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Abstract

Background

Myocardial perfusion reserve index (MPRI) and extracellular volume fraction (ECV) on cardiac magnetic resonance (CMR) are known to quantify coronary microvascular dysfunction and myocardial fibrosis, respectively.

Purpose

To demonstrate that cardiovascular risk factors such as hypertension, diabetes, hyperlipidemia, and smoking are correlated with MPRI and ECV on CMR in asymptomatic individuals.

Material and Methods

Between October 2013 and July 2014, 196 individuals underwent CMR. After excluding those with chest pain, arrhythmia, and obstructive coronary artery disease, participants were divided into five groups: those without risk factor (n = 26) and those with one (n = 43), two (n = 35), three (n = 24), or four (n = 6) risk factors. MPRI and ECV were obtained on perfusion CMR and pre- and post-T1 mapping, respectively.

Results

A total of 134 asymptomatic individuals (109 men, 25 women; mean age = 54.4 ± 7.08 years; body mass index [BMI] = 24.96 ± 2.76 kg/m²; Framingham risk score [FRS] = 7.71 ± 5.21) were included. The Jonckheere-Terpstra test demonstrated trends of increasing BMI, FRS, and left ventricular mass index (all P values < 0.001), but decreasing MPRI (P = 0.001) with increasing numbers of risk factors. Stepwise multiple linear regression demonstrated that an increasing number of cardiovascular risk factors was an independent predictor of MPRI (P = 0.001). However, there was no significant association between the number of risk factors and ECV (P = 0.99).

Conclusion

We demonstrated that an increasing number of cardiovascular risk factors is significantly associated with reduced MPRI, but not with ECV on CMR.

Keywords

Cardiac magnetic resonance myocardial perfusion reserve index extracellular volume fraction cardiovascular risk factor asymptomatic

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References

Cannon

3rd Epstein

. “Microvascular angina” as a cause of chest pain with angiographically normal coronary arteries. Am J Cardiol 1988; 61: 1338–1343.

Cox

Vita

Treasure

et al.

Atherosclerosis impairs flow-mediated dilation of coronary arteries in humans. Circulation 1989; 80: 458–465.

Thomson

Wei

Agarwal

et al.

Cardiac magnetic resonance myocardial perfusion reserve index is reduced in women with coronary microvascular dysfunction. A National Heart, Lung, and Blood Institute-sponsored study from the Women’s Ischemia Syndrome Evaluation. Circ Cardiovasc Imaging 2015; 8: 002481–002481.

Ahn

Kim

Park

et al.

Coronary microvascular dysfunction as a mechanism of angina in severe AS: prospective adenosine-stress CMR study. J Am Coll Cardiol 2016; 67: 1412–1422.

Schelbert

Messroghli

. State of the art: clinical applications of cardiac T1 mapping. Radiology 2016; 278: 658–676.

Fontana

White

Banypersad

et al.

Comparison of T1 mapping techniques for ECV quantification. Histological validation and reproducibility of ShMOLLI versus multibreath-hold T1 quantification equilibrium contrast CMR. J Cardiovasc Magn Reson 2012; 14: 88–88.

Crea

Camici

Bairey Merz

. Coronary microvascular dysfunction: an update. Eur Heart J 2014; 35: 1101–1111.

Moreau

d’Uscio

Luscher

. Structure and reactivity of small arteries in aging. Cardiovasc Res 1998; 37: 247–253.

Antony

Nitenberg

Foult

et al.

Coronary vasodilator reserve in untreated and treated hypertensive patients with and without left ventricular hypertrophy. J Am Coll Cardiol 1993; 22: 514–520.

10.

Nahser

Jr Brown

Oskarsson

et al.

Maximal coronary flow reserve and metabolic coronary vasodilation in patients with diabetes mellitus. Circulation 1995; 91: 635–640.

11.

Pitt

Zannad

. The detection of myocardial fibrosis: an opportunity to reduce cardiovascular risk in patients with diabetes mellitus? Circ Cardiovasc Imaging 2012; 5: 9–11.

12.

Kaufmann

Gnecchi-Ruscone

Schafers

et al.

Low density lipoprotein cholesterol and coronary microvascular dysfunction in hypercholesterolemia. J Am Coll Cardiol 2000; 36: 103–109.

13.

Goette

Lendeckel

Kuchenbecker

et al.

Cigarette smoking induces atrial fibrosis in humans via nicotine. Heart 2007; 93: 1056–1063.

14.

Kellman

Arai

Xue

. T1 and extracellular volume mapping in the heart: estimation of error maps and the influence of noise on precision. J Cardiovasc Magn Reson 2013; 15: 56–56.

15.

Kellman

Hansen

. T1-mapping in the heart: accuracy and precision. J Cardiovasc Magn Reson 2014; 16: 2–2.

16.

Diesbourg

Prato

Wisenberg

et al.

Quantification of myocardial blood flow and extracellular volumes using a bolus injection of Gd-DTPA: kinetic modeling in canine ischemic disease. Magn Reson Med 1992; 23: 239–253.

17.

Arheden

Saeed

Higgins

et al.

Measurement of the distribution volume of gadopentetate dimeglumine at echo-planar MR imaging to quantify myocardial infarction: comparison with 99mTc-DTPA autoradiography in rats. Radiology 1999; 211: 698–708.

18.

Arheden

Saeed

Higgins

et al.

Reperfused rat myocardium subjected to various durations of ischemia: estimation of the distribution volume of contrast material with echo-planar MR imaging. Radiology 2000; 215: 520–528.

19.

Olivotto

Maron

Autore

et al.

Assessment and significance of left ventricular mass by cardiovascular magnetic resonance in hypertrophic cardiomyopathy. J Am Coll Cardiol 2008; 52: 559–566.

20.

Kuruvilla

Janardhanan

Antkowiak

et al.

Increased extracellular volume and altered mechanics are associated with LVH in hypertensive heart disease, not hypertension alone. JACC Cardiovasc Imaging 2015; 8: 172–180.

21.

Wang

Jerosch-Herold

Jacobs

Jr et al.

Coronary risk factors and myocardial perfusion in asymptomatic adults: the Multi-Ethnic Study of Atherosclerosis (MESA). J Am Coll Cardiol 2006; 47: 565–572.

22.

Kannel

McGee

Gordon

. A general cardiovascular risk profile: the Framingham Study. Am J Cardiol 1976; 38: 46–51.

23.

D’Agostino

Sr. Grundy

Sullivan

et al.

Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001; 286: 180–187.

24.

Rodondi

Locatelli

Aujesky

et al.

Framingham risk score and alternatives for prediction of coronary heart disease in older adults. PLoS One 2012; 7: e34287–e34287.

25.

Tzoulaki

Liberopoulos

Ioannidis

. Assessment of claims of improved prediction beyond the Framingham risk score. JAMA 2009; 302: 2345–2352.

26.

Greenland

LaBree

Azen

et al.

Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA 2004; 291: 210–215.

27.

Morton

Chiribiri

Ishida

et al.

Quantification of absolute myocardial perfusion in patients with coronary artery disease: comparison between cardiovascular magnetic resonance and positron emission tomography. J Am Coll Cardiol 2012; 60: 1546–1555.

28.

Shomanova

Florian

Bietenbeck

et al.

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 Heart J Cardiovasc Imaging 2017; 18: 851–859.

29.

Bairey Merz

Handberg

Shufelt

et al.

A randomized, placebo-controlled trial of late Na current inhibition (ranolazine) in coronary microvascular dysfunction (CMD): impact on angina and myocardial perfusion reserve. Eur Heart J 2016; 37: 1504–1513.

30.

Wolff

Schwitter

Coulden

et al.

Myocardial first-pass perfusion magnetic resonance imaging: a multicenter dose-ranging study. Circulation 2004; 110: 732–737.

31.

Utz

Niendorf

Wassmuth

et al.

Contrast-dose relation in first-pass myocardial MR perfusion imaging. J Magn Reson Imaging 2007; 25: 1131–1135.

32.

Gerber

Raman

Nayak

et al.

Myocardial first-pass perfusion cardiovascular magnetic resonance: history, theory, and current state of the art. J Cardiovasc Magn Reson 2008; 10: 18–18.

33.

Steadman

Jerosch-Herold

Grundy

et al.

Determinants and functional significance of myocardial perfusion reserve in severe aortic stenosis. JACC Cardiovasc Imaging 2012; 5: 182–189.

34.

Tee

et al.

The association between cardiovascular risk and cardiovascular magnetic resonance measures of fibrosis: the Multi-Ethnic Study of Atherosclerosis (MESA). J Cardiovasc Magn Reson 2015; 17: 15–15.

35.

Duvernoy

Meyer

Seifert-Klauss

et al.

Gender differences in myocardial blood flow dynamics: lipid profile and hemodynamic effects. J Am Coll Cardiol 1999; 33: 463–470.

36.

Nham

Kim

Lee

et al.

Association of cardiovascular disease risk factors with left ventricular mass, biventricular function, and the presence of silent myocardial infarction on cardiac MRI in an asymptomatic population. Int J Cardiovasc Imaging 2016; 32(Suppl 1): 173–181.

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Association of cardiovascular risk factors on myocardial perfusion and fibrosis in asymptomatic individuals: cardiac magnetic resonance study

Abstract

Background

Purpose

Material and Methods

Results

Conclusion

Keywords

Get full access to this article

References

Supplementary Material