Journal of Nuclear Cardiology

, Volume 24, Issue 2, pp 494–501 | Cite as

Quantitative relationship between coronary artery calcium and myocardial blood flow by hybrid rubidium-82 PET/CT imaging in patients with suspected coronary artery disease

  • Roberta Assante
  • Emilia Zampella
  • Parthiban Arumugam
  • Wanda Acampa
  • Massimo Imbriaco
  • Deborah Tout
  • Mario Petretta
  • Christine Tonge
  • Alberto Cuocolo
Original Article

Abstract

Background

We assessed the relationship between coronary artery calcium (CAC) score, myocardial blood flow (MBF) and coronary flow reserve (CFR) in patients undergoing hybrid 82Rb positron emission tomography (PET)/computed tomography (CT) imaging for suspected CAD. We also evaluated if CAC score is able to predict a reduced CFR independently from conventional coronary risk factors.

Methods

A total of 637 (mean age 58 ± 13 years) consecutive patients were studied. CAC score was measured according to the Agatston method and patients were categorized into 4 groups (0, 0.01-99.9, 100-399.9, and ≥400). Baseline and hyperemic MBF were automatically quantified. CFR was calculated as the ratio of hyperemic to baseline MBF and it was considered reduced when <2.

Results

Global CAC score showed a significant inverse correlation with hyperemic MBF and CFR (both P < .001), while no correlation between CAC score and baseline MBF was found. At multivariable logistic regression analysis age, diabetes and CAC score were independently associated with reduced CFR (all P < .001). The addition of CAC score to clinical data increased the global chi-square value for predicting reduced CFR from 81.01 to 91.13 (P < .01). Continuous net reclassification improvement, obtained by adding CAC score to clinical data, was 0.36.

Conclusions

CAC score provides incremental information about coronary vascular function over established CAD risk factors in patients with suspected CAD and it might be helpful for identifying those with a reduced CFR.

Keywords

Coronary artery calcium myocardial blood flow coronary flow reserve PET/CT coronary artery disease 

Abbreviations

CAC

Coronary artery calcium

CAD

Coronary artery disease

CFR

Coronary flow reserve

MBF

Myocardial blood flow

PET

Positron emission tomography

CT

Computed tomography

LAD

Left anterior descending artery

LCx

Left circumflex artery

RCA

Right coronary artery

Notes

Disclosure

The authors have indicated that they have no financial conflict of interest.

References

  1. 1.
    Rumberger JA, Simons DB, Fitzpatrick LA, Sheedy PF, Schwartz RS. Coronary artery calcium area by electron-beam computed tomography and coronary atherosclerotic plaque area. A histopathologic correlative study. Circulation 1995;92:2157-62.CrossRefPubMedGoogle Scholar
  2. 2.
    Nasir K, Clouse M. Role of nonenhanced multidetector CT coronary artery calcium testing in asymptomatic and symptomatic individuals. Radiology 2012;264:637-49.CrossRefPubMedGoogle Scholar
  3. 3.
    Burke AP, Weber DK, Kolodgie FD, Farb A, Taylor AJ, Virmani R. Pathophysiology of calcium deposition in coronary arteries. Herz 2001;26:239-44.CrossRefPubMedGoogle Scholar
  4. 4.
    Naya M, Murthy VL, Foster CR, Gaber M, Klein J, Hainer J, et al. Prognostic interplay of coronary artery calcification and underlying vascular dysfunction in patients with suspected coronary artery disease. J Am Coll Cardiol 2013;61:2098-106.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Curillova Z, Yaman BF, Dorbala S, Kwong RY, Sitek A, El Fakhri G, et al. Quantitative relationship between coronary calcium content and coronary flow reserve as assessed by integrated PET/CT imaging. Eur J Nucl Med Mol Imaging 2009;36:1603-10.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Wang L, Jerosch-Herold M, Jacobs DR Jr, Shahar E, Detrano R, Folsom AR, et al. Coronary artery calcification and myocardial perfusion in asymptomatic adults: The MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol 2006;48:1018-26.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Schindler TH, Facta AD, Prior JO, Cadenas J, Zhang XL, Li Y, et al. Structural alterations of the coronary arterial wall are associated with myocardial flow heterogeneity in type 2 diabetes mellitus. Eur J Nucl Med Mol Imaging 2009;36:219-29.CrossRefPubMedGoogle Scholar
  8. 8.
    Danad I, Raijmakers PG, Appelman YE, Harms HJ, de Haan S, Marques KM, et al. Quantitative relationship between coronary artery calcium score and hyperemic myocardial blood flow as assessed by hybrid 15O-water PET/CT imaging in patients evaluated for coronary artery disease. J Nucl Cardiol 2012;19:256-64.CrossRefPubMedGoogle Scholar
  9. 9.
    Rosendorff C, Black HR, Cannon CP, Gersh BJ, Gore J, Izzo JL Jr, et al. Treatment of hypertension in the prevention and management of ischemic heart disease: A scientific statement from the American Heart Association Council for High Blood Pressure Research and the Councils on Clinical Cardiology and Epidemiology and Prevention. Circulation 2007;115:2761-88.CrossRefPubMedGoogle Scholar
  10. 10.
    Klein R, Renaud JM, Ziadi MC, Thorn SL, Adler A, Beanlands RS, et al. Intra- and inter-operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-82 pet and a highly automated analysis program. J Nucl Cardiol 2010;17:600-16.CrossRefPubMedGoogle Scholar
  11. 11.
    Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Kaul S, Laskey WK, et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation 2002;105:539-42.CrossRefPubMedGoogle Scholar
  12. 12.
    Camici PG, Crea F. Coronary microvascular dysfunction. N Engl J Med 2007;356:830-40.CrossRefPubMedGoogle Scholar
  13. 13.
    Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990;15:827-32.CrossRefPubMedGoogle Scholar
  14. 14.
    Diamond GA, Staniloff HM, Forrester JS, Pollock BH, Swan HJ. Computer assisted diagnosis in the noninvasive evaluation of patients with suspected coronary artery disease. J Am Coll Cardiol 1983;1(2 Pt 1):444-55.CrossRefPubMedGoogle Scholar
  15. 15.
    Petretta M, Acampa W, Evangelista L, Daniele S, Ferro A, Cuocolo A, et al. Impact of inducible ischemia by stress SPECT in cardiac risk assessment in diabetic patients: Rationale and design of a prospective, multicenter trial. J Nucl Cardiol 2008;15:100-4.CrossRefPubMedGoogle Scholar
  16. 16.
    Pencina MJ, D’Agostino RB Sr, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011;30:11-21.CrossRefPubMedGoogle Scholar
  17. 17.
    Uren NG, Melin JA, De Bruyne B, Wijns W, Baudhuin T, Camici PG. Relation between myocardial blood flow and the severity of coronary-artery stenosis. N Engl J Med 1994;330:1782-8.CrossRefPubMedGoogle Scholar
  18. 18.
    Di Carli MF, Janisse J, Grunberger G, Ager J. Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol 2003;41:1387-93.CrossRefPubMedGoogle Scholar

Copyright information

© American Society of Nuclear Cardiology 2016

Authors and Affiliations

  • Roberta Assante
    • 1
  • Emilia Zampella
    • 1
  • Parthiban Arumugam
    • 2
  • Wanda Acampa
    • 1
    • 3
  • Massimo Imbriaco
    • 1
  • Deborah Tout
    • 2
  • Mario Petretta
    • 4
  • Christine Tonge
    • 2
  • Alberto Cuocolo
    • 1
  1. 1.Department of Advanced Biomedical SciencesUniversity Federico IINaplesItaly
  2. 2.Nuclear Medicine CenterCentral Manchester University Teaching HospitalsManchesterUK
  3. 3.Institute of Biostructure and BioimagingNational Council of ResearchNaplesItaly
  4. 4.Department of Translational Medical SciencesUniversity Federico IINaplesItaly

Personalised recommendations