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The relationship between systolic vector flow mapping parameters and left ventricular cardiac function in healthy dogs

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Abstract

Vector flow mapping (VFM) is a novel echocardiographic technology that shows blood flow vectors and vortexes, enabled the hydrokinetic evaluation of hemodynamics within the left ventricle. VFM provides several unique parameters: circulation, vorticity, vortex area, and energy loss. The present study aims to reveal a relationship between VFM parameters and cardiac function. Five healthy Beagle dogs were anesthetized and administered with dobutamine (0, 2, 4, 8, 12 µg/kg/min). Pressure–volume diagrams were acquired to assess cardiac function using pressure–volume conductance catheter. Systolic maximum circulation, vorticity, vortex area, and energy loss were measured using VFM. The systolic maximum circulation, systolic vorticity, systolic vortex area, and systolic energy loss were increased by dobutamine administration. There was a strongly significant correlation between the systolic maximum circulation and ejection fraction (r = 0.76), maximal positive left ventricular (LV) pressure derivatives (dP/dt max) (r = 0.80), and end-systolic LV elastance (r = 0.73). Systolic vorticity and systolic vortex area were strongly correlated with ejection fraction (r = 0.76, 0.68) and dP/dt max (r = 0.76, 0.69), and end-systolic LV elastance (r = 0.62, 0.74), respectively. Systolic energy loss was strongly correlated with dP/dt max (r = 0.78), systolic maximum circulation (r = 0.81), and systolic vorticity (r = 0.82). The present study revealed that systolic VFM parameters are associated with the LV contractility. Furthermore, systolic energy loss was susceptible to the systolic vortex parameters such as systolic vorticity and systolic maximum circulation. Systolic VFM parameters are new hydrokinetic indices reflecting LV contractility.

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References

  1. Lu J, Li WH, Zhong Y, Luo AG, Xie SH, Yin LX (2012) Intuitive visualization and quantification of intraventricular convection in acute ischemic left ventricular failure during early diastole using color Doppler-based echocardiographic vector flow mapping. Int J Cardiovasc Imaging 28:1035–1047

    Article  CAS  PubMed  Google Scholar 

  2. Baccani B, Domenichini F, Pedrizzetti G, Tonti G (2002) Fluid dynamics of the left ventricular filling in dilated cardiomyopathy. J Biomech 35:665–671

    Article  PubMed  Google Scholar 

  3. Loerakker S, Cox LGE, van Heijst GJF, de Mol BAJM, van de Vosse FN (2008) Influence of dilated cardiomyopathy and a left ventricular assist device on vortex dynamics in the left ventricle. Comput Methods Biomech Biomed Eng 11:649–660

    Article  CAS  Google Scholar 

  4. Zhang HB, Zhang J, Zhu XX, Chen LL, Liu LW, Duan YY, Yu M, Zhou XD, Zhu T, Zhu MZ, Li HL (2012) The Left Ventricular intracavitary vortex during the isovolumic contraction period as detected by vector flow mapping. Echocardiography 29:579–587

    Article  PubMed  Google Scholar 

  5. Kheradvar A, Houle H, Pedrizzetti G, Tonti G, Belcik T, Ashraf M, Lindner JR, Gharib M, Sahn D (2010) Echocardiographic particle image velocimetry: a novel technique for quantification of left ventricular blood vorticity pattern. J Am Soc Echocardiogr 23:86–94

    Article  PubMed  Google Scholar 

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

    Article  Google Scholar 

  7. Mehregan F, Tournoux F, Muth S, Pibarot P, Rieu R, Cloutier G, Garcia D (2014) Doppler vortography: a Color Doppler approach to quantification of intraventricular blood flow vortices. Ultrasound Med Biol 40:210–221

    Article  PubMed  Google Scholar 

  8. Kvitting JPE, Ebbers T, Wigstrom L, Engvall J, Olin CL, Bolger AF (2004) Flow patterns in the aortic root and the aorta studied with time-resolved, 3-dimensional, phase-contrast magnetic resonance imaging: implications for aortic valve-sparing surgery. J Thorac Cardiovasc Surg 127:1602–1607

    Article  PubMed  Google Scholar 

  9. Ishizu T, Seo Y, Ishimitsu T, Obara K, Moriyama N, Kawano S, Watanabe S, Yamaguchi I (2006) The wake of a large vortex is associated with intraventricular filling delay in impaired left ventricles with a pseudonormalized transmitral flow pattern. Echocardiography 23:369–375

    Article  PubMed  Google Scholar 

  10. Kheradvar A, Gharib M (2009) On mitral valve dynamics and its connection to early diastolic flow. Ann Biomed Eng 37:1–13

    Article  PubMed  Google Scholar 

  11. Kheradvar A, Milano M, Gharib M (2007) Correlation between vortex ring formation and mitral annulus dynamics during ventricular rapid filling. ASAIO J 53:8–16

    Article  PubMed  Google Scholar 

  12. Zhang H, Liu L, Chen L, Ma N, Zhou L, Liu Y, Li Z, Liu C, Hou R, Zhu S (2013) The evolution of intraventricular vortex during ejection studied by using vector flow mapping. Echocardiography 30:27–36

    Article  PubMed  Google Scholar 

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

    Article  Google Scholar 

  14. Munoz DR, Mur JLM, Fernandez-Golfin C, Becker DC, Gomez A, Santos SF, Rivera CL, Diaz LMR, Rojo EC, Gomez JLZ (2015) Left ventricular vortices as observed by vector flow mapping: main determinants and their relation to left ventricular filling. Echocardiography 32:96–105

    Article  Google Scholar 

  15. Hayashi T, Itatani K, Inuzuka R, Shimizu N, Shindo T, Hirata Y, Miyaji K (2015) Dissipative energy loss within the left ventricle detected by vector flow mapping in children: normal values and effects of age and heart rate. J Cardiol 66:403–410

    Article  PubMed  Google Scholar 

  16. Garcia D, Pibarot P, Dumesnil JG, Sakr F, Durand LG (2000) Assessment of aortic valve stenosis severity—a new index based on the energy loss concept. Circulation 101:765–771

    Article  CAS  PubMed  Google Scholar 

  17. Baan J, van der Velde ET, de Bruin HG, Smeenk GJ, Koops J, van Dijk AD, Temmerman D, Senden J, Buis B (1984) Continuous measurement of left ventricular volume in animals and humans by conductance catheter. Circulation 70:812–823

    Article  CAS  PubMed  Google Scholar 

  18. Steendijk P, Staal E, Jukema JW, Baan J (2001) Hypertonic saline method accurately determines parallel conductance for dual-field conductance catheter. Am J Physiol-Heart Circ Physiol 281:H755–H763

    Article  CAS  PubMed  Google Scholar 

  19. Fukuda N, Itatani K, Kimura K, Ebihara A, Negishi K, Uno K, Miyaji K, Kurabayashi M (2001) Takenaka K (2014) Prolonged vortex formation during the ejection period in the left ventricle with low ejection fraction: a study by vector flow mapping. J Med Ultrasonics 41:301–310

    Article  Google Scholar 

  20. Suzuki H, Shimano M, Yoshida Y, Inden Y, Muramatsu T, Tsuji Y, Tsuboi N, Hirayama H, Shibata R, Murohara T (2010) Maximum derivative of left ventricular pressure predicts cardiac mortality after cardiac resynchronization therapy. Clin Cardiol 33:E18–E23

    Article  PubMed  Google Scholar 

  21. Kohno F, Kumada T, Kambayashi M, Hayashida W, Ishikawa N, Sasayama S (1996) Change in aortic end-systolic pressure by alterations in loading sequence and its relation to left ventricular isovolumic relaxation. Circulation 93:2080–2087

    Article  CAS  PubMed  Google Scholar 

  22. Sengupta PP, Khandheria BK, Korinek J, Wang J, Jahangir A, Seward JB, Belohlavek M (2006) Apex-to-base dispersion in regional timing of left ventricular shortening and lengthening. J Am Coll Cardiol 47:163–172

    Article  PubMed  Google Scholar 

  23. Kroeker CA, Tyberg JV, Beyar R (1995) Effects of ischemia on left ventricular apex rotation. An experimental study in anesthetized dogs. Circulation 92:3539–3548

    Article  CAS  PubMed  Google Scholar 

  24. Taber LA, Yang M, Podszus WW (1996) Mechanics of ventricular torsion. J Biomech 29:745–752

    Article  CAS  PubMed  Google Scholar 

  25. Davis JS, Hassanzadeh S, Winitsky S, Lin H, Satorius C, Vemuri R, Aletras AH, Wen H, Epstein ND (2001) The overall pattern of cardiac contraction depends on a spatial gradient of myosin regulatory light chain phosphorylation. Cell 107:631–641

    Article  CAS  PubMed  Google Scholar 

  26. Kim WJ, Lee BH, Kim YJ, Kang JH, Jung YJ, Song JM, Kang DH, Song JK (2009) Apical rotation assessed by speckle-tracking echocardiography as an index of global left ventricular contractility. Circ Cardiovasc Imaging 2:123–131

    Article  PubMed  Google Scholar 

  27. Sengupta PP, Pedrizzetti G, Kilner PJ, Kheradvar A, Ebbers T, Tonti G, Fraser AG, Narula J (2012) Emerging trends in CV flow visualization. JACC Cardiovasc Imaging 5:305–316

    Article  PubMed  Google Scholar 

  28. Hong GR, Pedrizzetti G, Tonti G, Li P, Wei Z, Kim JK, Baweja A, Liu S, Chung N, Houle H, Narula J, Vannan MA (2008) Characterization and quantification of vortex flow in the human left ventricle by contrast echocardiography using vector particle image velocimetry. JACC Cardiovasc Imaging 1:705–717

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bot H, Verburg J, Delemarre BJ, Strackee J (1990) Determinants of the occurrence of vortex rings in the left-ventricle during diastole. J Biomech 23:607–615

    Article  CAS  PubMed  Google Scholar 

  30. Houston JG, Gandy SJ, Sheppard DG, Dick JB, Belch JJ, Stonebridge PA (2003) Two-dimensional flow quantitative MRI of aortic arch blood flow patterns: effect of age, sex, and presence of carotid atheromatous disease on prevalence of spiral blood flow. J Magn Reson Imaging 18:169–174

    Article  PubMed  Google Scholar 

  31. Houston JG, Gandy SJ, Milne W, Dick JB, Belch JJ, Stonebridge PA (2004) Spiral laminar flow in the abdominal aorta: a predictor of renal impairment deterioration in patients with renal artery stenosis? Nephrol Dial Transplant 19:1786–1791

    Article  PubMed  Google Scholar 

  32. Honda T, Itatani K, Takanashi M, Mineo E, Kitagawa A, Ando H, Kimura S, Nakahata Y, Oka N, Miyaji K, Ishii M (2014) Quantitative evaluation of hemodynamics in the fontan circulation: a cross-sectional study measuring energy loss in vivo. Pediatr Cardiol 35:361–367

    Article  PubMed  Google Scholar 

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Correspondence to Seijirow Goya.

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Conflict of interest

The authors declare that there is no conflict of interest.

Funding

This research received no specific Grant from any funding agency in the public, commercial, or not-for-profit sectors.

Ethical approval

During the study, the dogs were managed and cared for in accordance with the standards established by the Tokyo University of Agriculture and Technology (TUAT) and described in its ‘‘Guide for the Care and Use of Laboratory Animals”. This study was approved by the Experimental Animal Committee of TUAT (Acceptance No. 26-95).

Electronic supplementary material

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Online Resource 1. Intra-ventricular hemodynamics during one cardiac cycle in isoflurane-anesthetized dogs was recorded by VFM. Red circles show the occurred vortex. Circulation and vortex area are automatically calculated and displayed on the upper left of the screen (MP4 1817 kb)

Appendix

Appendix

$$ ``{\text{Vorticity}}{\mkern 1mu} (\omega ) = \left( {\begin{array}{*{20}c} {\frac{\partial w}{\partial y} - \frac{\partial v}{\partial z}} \\ {\frac{\partial u}{\partial z} - \frac{\partial w}{\partial x}} \\ {\frac{\partial v}{\partial x} - \frac{\partial u}{\partial y}} \\ \end{array} } \right)" $$

u, v, w is the velocity components in x, y, z axes directions, respectively.

In 2D flow with w = 0,

$$ \begin{aligned} {\text{Vorticity}}{\mkern 1mu} (\omega ) & = \frac{\partial v}{\partial x} - \frac{\partial u}{\partial y} \\ `` {\text{Circulation}} & = \iint_{s} {\omega_{n} {\text{d}}S}" \\ \end{aligned} $$

S is the arbitrary curved surface surrounded by a closed curve; \( \omega_{n} \) is the normal component of vorticity \( \omega \).

$$`` {\text{Energy loss }} = \int {\mu \frac{1}{2}\sum\limits_{i,j } {\left( {\frac{{\partial u_{i} }}{{\partial x_{j} }} + \frac{{\partial u_{j} }}{{\partial x_{i} }}} \right)^{2} } {\text{d}}v} = \mu \int {\left( {2\frac{\partial u}{\partial x}^{2} + \left( {\frac{\partial u}{\partial y} + \frac{\partial v}{\partial x}} \right)^{2} + 2\frac{\partial v}{\partial y}^{2} } \right){\text{d}}v} " $$

μ is the coefficient of blood viscosity; u, v is the velocity components in x, y axes directions, respectively.

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Goya, S., Wada, T., Shimada, K. et al. The relationship between systolic vector flow mapping parameters and left ventricular cardiac function in healthy dogs. Heart Vessels 33, 549–560 (2018). https://doi.org/10.1007/s00380-017-1093-1

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