Skip to main content
SpringerLink
Log in

Prognostic value of atherosclerotic burden and coronary vascular function in patients with suspected coronary artery disease

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

To evaluate the prognostic value of coronary atherosclerotic burden, assessed by coronary artery calcium (CAC) score, and coronary vascular function, assessed by coronary flow reserve (CFR) in patients with suspected coronary artery disease (CAD).

Methods

We studied 436 patients undergoing hybrid 82Rb positron emission tomography/computed tomography imaging. CAC score was measured according to the Agatston method, and patients were categorized into three groups (0, <400, and ≥400). CFR was calculated as the ratio of hyperemic to baseline myocardial blood flow, and it was considered reduced when <2.

Results

Follow-up was 94% complete during a mean period of 47±15 months. During follow-up, 17 events occurred (4% cumulative event rate). Event-free survival decreased with worsening of CAC score category (p < 0.001) and in patients with reduced CFR (p < 0.005). At multivariable analysis, CAC score ≥400 (p < 0.01) and CFR (p < 0.005) were independent predictors of events. Including CFR in the prognostic model, continuous net reclassification improvement was 0.51 (0.14 in patients with events and 0.37 in those without). At classification and regression tree analysis, the initial split was on CAC score. For patients with a CAC score < 400, no further split was performed, while patients with a CAC score ≥400 were further stratified by CFR values. Decision curve analyses indicate that the model including CFR resulted in a higher net benefit across a wide range of decision threshold probabilities.

Conclusions

In patients with suspected CAD, CFR provides significant incremental risk stratification over established cardiac risk factors and CAC score for prediction of adverse cardiac events.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Berman DS, Hachamovitch R, Shaw LJ, Friedman JD, Hayes SW, Thomson LE, et al. Roles of nuclear cardiology, cardiac computed tomography, and cardiac magnetic resonance: Noninvasive risk stratification and a conceptual framework for the selection of noninvasive imaging tests in patients with known or suspected coronary artery disease. J Nucl Med. 2006;47:1107–18.

    PubMed  Google Scholar 

  2. Lee H, Yoon YE, Park JB, Kim HL, Park HE, Lee SP, et al. The incremental prognostic value of cardiac computed tomography in comparison with single-photon emission computed tomography in patients with suspected coronary artery disease. PLoS One. 2016;11:e0160188.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Greenland P, Alpert JS, Beller GA, Benjamin EJ, Budoff MJ, Fayad ZA, et al. American College of Cardiology Foundation, American Heart Association. ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2010;2010:e50–103.

    Article  Google Scholar 

  4. Polonsky TS, McClelland RL, Jorgensen NW, Bild DE, Burke GL, Guerci AD, et al. Coronary artery calcium score and risk classification for coronary heart disease prediction. JAMA. 2010;303:1610–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Bybee KA, Lee J, Markiewicz R, Longmore R, McGhie AI, O'Keefe JH, et al. Diagnostic and clinical benefit of combined coronary calcium and perfusion assessment in patients undergoing PET/CT myocardial perfusion stress imaging. J Nucl Cardiol. 2010;17:188–96.

    Article  PubMed  Google Scholar 

  6. Daniele S, Nappi C, Acampa W, Storto G, Pellegrino T, Ricci F, et al. Incremental prognostic value of coronary flow reserve assessed with single-photon emission computed tomography. J Nucl Cardiol. 2011;18:612–9.

    Article  PubMed  Google Scholar 

  7. Taqueti VR, Hachamovitch R, Murthy VL, Naya M, Foster CR, Hainer J, et al. Global coronary flow reserve is associated with adverse cardiovascular events independently of luminal angiographic severity and modifies the effect of early revascularization. Circulation. 2015;131:19–27.

    Article  PubMed  Google Scholar 

  8. Herzog BA, Husmann L, Valenta I, Gaemperli O, Siegrist PT, Tay FM, et al. Long-term prognostic value of 13N-ammonia myocardial perfusion positron emission tomography added value of coronary flow reserve. J Am Coll Cardiol. 2009;54:150–6.

    Article  PubMed  Google Scholar 

  9. 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.

    Article  PubMed  Google Scholar 

  10. Assante R, Zampella E, Arumugam P, Acampa W, Imbriaco M, Tout D, et al. Quantitative relationship between coronary artery calcium and myocardial blood flow by hybrid rubidium-82 PET/CT imaging in patients with suspected coronary artery disease. J Nucl Cardiol. 2017;24:494–501.

    Article  PubMed  Google Scholar 

  11. 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.

    Article  PubMed  Google Scholar 

  12. 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.

    Article  PubMed  Google Scholar 

  13. 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.

    Article  PubMed  Google Scholar 

  14. Camici PG, Crea F. Coronary microvascular dysfunction. N Engl J Med. 2007;356:830–40.

    Article  CAS  PubMed  Google Scholar 

  15. 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.

    Article  CAS  PubMed  Google Scholar 

  16. Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD. Joint ESC/ACCF/AHA/WHF task force for the universal definition of myocardial infarction. Third universal definition of myocardial infarction. Circulation. 2012;126:2020–35.

    Article  PubMed  Google Scholar 

  17. Vickers AJ, Cronin AM, Begg CB. One statistical test is sufficient for assessing new predictive markers. BMC Med Res Methodol. 2011;11:13.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Newson R. Comparing the predictive powers of survival models using Harrell’s C or Somers’ D. Stata J. 2010;10:339–58.

    Google Scholar 

  19. van Putten W. Classification and regression tree analysis with Stata. http://www.stata.com/meeting/2dutch/cart.pdf.

  20. 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.

    Article  PubMed  Google Scholar 

  21. Chambless LE, Cummiskey CP, Cui G. Several methods to assess improvement in risk prediction models: extension to survival analysis. Stat Med. 2011;30:22–38.

    Article  PubMed  Google Scholar 

  22. Uno H, Tian L, Cai T, Kohane IS, Wei LJ. A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data. Stat Med. 2013;32:2430–42.

    Article  PubMed  Google Scholar 

  23. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26:565–74.

    Article  Google Scholar 

  24. Budoff MJ, McClelland RL, Nasir K, Greenland P, Kronmal RA, Kondos GT, et al. Cardiovascular events with absent or minimal coronary calcification: the Multi-Ethnic Study of Atherosclerosis (MESA). Am Heart J. 2009;158:554–61.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Budoff MJ, Shaw LJ, Liu ST, Weinstein SR, Mosler TP, Tseng PH, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. J Am Coll Cardiol. 2007;49:1860–70.

    Article  PubMed  Google Scholar 

  26. Yeboah J, McClelland RL, Polonsky TS, Burke GL, Sibley CT, O'Leary D, et al. Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA. 2012;308:788–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Murthy VL, Naya M, Foster CR, Hainer J, Gaber M, Di Carli G, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124:2215–24.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ziadi MC, Dekemp RA, Williams KA, Guo A, Chow BJ, Renaud JM, et al. Impaired myocardial flow reserve on rubidium-82 positron emission tomography imaging predicts adverse outcomes in patients assessed for myocardial ischemia. J Am Coll Cardiol. 2011;58:740–8.

    Article  PubMed  Google Scholar 

  29. Dikic M, Tesic M, Markovic Z, Giga V, Djordjevic-Dikic A, Stepanovic J, et al. Prognostic value of calcium score and coronary flow velocity reserve in asymptomatic diabetic patients. Cardiovasc Ultrasound. 2015;13:41.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Advanced Biomedical Sciences, University Federico II, Naples, Italy

    Roberta Assante, Wanda Acampa, Emilia Zampella, Carmela Nappi, Ciro Gabriele Mainolfi & Alberto Cuocolo

  2. Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy

    Wanda Acampa, Valeria Gaudieri, Mariarosaria Panico & Mario Magliulo

  3. Nuclear Medicine Center, Central Manchester University Teaching Hospitals, Manchester, UK

    Parthiban Arumugam & Christine M. Tonge

  4. Department of Translational Medical Sciences, University Federico II, Naples, Italy

    Mario Petretta

Authors
  1. Roberta Assante
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wanda Acampa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emilia Zampella
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Parthiban Arumugam
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Carmela Nappi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Valeria Gaudieri
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ciro Gabriele Mainolfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mariarosaria Panico
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Mario Magliulo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Christine M. Tonge
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Mario Petretta
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Alberto Cuocolo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alberto Cuocolo.

Ethics declarations

Conflict of interest

None.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Assante, R., Acampa, W., Zampella, E. et al. Prognostic value of atherosclerotic burden and coronary vascular function in patients with suspected coronary artery disease. Eur J Nucl Med Mol Imaging 44, 2290–2298 (2017). https://doi.org/10.1007/s00259-017-3800-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-017-3800-7

Keywords

Search

Navigation