Skip to main content

Advertisement

SpringerLink
Log in

High-frequency QRS analysis to supplement ST evaluation in exercise stress electrocardiography: Incremental diagnostic accuracy and net reclassification

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

Abstract

Background

Exercise stress electrocardiography (ECG) alone is underutilized in part due to poor diagnostic accuracy. High-frequency QRS analysis (HF-QRS) is a novel tool to supplement ST evaluation during stress ECG. We compared the diagnostic accuracy and net reclassification of HF-QRS analysis compared with ST evaluation for substantial myocardial ischemia by exercise SPECT myocardial perfusion imaging (MPI).

Methods and Results

Exercise SPECT MPI was performed in 257 consecutive eligible patients (mean age 59 ± 12, 67% male). An ischemic HF-QRS pattern was defined as a ≥ 1 µV absolute reduction and a ≥ 50% relative reduction of the root-mean-square of the 150-250 Hz band signal in ≥ 3 leads. Left ventricular ischemia of ≥ 10% on SPECT MPI was the diagnostic standard for substantial myocardial ischemia. HF-QRS analysis demonstrated incremental diagnostic value to ST evaluation plus clinical risk factors (AUC 0.804 vs 0.749, P < .0001). A HF-QRS + ST -analysis strategy identified 92.3% of subjects with substantial ischemia and no abnormality in 59.9% of the cohort. No cardiac events occurred in patients without substantial ischemia identified by HF-QRS analysis.

Conclusions

In this prospective analysis, exercise stress ECG with HF-QRS analysis identified any and substantial ischemia with high diagnostic accuracy and may allow more than half of referred patients to safely avoid imaging.

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
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

Abbreviations

AUC:

Area under the curve

CAD:

Coronary artery disease

ECG:

Electrocardiography

HF-QRS:

High-frequency QRS

MAPHR:

Maximum age-predicted heart rate

MPI:

Myocardial perfusion imaging

SPECT:

Single-photon emission computed tomography

References

  1. Ronan G, Wolk MJ, Bailey SR, Doherty JU, Douglas PS, Hendel RC, et al. ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 Multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. J Nucl Cardiol 2014;21:192-220.

    Article  Google Scholar 

  2. 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  Google Scholar 

  3. Jouni H, Askew JW, Crusan DJ, Miller TD, Gibbons RJ. Temporal Trends of single-photon emission computed tomography myocardial perfusion imaging in patients with coronary artery disease: A 22-year experience from a Tertiary Academic Medical Center. Circulation Cardiovasc Imaging 2017;10:e005628.

    Google Scholar 

  4. Berrington de Gonzalez A, Kim KP, Smith-Bindman R, McAreavey D. Myocardial perfusion scans: projected population cancer risks from current levels of use in the United States. Circulation 2010;122:2403-10.

    Article  Google Scholar 

  5. Douglas PS, Hoffmann U, Patel MR, Mark DB, Al-Khalidi HR, Cavanaugh B, et al. Outcomes of anatomical versus functional testing for coronary artery disease. N Engl J Med 2015;372:1291-300.

    Article  CAS  Google Scholar 

  6. Detrano R, Gianrossi R, Froelicher V. The diagnostic accuracy of the exercise electrocardiogram: A meta-analysis of 22 years of research. Prog Cardiovasc Dis 1989;32:173-206.

    Article  CAS  Google Scholar 

  7. Ouellette M, Loffler AI, Beller GA, Workman VK, Holland E, Bourque JM. Clinical characteristics, sex differences, and outcomes in patients with normal or near-normal coronary arteries, non-obstructive or obstructive coronary artery disease. J Am Heart Assoc 2018;7(10):e007965.

    Article  Google Scholar 

  8. Amit G, Granot Y, Abboud S. Quantifying QRS changes during myocardial ischemia: Insights from high frequency electrocardiography. J Electrocardiogr 2014;47:505-11.

    Article  Google Scholar 

  9. Abboud S, Cohen RJ, Selwyn A, Ganz P, Sadeh D, Friedman PL. Detection of transient myocardial ischemia by computer analysis of standard and signal-averaged high-frequency electrocardiograms in patients undergoing percutaneous transluminal coronary angioplasty. Circulation 1987;76:585-96.

    Article  CAS  Google Scholar 

  10. Abboud S, Berenfeld O, Sadeh D. Simulation of high-resolution QRS complex using a ventricular model with a fractal conduction system. Effects of ischemia on high-frequency QRS potentials. Circ Res 1991;68:1751-60.

    Article  CAS  Google Scholar 

  11. Conti A, Bianchi S, Grifoni C, Trausi F, Bigiarini S, Lazzeretti D, et al. High-frequency QRS analysis superior to conventional ST-segment analysis of women with chest pain. Am J Emerg Med 2016;34:437-42.

    Article  Google Scholar 

  12. Sharir T, Merzon K, Kruchin I, Bojko A, Toledo E, Asman A, et al. Use of electrocardiographic depolarization abnormalities for detection of stress-induced ischemia as defined by myocardial perfusion imaging. Am J Cardiol 2012;109:642-50.

    Article  Google Scholar 

  13. Gibbons RJ, Balady GJ, Beasley JW, Bricker JT, Duvernoy WF, Froelicher VF, et al. ACC/AHA Guidelines for Exercise Testing. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Exercise Testing). J Am Coll Cardiol 1997;30:260-311.

    Article  CAS  Google Scholar 

  14. Watson DD, Smith WH 2nd. The role of quantitation in clinical nuclear cardiology: the University of Virginia approach. J Nucl Cardiol 2007;14:466-82.

    Article  Google Scholar 

  15. Bourque JM, Holland BH, Watson DD, Beller GA. Achieving an exercise workload of > or = 10 metabolic equivalents predicts a very low risk of inducible ischemia: does myocardial perfusion imaging have a role? J Am Coll Cardiol 2009;54:538-45.

    Article  Google Scholar 

  16. 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  Google Scholar 

  17. Pencina MJ, D’Agostino RB, Vasan RS. Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med 2010;48:1703-11.

    Article  CAS  Google Scholar 

  18. Bourque JM, Beller GA. Value of exercise ECG for risk stratification in suspected or known CAD in the era of advanced imaging technologies. JACC Cardiovasc Imaging 2015;8:1309-21.

    Article  Google Scholar 

  19. Gharacholou SM, Pellikka PA. Trends in noninvasive testing for coronary artery disease: less exercise, less information. Am J Med 2015;128:5-7.

    Article  Google Scholar 

  20. Lucas FL, DeLorenzo MA, Siewers AE, Wennberg DE. Temporal trends in the utilization of diagnostic testing and treatments for cardiovascular disease in the United States, 1993-2001. Circulation 2006;113:374-9.

    Article  CAS  Google Scholar 

  21. Argulian E, Po JRF, Uretsky S, Kommaraju KK, Patel S, Agarwal V, et al. Comparison of the current reasons for undergoing pharmacologic stress during echocardiographic and radionuclide stress testing. J Nucl Cardiol 2017;24:546-54.

    Article  Google Scholar 

  22. Detrano R, Gianrossi R, Mulvihill D, Lehmann K, Dubach P, Colombo A, et al. Exercise-induced ST segment depression in the diagnosis of multivessel coronary disease: a meta analysis. J Am Coll Cardiol 1989;14:1501-8.

    Article  CAS  Google Scholar 

  23. Gianrossi R, Detrano R, Mulvihill D, Lehmann K, Dubach P, Colombo A, et al. Exercise-induced ST depression in the diagnosis of coronary artery disease. A meta-analysis. Circulation 1989;80:87-98.

    Article  CAS  Google Scholar 

  24. Gibbons RJ, Balady GJ, Bricker JT, Chaitman BR, Fletcher GF, Froelicher VF, et al. ACC/AHA 2002 guideline update for exercise testing: summary article. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1997 Exercise Testing Guidelines). J Am Coll Cardiol 2002;40:1531-40.

    Article  Google Scholar 

  25. Beller GA. How should we interpret the decrease in annual volume of stress imaging tests for evaluation of suspected or known coronary artery disease with fewer high-risk test results? Circulation Cardiovasc Imaging 2017;10:e006702.

    Article  Google Scholar 

  26. Brenner H, Gefeller O. Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence. Stat Med 1997;16:981-91.

    Article  CAS  Google Scholar 

  27. Goldberger AL, Bhargava V, Froelicher V, Covell J. Effect of myocardial infarction on high-frequency QRS potentials. Circulation 1981;64:34-42.

    Article  CAS  Google Scholar 

  28. Lipton JA, Warren SG, Broce M, Abboud S, Beker A, Sornmo L, et al. High-frequency QRS electrocardiogram analysis during exercise stress testing for detecting ischemia. Int J Cardiol 2008;124:198-203.

    Article  Google Scholar 

  29. Toledo E, Lipton JA, Warren SG, Abboud S, Broce M, Lilly DR, et al. Detection of stress-induced myocardial ischemia from the depolarization phase of the cardiac cycle—a preliminary study. J Electrocardiogr 2009;42:240-7.

    Article  Google Scholar 

  30. Ringborn M, Pettersson J, Persson E, Warren SG, Platonov P, Pahlm O, et al. Comparison of high-frequency QRS components and ST-segment elevation to detect and quantify acute myocardial ischemia.J. Electrocardiography 2010;43:113-20.

    Article  Google Scholar 

  31. Rosenmann D, Mogilevski Y, Amit G, Davrath LR, Tzivoni D. High-frequency QRS analysis improves the specificity of exercise ECG testing in women referred for angiography. J Electrocardiogr 2013;46:19-26.

    Article  Google Scholar 

  32. Berman DS, Kang X, Slomka PJ, Gerlach J, de Yang L, Hayes SW, et al. 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  Google Scholar 

Download references

Acknowledgements

This study was supported by a NIH Grants: K23- HL119620-02 (JMB) and T32-EB003841 (JAG, PCB and PWS).

Disclosure

Jamieson Bourque receives research Grant support from Astellas Pharma and consults with Pfizer. All other authors have no conflicts of interest to disclose.

Author information

Author notes

  1. Pelbreton C. Balfour Jr. and Jorge A. Gonzalez have contributed equally to this manuscript.

Authors and Affiliations

  1. Cardiovascular Division, Department of Medicine, Cardiovascular Imaging Center, University of Virginia Health System, 1215 Lee Street, Box 800662, Charlottesville, VA, 22908, USA

    Pelbreton C. Balfour Jr. MD, ScM, Jack W. Melson MD, Michael Sobczak CNMT, Valerie Izarnotegui MD, Denny D. Watson PhD, George A. Beller MD & Jamieson M. Bourque MD, MHS

  2. Departments of Radiology, University of Virginia Health System, Charlottesville, VA, USA

    Denny D. Watson PhD, George A. Beller MD & Jamieson M. Bourque MD, MHS

  3. Division of Cardiovascular Disease, Scripps Clinic, La Jolla, CA, USA

    Jorge A. Gonzalez MD

  4. Berkshire Medical Center, Pittsfield, MA, USA

    Peter W. Shaw MD

  5. Cardiac and Vascular Institute, Memorial Healthcare System, Hollywood, FL, USA

    Margarita P. Caminero MD

  6. University of North Carolina, Chapel Hill, NC, USA

    Eric M. Holland MD

Authors
  1. Pelbreton C. Balfour Jr. MD, ScM
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jorge A. Gonzalez MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peter W. Shaw MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Margarita P. Caminero MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eric M. Holland MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jack W. Melson MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Michael Sobczak CNMT
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Valerie Izarnotegui MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Denny D. Watson PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. George A. Beller MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jamieson M. Bourque MD, MHS
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jamieson M. Bourque MD, MHS.

Additional information

The authors of this article have provided a PowerPoint file, available for download at SpringerLink, which summarizes the contents of the paper and is free for re-use at meetings and presentations. Search for the article DOI on SpringerLink.com.

Funding

Jorge Gonzalez, Pelbreton Balfour, and Peter Shaw receive support from NIH-T32-EB003841. Jamieson Bourque receives support from NIH K23-HL119620-02.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PPTX 49539 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Balfour, P.C., Gonzalez, J.A., Shaw, P.W. et al. High-frequency QRS analysis to supplement ST evaluation in exercise stress electrocardiography: Incremental diagnostic accuracy and net reclassification. J. Nucl. Cardiol. 27, 2063–2075 (2020). https://doi.org/10.1007/s12350-018-01530-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-018-01530-w

Keywords

Search

Navigation