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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

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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.

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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

References

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  Google Scholar 

  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

    Article  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  CAS  Google Scholar 

  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

    Article  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  CAS  PubMed  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  PubMed Central  Google Scholar 

  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

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Cardiovascular Medicine, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, 48149, Münster, Germany

    Michael Bietenbeck, Anca Florian, Zornitsa Shomanova, Claudia Meier & Ali Yilmaz

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  1. Michael Bietenbeck
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  2. Anca Florian
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  3. Zornitsa Shomanova
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  4. Claudia Meier
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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.

Corresponding author

Correspondence to Ali Yilmaz.

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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.

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Bietenbeck, M., Florian, A., Shomanova, Z. et al. 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. Clin Res Cardiol 107, 1062–1070 (2018). https://doi.org/10.1007/s00392-018-1279-2

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