Advertisement

Reduced global myocardial perfusion reserve in DCM and HCM patients assessed by CMR-based velocity-encoded coronary sinus flow measurements and first-pass perfusion imaging

  • Michael Bietenbeck
  • Anca Florian
  • Zornitsa Shomanova
  • Claudia Meier
  • Ali Yilmaz
Original Paper

Abstract

Background

Coronary microvascular dysfunction (CMD) is an independent predictor of poor prognosis in patients suffering from dilative or hypertrophic cardiomyopathy (DCM/HCM). To assess CMD, quantitative myocardial first-pass perfusion (1P) cardiovascular magnetic resonance (CMR) can be performed. Coronary sinus flow (CSF) measurements at rest and during maximal vasodilatation are an alternative and well-validated approach for the quantification of global myocardial blood flow (MBF) in CMR.

Methods

Global myocardial perfusion reserve (MPR) was used to compare both methods, 1P and CSF. This measure reflects the ratio of myocardial blood flow during maximal coronary vasodilatation over rest. 1P-MPR and CSF-MPR were calculated in 17 HCM patients, 14 DCM patients and 16 controls, who underwent a stress CMR study to rule out obstructive coronary artery disease. All patients were examined on a 1.5-T system and the study protocol comprised both, first-pass myocardial perfusion imaging (MPI) and velocity-encoded (VENC) phase-contrast imaging of CSF during rest and adenosine stress.

Results

1P-MPR was significantly decreased only in HCM patients compared to controls (1.14 vs. 1.43, p = 0.045) whereas CSF-MPR was significantly reduced in both patient groups, HCM and DCM, compared to controls (2.38 and 2.07 vs. 3.18, p = 0.041 and p = 0.032). CSF-MBF at maximal stress was significantly lower in HCM and DCM patients compared to the control group (0.11 and 1.23 vs. 1.58 ml/min/g, p = 0.008 and p = 0.040). A moderate but significant correlation between CSF-MPR and 1P-MPR was observed (r = 0.39, p = 0.011). A negative correlation between LV wall thickness and CSF-MBF at rest and stress was found in the DCM group using VENC-based CSF measurements (r = − 0.64, p = 0.013 and r = − 0.69, p = 0.006)—but not using 1P-MPI. Post-proceeding analysis regarding 1P-MPR and CSF-MPR measurements required 20.1 and 6.5 min, respectively (p < 0.001).

Conclusion

The presence of microvascular disease can be non-invasively and quickly detected by VENC-based CSF-MPR measurements during routine stress perfusion CMR in both HCM and DCM patients. Compared to conventional 1P-MPI, VENC-based CSF-MPR is particularly useful in DCM patients with thinned ventricular walls.

Keywords

Myocardial perfusion CMR Coronary sinus flow HCM DCM 

Abbreviations

CMR

Cardiovascular magnetic resonance

DCM

Dilative cardiomyopathy

LGE

Late-gadolinium-enhancement

LV

Left ventricle

LV-EDV

Left ventricular end-diastolic volume

LV-EF

Left ventricular ejection fraction

SSFP

Steady-state-free-precession

IQR

Interquartile range

CAD

Coronary artery disease

MPI

Myocardial perfusion imaging

BW

Body weight

ROI

Region of interest

RPP

Rate pressure product

MACE

Major cardiac events

CMD

Microvascular dysfunction

MPR

Myocardial perfusion reserve

CSF

Coronary sinus flow

1P

First-pass perfusion

MBF

Myocardial blood flow

VENC

Velocity encoding

Notes

Author contributions

MB participated in the CMR exams, carried out the data and statistical analysis, and wrote the initial draft version of the manuscript. AF participated in the CMR exams and in the analysis of the CMR data. CM and ZS critically reviewed the manuscript. AY supervised the study, critically reviewed the manuscript and drafted the manuscript. All authors read and approved the final manuscript.

Funding

None.

Compliance with ethical standards

Conflict of interest

The author declares that there is no competing interest.

Ethics approval and consent to participate

The study protocol complies with the Declaration of Helsinki. Written informed consent was obtained from every patient.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. 1.
    Cecchi F, Olivotto I, Gistri R, Lorenzoni R, Chiriatti G, Camici PG (2003) Coronary microvascular dysfunction and prognosis in hypertrophic cardiomyopathy. N Engl J Med 349:1027–1035.  https://doi.org/10.1056/NEJMoa025050 CrossRefPubMedGoogle Scholar
  2. 2.
    Neglia D, Michelassi C, Giovanna Trivieri M, Sambuceti G, Giorgetti A, Pratali L et al (2002) Prognostic role of myocardial blood flow impairment in idiopathic left ventricular dysfunction. Circulation 105:186–193.  https://doi.org/10.1161/hc0202.102119 CrossRefPubMedGoogle Scholar
  3. 3.
    Crea F, Camici PG, Merz CNB (2014) Coronary microvascular dysfunction: an update. Eur Heart J 35:1101–1111.  https://doi.org/10.1093/eurheartj/eht513 CrossRefPubMedGoogle Scholar
  4. 4.
    Shome JS, Perera D, Plein S, Chiribiri A (2017) Current perspectives in coronary microvascular dysfunction. Microcirculation 24:e12340.  https://doi.org/10.1111/micc.12340 CrossRefGoogle Scholar
  5. 5.
    Panting JR, Gatehouse PD, Yang G-Z, Grothues F, Firmin DN, Collins P et al (2002) Abnormal subendocardial perfusion in cardiac syndrome X detected by cardiovascular magnetic resonance imaging. N Engl J Med 346:1948–1953.  https://doi.org/10.1056/NEJMoa012369 CrossRefPubMedGoogle Scholar
  6. 6.
    Vermeltfoort IAC, Bondarenko O, Raijmakers PGHM., Odekerken DAM, Kuijper AFM, Zwijnenburg A et al (2007) Is subendocardial ischaemia present in patients with chest pain and normal coronary angiograms? A cardiovascular MR study. Eur Heart J 28:1554–1558.  https://doi.org/10.1093/eurheartj/ehm088 CrossRefPubMedGoogle Scholar
  7. 7.
    Pack NA, DiBella EVR (2010) Comparison of myocardial perfusion estimates from dynamic contrast-enhanced magnetic resonance imaging with four quantitative analysis methods. Magn Reson Med 64:125–137.  https://doi.org/10.1002/mrm.22282 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Salerno M, Beller GA (2009) Noninvasive assessment of myocardial perfusion. Circ Cardiovasc Imaging 2:412–424.  https://doi.org/10.1161/CIRCIMAGING.109.854893 CrossRefPubMedGoogle Scholar
  9. 9.
    Mordini FE, Haddad T, Hsu L-Y, Kellman P, Lowrey TB, Aletras AH et al (2014) Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment. JACC Cardiovasc Imaging 7:14–22.  https://doi.org/10.1016/J.JCMG.2013.08.014 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Koskenvuo JW, Sakuma H, Niemi P, Toikka JO, Knuuti J, Laine H et al (2001) Global myocardial blood flow and global flow reserve measurements by MRI and PET are comparable. J Magn Reson Imaging 13:361–366.  https://doi.org/10.1002/jmri.1051 CrossRefPubMedGoogle Scholar
  11. 11.
    Kato S, Saito N, Nakachi T, Fukui K, Iwasawa T, Taguri M et al (2017) Stress perfusion coronary flow reserve versus cardiac magnetic resonance for known or suspected CAD. J Am Coll Cardiol 70:869–879.  https://doi.org/10.1016/J.JACC.2017.06.028 CrossRefPubMedGoogle Scholar
  12. 12.
    Shomanova Z, Florian A, Bietenbeck M, Waltenberger J, Sechtem U, Yilmaz A (2017) Diagnostic value of global myocardial perfusion reserve assessment based on coronary sinus flow measurements using cardiovascular magnetic resonance in addition to myocardial stress perfusion imaging. Eur Hear J Cardiovasc Imaging 18:851–859.  https://doi.org/10.1093/ehjci/jew315 CrossRefGoogle Scholar
  13. 13.
    Schwitter J, DeMarco T, Kneifel S, von Schulthess GK, Jorg MC, Arheden H et al (2000) Magnetic resonance-based assessment of global coronary flow and flow reserve and its relation to left ventricular functional parameters: a comparison with positron emission tomography. Circulation 101:2696–2702.  https://doi.org/10.1161/01.CIR.101.23.2696 CrossRefPubMedGoogle Scholar
  14. 14.
    van Rossum AC, Visser FC, Hofman MB, Galjee MA, Westerhof N, Valk J (1992) Global left ventricular perfusion: noninvasive measurement with cine MR imaging and phase velocity mapping of coronary venous outflow. Radiology 182:685–691.  https://doi.org/10.1148/radiology.182.3.1535881 CrossRefPubMedGoogle Scholar
  15. 15.
    Coelho-Filho OR, Rickers C, Kwong RY, Jerosch-Herold M (2013) MR myocardial perfusion imaging. Radiology 266:701–715.  https://doi.org/10.1148/radiol.12110918 CrossRefPubMedGoogle Scholar
  16. 16.
    Doesch C, Seeger A, Hoevelborn T, Klumpp B, Fenchel M, Kramer U et al (2008) Adenosine stress cardiac magnetic resonance imaging for the assessment of ischemic heart disease. Clin Res Cardiol 97:905–912.  https://doi.org/10.1007/s00392-008-0708-z CrossRefPubMedGoogle Scholar
  17. 17.
    Kato S, Saito N, Kirigaya H, Gyotoku D, Iinuma N, Kusakawa Y et al (2016) Impairment of coronary flow reserve evaluated by phase contrast cine-magnetic resonance imaging in patients with heart failure with preserved ejection fraction. J Am Heart Assoc.  https://doi.org/10.1161/JAHA.115.002649 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Knaapen P, Lubberink M (2008) Cardiac positron emission tomography: myocardial perfusion and metabolism in clinical practice. Clin Res Cardiol 97:791–796.  https://doi.org/10.1007/s00392-008-0662-9 CrossRefPubMedGoogle Scholar
  19. 19.
    Maddahi J, Packard RRS (2014) Cardiac PET perfusion tracers: current status and future directions. Semin Nucl Med 44:333–343.  https://doi.org/10.1053/j.semnuclmed.2014.06.011 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Kellman P, Hansen MS, Nielles-Vallespin S, Nickander J, Themudo R, Ugander M et al (2017) Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification. J Cardiovasc Magn Reson.  https://doi.org/10.1186/s12968-017-0355-5 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Lee DC, Johnson NP (2009) Quantification of absolute myocardial blood flow by magnetic resonance perfusion imaging. JACC Cardiovasc Imaging 2:761–770.  https://doi.org/10.1016/J.JCMG.2009.04.003 CrossRefPubMedGoogle Scholar
  22. 22.
    Kawada N, Sakuma H, Yamakado T, Takeda K, Isaka N, Nakano T et al (1999) Hypertrophic cardiomyopathy: MR measurement of coronary blood flow and vasodilator flow reserve in patients and healthy subjects. Radiology 211:129–135.  https://doi.org/10.1148/radiology.211.1.r99ap36129 CrossRefPubMedGoogle Scholar
  23. 23.
    Karamitsos TD, Dass S, Suttie J, Sever E, Birks J, Holloway CJ et al (2013) Blunted myocardial oxygenation response during vasodilator stress in patients with hypertrophic cardiomyopathy. J Am Coll Cardiol 61:1169–1176.  https://doi.org/10.1016/j.jacc.2012.12.024 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Watzinger N, Lund GK, Saeed M, Reddy GP, Araoz PA, Yang M et al (2005) Myocardial blood flow in patients with dilated cardiomyopathy: Quantitative assessment with velocity-encoded cine magnetic resonance imaging of the coronary sinus. J Magn Reson Imaging 21:347–353.  https://doi.org/10.1002/jmri.20274 CrossRefPubMedGoogle Scholar
  25. 25.
    Dass S, Holloway CJ, Cochlin LE, Rider OJ, Mahmod M, Robson M et al (2015) No evidence of myocardial oxygen deprivation in nonischemic heart failure. Circ Hear Fail 8:1088–1093.  https://doi.org/10.1161/CIRCHEARTFAILURE.114.002169 CrossRefGoogle Scholar
  26. 26.
    Bratis K, Child N, Terrovitis J, Nanas J, Felekos I, Aggeli C et al (2014) Coronary microvascular dysfunction in overt diabetic cardiomyopathy. IJC Metab Endocr 5:19–23.  https://doi.org/10.1016/j.ijcme.2014.08.007 CrossRefGoogle Scholar
  27. 27.
    Opherk D, Schwarz F, Mall G, Manthey J, Baller D, Kübler W (1983) Coronary dilatory capacity in idiopathic dilated cardiomyopathy: Analysis of 16 patients. Am J Cardiol 51:1657–1662.  https://doi.org/10.1016/0002-9149(83)90205-9 CrossRefPubMedGoogle Scholar
  28. 28.
    Stolen KQ, Kemppainen J, Kalliokoski KK, Karanko H, Toikka J, Janatuinen T et al (2004) Myocardial perfusion reserve and peripheral endothelial function in patients with idiopathic dilated cardiomyopathy. Am J Cardiol 93:64–68.  https://doi.org/10.1016/j.amjcard.2003.08.074 CrossRefPubMedGoogle Scholar
  29. 29.
    Dimitrow PP, Galderisi M, Rigo F (2005) The non-invasive documentation of coronary microcirculation impairment: role of transthoracic echocardiography. Cardiovasc Ultrasound 3:18.  https://doi.org/10.1186/1476-7120-3-18 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Mathier MA, Rose GA, Fifer MA, Miyamoto MI, Dinsmore RE, Casta OHH et al (1998) Coronary endothelial dysfunction in patients with acute-onset idiopathic dilated cardiomyopathy. J Am Coll Cardiol 32:216–224.  https://doi.org/10.1016/S0735-1097(98)00209-5 CrossRefPubMedGoogle Scholar
  31. 31.
    Abraham D, Hofbauer R, Schäfer R, Blumer R, Paulus P, Miksovsky A et al (2000) Selective downregulation of VEGF-A(165), VEGF-R(1), and decreased capillary density in patients with dilative but not ischemic cardiomyopathy. Circ Res 87:644–647.  https://doi.org/10.1161/01.RES.87.8.644 CrossRefPubMedGoogle Scholar
  32. 32.
    Luk A, Ahn E, Soor GS, Butany J (2009) Dilated cardiomyopathy: a review. J Clin Pathol 62:219–225.  https://doi.org/10.1136/jcp.2008.060731 CrossRefPubMedGoogle Scholar
  33. 33.
    Sammut E, Zarinabad N, Wesolowski R, Morton G, Chen Z, Sohal M et al (2015) Feasibility of high-resolution quantitative perfusion analysis in patients with heart failure. J Cardiovasc Magn Reson 17:13.  https://doi.org/10.1186/s12968-015-0124-2 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Feher A, Sinusas AJ (2017) Quantitative assessment of coronary microvascular function. Circ Cardiovasc Imaging 10:e006427.  https://doi.org/10.1161/CIRCIMAGING.117.006427 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Merkle N, Wöhrle J, Nusser T, Grebe O, Spiess J, Torzewski J et al (2010) Diagnostic performance of magnetic resonance first pass perfusion imaging is equally potent in female compared to male patients with coronary artery disease. Clin Res Cardiol 99:21–28.  https://doi.org/10.1007/s00392-009-0071-8 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Cardiovascular MedicineUniversity Hospital MünsterMünsterGermany

Personalised recommendations