, Modeling of Congenital Hearts Alliance (MOCHA) Investigators. Use of mathematical modeling to compare and predict hemodynamic effects between hybrid and surgical Norwood palliations for hypoplastic left heart syndrome. Circulation. 2011;124(11 Suppl):S204–210.

    Article  PubMed  Google Scholar 

  56. Goto S, Nakamura M, Itatani K, Miyazaki S, Oka N, Honda T, Kitamura T, Horai T, Ishii M, Miyaji K. Synchronization of the flow and pressure waves obtained with non-simultaneous multipoint measurements. Int Heart J. 2016;57(4):449–55.

    Article  PubMed  Google Scholar 

  57. Honda T, Itatani K, Takanashi M, Kitagawa A, Ando H, Kimura S, Nakahata Y, Oka N, Miyaji K, Ishii M. Contributions of respiration and heartbeat to the pulmonary blood flow in the Fontan circulation. Ann Thorac Surg. 2016;102(5):1596–606.

    Article  PubMed  Google Scholar 

  58. Taylor C a, Fonte T a, Min JK. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013;61:2233–41.

    Article  PubMed  Google Scholar 

  59. Koo BK, Erglis A, Doh JH, Daniels DV, Jegere S, Kim HS, Dunning A, DeFrance T, Lansky A, Leipsic J, Min JK. 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. 2011;58(19):1989–97.

    Article  PubMed  Google Scholar 

  60. Min JK, Leipsic J, Pencina MJ, Berman DS, Koo BK, van Mieghem C, Erglis A, Lin FY, Dunning AM, Apruzzese P, Budoff MJ, Cole JH, Jaffer FA, Leon MB, Malpeso J, Mancini GB, Park SJ, Schwartz RS, Shaw LJ, Mauri L. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308(12):1237–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Nørgaard BL, Leipsic J, Gaur S, Seneviratne S, Ko BS, Ito H, Jensen JM, Mauri L, De Bruyne B, Bezerra H, Osawa K, Marwan M, Naber C, Erglis A, Park SJ1, Christiansen EH, Kaltoft A, Lassen JF, Bøtker HE, Achenbach S. NXT Trial Study Group. 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 Coll Cardiol. 2014;63(12):1145–55.

    Article  PubMed  Google Scholar 

  62. Douglas PS, De Bruyne B, Pontone G, Patel MR, Norgaard BL, Byrne RA, Curzen N, Purcell I, Gutberlet M, Rioufol G, Hink U, Schuchlenz HW, Feuchtner G, Gilard M, Andreini D, Jensen JM, Hadamitzky M, Chiswell K, Cyr D, Wilk A, Wang F, Rogers C, Hlatky MA. 1-Year outcomes of FFRCT-guided care in patients with suspected coronary disease: the PLATFORM study. J Am Coll Cardiol. 2016;68(5):435–45.

    Article  PubMed  Google Scholar 

  63. Haggerty CM, Restrepo M, Tang E, de Zélicourt D a, Sundareswaran KS, Mirabella L, Bethel J, Whitehead KK, Fogel M a, Yoganathan AP. Fontan hemodynamics from 100 patient-specific cardiac magnetic resonance studies: a computational fluid dynamics analysis. J Thorac Cardiovasc Surg. 2013:1–10.

  64. Van Haesdonck JM, Mertens L, Sizaire R, Montas G, Purnode B, Daenen W, Crochet M, Gewillig M. Comparison by computerized numeric modeling of energy losses in different Fontan connections. Circulation. 1995;92:322–6.

    Article  Google Scholar 

  65. Bove EL, Migliavacca F, de Leval MR, Balossino R, Pennati G, Lloyd TR, Khambadkone S, Hsia T-Y, Dubini G. Use of mathematic modeling to compare and predict hemodynamic effects of the modified Blalock–Taussig and right ventricle-pulmonary artery shunts for hypoplastic left heart syndrome. J Thorac Cardiovasc surg. 2008;136:312–320 (e2).

    Article  PubMed  Google Scholar 

  66. Pekkan K, Kitajima HD, de Zelicourt D, Forbess JM, Parks WJ, Fogel M a, Sharma S, Kanter KR, Frakes D, Yoganathan AP. Total cavopulmonary connection flow with functional left pulmonary artery stenosis: angioplasty and fenestration in vitro. Circulation. 2005;112:3264–71.

    Article  PubMed  Google Scholar 

  67. de Zélicourt D a, Pekkan K, Parks J, Kanter K, Fogel M, Yoganathan AP. Flow study of an extracardiac connection with persistent left superior vena cava. J Thorac Cardiovasc Surg. 2006;131:785–91.

    Article  PubMed  Google Scholar 

  68. Corsini Baretta a, Yang C, Vignon-Clementel W, Marsden a IE, Feinstein L, Hsia J a, Dubini T-Y, Migliavacca G, Pennati FG. Virtual surgeries in patients with congenital heart disease: a multi-scale modelling test case. Philos Transact A Math Phys Eng Sci. 2011;369:4316–30.

    Article  Google Scholar 

  69. Qian Y, Liu JL, Itatani K, Miyaji K, Umezu M. Computational hemodynamic analysis in congenital heart disease: simulation of the Norwood procedure. Ann Biomed Eng. 2010;38(7):2302–13.

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Cardiovascular Surgery, Cardiovascular Imaging Research Laboratory, Kyoto Prefectural University of Medicine, Kawaramachi-Hirokoji Kajicho 465, Kamigyo-ku, Kyoto, 602-8566, Japan

    Keiichi Itatani, Satoshi Numata, Sachiko Yamazaki, Kazuki Morimoto, Rina Makino, Hiroko Morichi & Hitoshi Yaku

  2. Cardio Flow Design Inc., Tokyo, Japan

    Shohei Miyazaki, Tokoki Furusawa & Teruyasu Nishino

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  1. Keiichi Itatani
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Keiichi Itatani is an endowed chair of Kyoto Prefectural University of Medicine, financially supported by Medtronic Japan. Keiichi Itatani also has a stock option of Cardio Flow Design Inc. Keiichi Itatani has a KAKEN grant for young researcher A. Keiichi Itatani is a director of Hokkaido Cardiovascular Hospital. Other authors: Shohei Miyazaki, Tokoki Furusawa, Satoshi Numata, Sachiko Yamazaki, Kazuki Morimoto, Rina Makino, Hiroko Morichi, Teruyasu Nishino, and Hitoshi Yaku have no conflict of interest exists.

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Itatani, K., Miyazaki, S., Furusawa, T. et al. New imaging tools in cardiovascular medicine: computational fluid dynamics and 4D flow MRI. Gen Thorac Cardiovasc Surg 65, 611–621 (2017). https://doi.org/10.1007/s11748-017-0834-5

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