Skip to main content
SpringerLink
Log in

Predictors of high-risk coronary artery disease in subjects with normal SPECT myocardial perfusion imaging

  • Original Article
  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

Background

While uncommon, normal stress SPECT myocardial perfusion imaging (MPI) can be seen in patients with high-risk coronary artery disease (CAD) by invasive coronary angiography (ICA).The predictors of high-risk CAD in patients with normal SPECT-MPI have not been described.

Methods

We studied 580 patients (age 64 ± 12 years, 49% men) without known CAD who underwent stress-gated SPECT-MPI [exercise (41%) or vasodilator (59%)] <2 months before ICA and had summed stress score (SSS) <4. High-risk CAD was defined as 3 vessels with ≥70% stenosis, 2 vessels with ≥70% stenosis including proximal left anterior descending, or left main with ≥50% stenosis. Obstructive non-high-risk CAD was defined by the presence of a ≥70% stenosis but without having other high-risk criteria. Tenfold cross-validated receiver operating characteristic (ROC) estimates were obtained to assess the predictors of high-risk CAD.

Results

Forty-two subjects (7.2%) had high-risk CAD and 168 (29.0%) had obstructive non-high-risk CAD. Variables associated with high-risk CAD were pretest probability of CAD ≥66% (Odds ratio [OR] 3.63, 95% CI 1.6-8.3, P = .002), SSS > 0 (OR 7.46, 95% CI 2.6-21.1, P < 0.001), and abnormal TID (OR 2.16, 95% CI 1.0-4.5, P = 0.044). When substituted for TID, EF change was also predictive of high-risk CAD (OR 0.93, 95% CI 0.9-1.0, P = 0.023). The prevalence of high-risk CAD increased as the number of these predictors increased. In a sub-analysis of patients in whom quantitative total perfusion deficit (TPD) was available, TPD > 0 was also a predictor of high-risk CAD (OR 6.01, 95% CI 1.5-22.2, P = 0.011).

Conclusion

Several clinical, stress, and SPECT-MPI findings are associated high-risk CAD among patients with normal SPECT-MPI. Consideration of these factors may improve the overall assessment of the likelihood of high-risk CAD in patients undergoing stress SPECT-MPI.

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

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Hachamovitch R, Hayes SW, Friedman JD, Cohen I, Berman DS. Comparison of the short-term survival benefit associated with revascularization compared with medical therapy in patients with no prior coronary artery disease undergoing stress myocardial perfusion single photon emission computed tomography. Circulation. 2003;107:2900-7.

    Article  PubMed  Google Scholar 

  2. Hachamovitch R, Hayes S, Friedman JD, Cohen I, Shaw LJ, Germano G, Berman DS. Determinants of risk and its temporal variation in patients with normal stress myocardial perfusion scans: What is the warranty period of a normal scan? J Am Coll Cardiol. 2003;41:1329-40.

    Article  PubMed  Google Scholar 

  3. Ottenhof MJ, Wai MC, Boiten HJ, Korbee RS, Valkema R, van Domburg RT, Schinkel AF. 12-year outcome after normal myocardial perfusion spect in patients with known coronary artery disease. J Nucl Cardiol. 2013;20:748-54.

    Article  PubMed  Google Scholar 

  4. Berman DS, Kang X, Slomka PJ, Gerlach J, de Yang L, Hayes SW, Friedman JD, Thomson LE, Germano G. Underestimation of extent of ischemia by gated spect myocardial perfusion imaging in patients with left main coronary artery disease. J Nucl Cardiol. 2007;14:521-8.

    Article  PubMed  Google Scholar 

  5. Lima RS, Watson DD, Goode AR, Siadaty MS, Ragosta M, Beller GA, Samady H. Incremental value of combined perfusion and function over perfusion alone by gated spect myocardial perfusion imaging for detection of severe three-vessel coronary artery disease. J Am Coll Cardiol. 2003;42:64-70.

    Article  PubMed  Google Scholar 

  6. Berman DS. Fourth annual Mario S. Verani, MD memorial lecture: Noninvasive imaging in coronary artery disease: Changing roles, changing players. J Nucl Cardiol. 2006;13:457-73.

    Article  PubMed  Google Scholar 

  7. Rozanski A, Gransar H, Shaw LJ, Kim J, Miranda-Peats L, Wong ND, Rana JS, Orakzai R, Hayes SW, Friedman JD, Thomson LE, Polk D, Min J, Budoff MJ, Berman DS. Impact of coronary artery calcium scanning on coronary risk factors and downstream testing the Eisner (early identification of subclinical atherosclerosis by noninvasive imaging research) prospective randomized trial. J Am Coll Cardiol. 2011;57:1622-32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. 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;1:444-55.

    Article  CAS  PubMed  Google Scholar 

  9. Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med. 1979;300:1350-8.

    Article  CAS  PubMed  Google Scholar 

  10. Montalescot G, Sechtem U, Achenbach S, Andreotti F, Arden C, Budaj A, et al. 2013 Esc guidelines on the management of stable coronary artery disease: The task force on the management of stable coronary artery disease of the european society of cardiology. Eur Heart J. 2013;34:2949-3003.

    Article  PubMed  Google Scholar 

  11. Berman DS, Kang X, Hayes SW, Friedman JD, Cohen I, Abidov A, et al. Adenosine myocardial perfusion single-photon emission computed tomography in women compared with men. Impact of diabetes mellitus on incremental prognostic value and effect on patient management. J Am Coll Cardiol. 2003;41:1125-33.

    Article  PubMed  Google Scholar 

  12. Arsanjani R, Xu Y, Hayes SW, Fish M, Lemley M, Gerlach J, et al. Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease from myocardial perfusion spect in a large population. J Nucl Med. 2013;54:221-8.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Berman DS, Abidov A, Kang X, Hayes SW, Friedman JD, Sciammarella MG, et al. Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion spect interpretation. J Nucl Cardiol. 2004;11:414-23.

    Article  PubMed  Google Scholar 

  14. Rozanski A, Gransar H, Hayes SW, Min J, Friedman JD, Thomson LE, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009. J Am Coll Cardiol. 2013;61:1054-65.

    Article  PubMed  Google Scholar 

  15. Germano G, Berman DS. On the accuracy and reproducibility of quantitative gated myocardial perfusion spect. J Nucl Med. 1999;40:810-3.

    CAS  PubMed  Google Scholar 

  16. 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 

  17. Berman DS, Hachamovitch R, Kiat H, Cohen I, Cabico JA, Wang FP, et al. Incremental value of prognostic testing in patients with known or suspected ischemic heart disease: A basis for optimal utilization of exercise technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol. 1995;26:639-47.

    Article  CAS  PubMed  Google Scholar 

  18. Slomka PJ, Nishina H, Berman DS, Akincioglu C, Abidov A, Friedman JD, et al. Automated quantification of myocardial perfusion spect using simplified normal limits. J Nucl Cardiol. 2005;12:66-77.

    Article  PubMed  Google Scholar 

  19. Nishina H, Slomka PJ, Abidov A, Yoda S, Akincioglu C, Kang X, et al. Combined supine and prone quantitative myocardial perfusion spect: Method development and clinical validation in patients with no known coronary artery disease. J Nucl Med. 2006;47:51-8.

    PubMed  Google Scholar 

  20. Germano G, Kavanagh PB, Waechter P, Areeda J, Van Kriekinge S, Sharir T, Lewin HC, Berman DS. A new algorithm for the quantitation of myocardial perfusion spect I: Technical principles and reproducibility. J Nucl Med. 2000;41:712-9.

    CAS  PubMed  Google Scholar 

  21. Sharir T, Germano G, Waechter PB, Kavanagh PB, Areeda JS, Gerlach J, et al. A new algorithm for the quantitation of myocardial perfusion spect II: Validation and diagnostic yield. J Nucl Med. 2000;41:720-7.

    CAS  PubMed  Google Scholar 

  22. Mazzanti M, Germano G, Kiat H, Kavanagh PB, Alexanderson E, Friedman JD, et al. Identification of severe and extensive coronary artery disease by automatic measurement of transient ischemic dilation of the left ventricle in dual-isotope myocardial perfusion spect. J Am Coll Cardiol. 1996;27:1612-20.

    Article  CAS  PubMed  Google Scholar 

  23. Abidov A, Germano G, Berman DS. Transient ischemic dilation ratio: A universal high-risk diagnostic marker in myocardial perfusion imaging. J Nucl Cardiol. 2007;14:497-500.

    Article  PubMed  Google Scholar 

  24. Germano G, Kavanagh PB, Slomka PJ, Van Kriekinge SD, Pollard G, Berman DS. Quantitation in gated perfusion spect imaging: The cedars-sinai approach. J Nucl Cardiol. 2007;14:433-54.

    Article  PubMed  Google Scholar 

  25. Sharir T, Kang X, Germano G, Bax JJ, Shaw LJ, Gransar H, et al. Prognostic value of poststress left ventricular volume and ejection fraction by gated myocardial perfusion SPECT in women and men: Gender-related differences in normal limits and outcomes. J Nucl Cardiol. 2006;13:495-506.

    Article  PubMed  Google Scholar 

  26. Min JK, Berman DS, Dunning A, Achenbach S, Al-Mallah M, Budoff MJ, et al. All-cause mortality benefit of coronary revascularization vs. Medical therapy in patients without known coronary artery disease undergoing coronary computed tomographic angiography: Results from confirm (coronary ct angiography evaluation for clinical outcomes: An international multicenter registry). Eur Heart J. 2012;33:3088-97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Azarbal B, Hayes SW, Lewin HC, Hachamovitch R, Cohen I, Berman DS. The incremental prognostic value of percentage of heart rate reserve achieved over myocardial perfusion single-photon emission computed tomography in the prediction of cardiac death and all-cause mortality: Superiority over 85% of maximal age-predicted heart rate. J Am Coll Cardiol. 2004;44:423-30.

    Article  PubMed  Google Scholar 

  28. Fletcher GF, Balady G, Froelicher VF, Hartley LH, Haskell WL, Pollock ML. Exercise standards. A statement for healthcare professionals from the American Heart Association. Writing group. Circulation. 1995;91:580-615.

    Article  CAS  PubMed  Google Scholar 

  29. Abidov A, Hachamovitch R, Hayes SW, Ng CK, Cohen I, Friedman JD, et al. Prognostic impact of hemodynamic response to adenosine in patients older than age 55 years undergoing vasodilator stress myocardial perfusion study. Circulation. 2003;107:2894-9.

    Article  PubMed  Google Scholar 

  30. Melikian N, De Bondt P, Tonino P, De Winter O, Wyffels E, Bartunek J, et al. Fractional flow reserve and myocardial perfusion imaging in patients with angiographic multivessel coronary artery disease. JACC. Cardiovasc Interv. 2010;3:307-14.

    Article  PubMed  Google Scholar 

  31. Bateman TM, Maddahi J, Gray RJ, Murphy FL, Garcia EV, Conklin CM, et al. Diffuse slow washout of myocardial thallium-201: A new scintigraphic indicator of extensive coronary artery disease. J Am Coll Cardiol. 1984;4:55-64.

    Article  CAS  PubMed  Google Scholar 

  32. Tonino PA, Fearon WF, De Bruyne B, Oldroyd KG, Leesar MA, Ver Lee PN, et al. Angiographic versus functional severity of coronary artery stenoses in the fame study fractional flow reserve versus angiography in multivessel evaluation. J Am Coll Cardiol. 2010;55:2816-21.

    Article  PubMed  Google Scholar 

  33. Abidov A, Hachamovitch R, Hayes SW, Friedman JD, Cohen I, Kang X, et al. Are shades of gray prognostically useful in reporting myocardial perfusion single-photon emission computed tomography? Circulation Cardiovasc Imaging. 2009;2:290-8.

    Article  Google Scholar 

  34. Nakazato R, Berman DS, Gransar H, Hyun M, Miranda-Peats R, Kite FC, et al. Prognostic value of quantitative high-speed myocardial perfusion imaging. J Nucl Cardiol. 2012;19:1113-23.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Abidov A, Bax JJ, Hayes SW, Hachamovitch R, Cohen I, Gerlach J, et al. Transient ischemic dilation ratio of the left ventricle is a significant predictor of future cardiac events in patients with otherwise normal myocardial perfusion spect. J Am Coll Cardiol. 2003;42:1818-25.

    Article  PubMed  Google Scholar 

  36. Mandour Ali MA, Bourque JM, Allam AH, Beller GA, Watson DD. The prevalence and predictive accuracy of quantitatively defined transient ischemic dilation of the left ventricle on otherwise normal spect myocardial perfusion imaging studies. J Nucl Cardiol. 2011;18:1036-43.

    Article  PubMed  Google Scholar 

  37. Halligan WT, Morris PB, Schoepf UJ, Mischen BT, Spearman JV, Spears JR, et al. Transient ischemic dilation of the left ventricle on spect: Correlation with findings at coronary ct angiography. J Nucl Med. 2014;55:917-22.

    Article  PubMed  Google Scholar 

  38. Valdiviezo C, Motivala AA, Hachamovitch R, Chamarthy M, Navarro PC, Ostfeld RJ, et al. The significance of transient ischemic dilation in the setting of otherwise normal spect radionuclide myocardial perfusion images. J Nucl Cardiol. 2011;18:220-9.

    Article  PubMed  Google Scholar 

  39. Dorbala S, Vangala D, Sampson U, Limaye A, Kwong R, Di Carli MF. Value of vasodilator left ventricular ejection fraction reserve in evaluating the magnitude of myocardium at risk and the extent of angiographic coronary artery disease: A 82rb Pet/CT study. J Nucl Med. 2007;48:349-58.

    PubMed  Google Scholar 

  40. Fujimoto S, Wagatsuma K, Uchida Y, Nii H, Nakano M, Toda M, et al. Study of the predictors and lesion characteristics of ischemic heart disease patients with false negative results in stress myocardial perfusion single-photon emission tomography. Circ J. 2006;70:297-303.

    Article  PubMed  Google Scholar 

  41. Arsanjani R, Xu Y, Dey D, Vahistha V, Shalev A, Nakanishi R, et al. Improved accuracy of myocardial perfusion spect for detection of coronary artery disease by machine learning in a large population. J Nucl Cardiol. 2013;20:553-62.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Bourque JM, Charlton GT, Holland BH, Belyea CM, Watson DD, Beller GA. Prognosis in patients achieving ≥10 mets on exercise stress testing: Was spect imaging useful? J Nucl Cardiol. 2011;18:230-7.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgment

Dr. Nakanishi was supported in part by research fellowship awards from the Society of Nuclear Medicine and Toho University School of Medicine, Tokyo, Japan. This research was supported in part by Grants R01HL089765 and 5K23HL92299 from the National Heart, Lung, and Blood Institute/National Institutes of Health (NHLBI/NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NHLBI. Cedars-Sinai Medical Center receives royalties for the quantitative assessment of function, perfusion, and viability, a portion of which is distributed to some of the authors of this manuscript (Daniel S. Berman, Guido Germano and Piotr Slomka). No other potential conflict of interest relevant to this article was reported. This work was also supported by Grants to Dr. Berman from the Jane and Michael Eisner, and the Diane and Guilford Glazer Foundations.

Author information

Authors and Affiliations

  1. Departments of Imaging and Medicine, Cedars-Sinai Heart Institute, Cedars Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA, 90048, USA

    Rine Nakanishi MD, PhD, Heidi Gransar MS, Piotr Slomka PhD, Reza Arsanjani MD, Aryeh Shalev MD, Yuka Otaki MD, PhD, John D. Friedman MD, Sean W. Hayes MD, Louise E. B. Thomson MBChB, Guido Germano PhD & Daniel S. Berman MD, FACC

  2. Oregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, OR, USA

    Mathews Fish MD

  3. Sarver Heart Center, University of Arizona College of Medicine, Tucson, AZ, USA

    Aiden Abidov MD, PhD

  4. Department of Medicine, Emory University, Atlanta, GA, USA

    Leslee Shaw PhD

  5. Division of Cardiology, St. Luke’s Roosevelt Hospital, New York, NY, USA

    Alan Rozanski MD

  6. Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    Daniel S. Berman MD, FACC

Authors
  1. Rine Nakanishi MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heidi Gransar MS
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Piotr Slomka PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Reza Arsanjani MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aryeh Shalev MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuka Otaki MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John D. Friedman MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sean W. Hayes MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Louise E. B. Thomson MBChB
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mathews Fish MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Guido Germano PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Aiden Abidov MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Leslee Shaw PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Alan Rozanski MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Daniel S. Berman MD, FACC
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniel S. Berman MD, FACC.

Additional information

See related editorial, doi:10.1007/s12350-015-0167-7.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nakanishi, R., Gransar, H., Slomka, P. et al. Predictors of high-risk coronary artery disease in subjects with normal SPECT myocardial perfusion imaging. J. Nucl. Cardiol. 23, 530–541 (2016). https://doi.org/10.1007/s12350-015-0150-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-015-0150-3

Keywords

Search

Navigation