Skip to main content

Advertisement

SpringerLink
Log in

Software reproducibility of myocardial blood flow and flow reserve quantification in ischemic heart disease: A 13N-ammonia PET study

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

Abstract

Background

We explored agreement in the quantification of myocardial perfusion by cross-comparison of implemented software packages (SPs) in three distinguishable patient profile populations.

Methods

We studied 91 scans of patients divided into 3 subgroups based on their semi-quantitative perfusion findings: patients with normal perfusion, with reversible perfusion defects, and with fixed perfusion defects. Rest myocardial blood flow (MBF), stress MBF, and myocardial flow reserve (MFR) were obtained with QPET, SyngoMBF, and Carimas. Agreement between SPs was considered adequate when a pairwise standardized difference was found to be < 0.20 and its corresponding intraclass correlation coefficient was ≥ 0.75.

Results

In patients with normal perfusion, two out of three comparisons of global stress MBF quantifications were outside the limits of agreement. In ischemic patients, all comparisons of global stress MBF and MFR were outside the limits of established agreement. In patients with fixed perfusion defects, all SP comparisons of perfusion quantifications were within the limit of agreement. Regionally, agreement of these perfusion estimates was mostly found for the left anterior descending artery vascular territory.

Conclusion

Reversible defects demonstrated the worst agreement in global stress MBF and MFR and discrepancies showed to be regional dependent. Reproducibility between SPs should not be assumed.

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

Similar content being viewed by others

Abbreviations

MBF:

Myocardial blood flow

MFR:

Myocardial flow reserve

LAD:

Left anterior descending artery

LCx:

Left circumflex coronary artery

RCA:

Right coronary artery

PET:

Positron emission tomography

References

  1. Jaarsma C, Leiner T, Bekkers SC, Crijns HJ, Joachim E, Nagel E, et al. Diagnostic performance of noninvasive myocardial perfusion imaging using single-photon emission computed tomography, cardiac magnetic resonance, and positron emission tomography imaging for the detection of obstructive coronary artery disease. JACC 2012;59:1719-28. https://doi.org/10.1016/j.jacc.2011.12.040.

    Article  PubMed  Google Scholar 

  2. Sciagrà R, Passeri A, Bucerius J, Verberne HJ, Slart RHJA, Lindner O, et al. Clinical use of quantitative cardiac perfusion PET: Rationale, modalities and possible indications. Position paper of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM). Eur J Nucl Med Mol Imaging 2016;43:1530-45. https://doi.org/10.1007/s00259-016-3317-5.

    Article  PubMed  Google Scholar 

  3. Knuuti J, Ballo H, Juarez-Orozco LE, Saraste A, Kolh P, Rutjes AWS, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: A meta-analysis focused on post-test disease probability. Eur Heart J 2018;1-9. https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehy267/5020750.

  4. Juárez-Orozco LE, Tio RA, Alexanderson E, Dweck M, Vliegenthart R, El Moumni M, et al. Quantitative myocardial perfusion evaluation with positron emission tomography and the risk of cardiovascular events in patients with coronary artery disease: A systematic review of prognostic studies. Eur Heart J Cardiovasc Imaging 2017. https://doi.org/10.1093/ehjci/jex331.

    Article  PubMed Central  Google Scholar 

  5. Dorbala S, Di Carli MF. Cardiac PET perfusion: Prognosis, risk stratification, and clinical management. Semin Nucl Med 2014;44:344-57.

    Article  Google Scholar 

  6. Camici PG, D’Amati G, Rimoldi O. Coronary microvascular dysfunction: Mechanisms and functional assessment. Nat Rev Cardiol 2015;12:48-62. http://www.ncbi.nlm.nih.gov/pubmed/25311229.

  7. Slomka PJ, Alexanderson E, Jácome R, Jiménez M, Romero E, Meave A, et al. Comparison of clinical tools for measurements of regional stress and rest myocardial blood flow assessed with 13N-ammonia PET/CT. J Nucl Med 2012;53:171-81. http://www.ncbi.nlm.nih.gov/pubmed/22228795.

  8. Nesterov SV, Deshayes E, Sciagrà R, Settimo L, Declerck JM, Pan X-B, et al. Quantification of myocardial blood flow in absolute terms using (82)Rb PET imaging: The RUBY-10 Study. JACC Cardiovasc Imaging 2014;7:1119-27. http://www.sciencedirect.com/science/article/pii/S1936878X1400641X (cited 2016 Feb 24).

  9. Harms HJ, Nesterov SV, Han C, Danad I, Leonora R, Raijmakers PG, et al. Comparison of clinical non-commercial tools for automated quantification of myocardial blood flow using oxygen-15-labelled water PET/CT. Eur Heart J Cardiovasc Imaging 2014;15:431-41. http://ehjcimaging.oxfordjournals.org/content/15/4/431.abstract.

  10. Alexánderson Rosas E, Slomka PJ, García-Rojas L, Calleja R, Jácome R, Jiménez-Santos M, et al. Functional impact of coronary stenosis observed on coronary computed tomography angiography: Comparison with 13N-ammonia PET. Arch Med Res 2010;41:642-8.

    Article  Google Scholar 

  11. Juárez-Orozco LE, Alexanderson E, Dierckx RA, Boersma HH, Hillege JL, Zeebregts CJ, et al. Stress myocardial blood flow correlates with ventricular function and synchrony better than myocardial perfusion reserve: A nitrogen-13 ammonia PET study. J Nucl Cardiol 2016;1-10. http://link.springer.com/10.1007/s12350-016-0669-y.

  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. J Cardiovasc Magn Reson 2002;4:203-10.

    Article  Google Scholar 

  13. Hutchins GD, Schwaiger M, Rosenspire KC, Krivokapich J, Schelbert H, Kuhl DE. Noninvasive quantification of regional blood flow in the human heart using N-13 ammonia and dynamic positron emission tomographic imaging. J Am Coll Cardiol 1990;15:1032-42. http://linkinghub.elsevier.com/retrieve/pii/073510979090237J (cited 2016 June 30).

  14. Choi Y, Huang S, Hawkins RA, Kuhle WG, Czernin J, Phelps ME, et al. A simplified method for quantification of myocardial blood flow using nitrogen-13-ammonia and dynamic PET. J Nucl Med 1993;34:488-97.

    CAS  PubMed  Google Scholar 

  15. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab 2007;27:1533-9.

    Article  CAS  Google Scholar 

  16. Efseaff M, Klein R, Ziadi MC, Beanlands RS, Dekemp RA. Short-term repeatability of resting myocardial blood flow measurements using rubidium-82 PET imaging. J Nucl Cardiol 2012;19:997-1006.

    Article  Google Scholar 

  17. Kitkungvan D, Johnson NP, Roby AE, Patel MB, Kirkeeide R, Gould KL. Routine clinical quantitative rest stress myocardial perfusion for managing coronary artery disease: Clinical relevance of test–retest variability. JACC Cardiovasc Imaging 2017;10:565-77.

    Article  Google Scholar 

  18. Rosner B. Fundamentals of biostatistics. 8th ed. New York: Duxbury Press; 2015.

    Google Scholar 

  19. Kaufmann PA, Gnecchi-Ruscone T, Yap JT, Rimoldi O, Camici PG. Assessment of the reproducibility of baseline and hyperemic myocardial blood flow measurements with 15O-labeled water and PET. J Nucl Med 1999;40:1848-56. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=10565780.

  20. Manabe O, Yoshinaga K, Katoh C, Naya M, deKemp RA, Tamaki N. Repeatability of rest and hyperemic myocardial blood flow measurements with 82Rb dynamic PET. J Nucl Med 2008;50:68-71. http://jnm.snmjournals.org/cgi/doi/10.2967/jnumed.108.055673.

  21. Sunderland JJ, Pan X-B, Declerck J, Menda Y. Dependency of cardiac rubidium-82 imaging quantitative measures on age, gender, vascular territory, and software in a cardiovascular normal population. J Nucl Cardiol 2015;22:72-84. https://doi.org/10.1007/s12350-014-9920-6.

    Article  PubMed  Google Scholar 

  22. Yalcin H, Valenta I, Zhao M, Tahari A, Lu DY, Higuchi T, et al. Comparison of two software systems for quantification of myocardial blood flow in patients with hypertrophic cardiomyopathy. J Nucl Cardiol 2018. https://doi.org/10.1007/s12350-017-1155-x.

    Article  PubMed  Google Scholar 

  23. Nesterov SV, Lee BC, Moody JB, Slomka P, Han C, Knuuti JM. The status and future of PET myocardial blood flow quantification software. Ann Nucl Cardiol 2016;2:106-10. https://www.jstage.jst.go.jp/article/anc/2/1/2_106/_article.

  24. Klingensmith WC, Noonan C, Goldberg JH, Buchwald D, Kimball JT, Manson SM. Decreased perfusion in the lateral wall of the left ventricle in PET/CT studies with 13N-ammonia: Evaluation in healthy adults. J Nucl Med Technol 2009;37:215-9. http://tech.snmjournals.org/cgi/doi/10.2967/jnmt.109.062059.

  25. Martinez-Möller A, Zikic D, Botnar RM, Bundschuh RA, Howe W, Ziegler SI, et al. Dual cardiac-respiratory gated PET: Implementation and results from a feasibility study. Eur J Nucl Med Mol Imaging 2007;34:1447-54.

    Article  Google Scholar 

  26. Nakazato R, Heo R, Leipsic J, Min JK. CFR and FFR assessment with PET and CTA: Strengths and limitations. Curr Cardiol Rep 2014;16:484. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578154/.

  27. Khurshid K, McGough RJ, Berger K. Automated cardiac motion compensation in PET/CT for accurate reconstruction of PET myocardial perfusion images. Phys Med Biol 2008;53:5705-18.

    Article  Google Scholar 

  28. Hove JD, Gambhir SS, Kofoed KF, Freiberg J, Kelbæk H. Quantitation of the regional blood flow in the interventricular septum using positron emission tomography and nitrogen-13 ammonia. Eur J Nucl Med Mol Imaging 2003;30:109-16.

    Article  Google Scholar 

  29. Du Y, Madar I, Stumpf MJ, Rong X, Fung GSK, Frey EC. Compensation for spill-in and spill-out partial volume effects in cardiac PET imaging. J Nucl Cardiol 2013;20:84-98.

    Article  Google Scholar 

  30. Slomka PJ, Nishina H, Berman DS, Kang X, Akincioglu C, Friedman JD, et al. “Motion-frozen” display and quantification of myocardial perfusion. J Nucl Med 2004;45:1128-34.

    PubMed  Google Scholar 

Download references

Acknowledgments

This project was supported with public funds of the National Mexican Council of Science and Technology (CONACYT) and the University of Groningen/University Medical Center Groningen (RuG/UMCG). We thank Andres Sanabria Rodríguez for assisting in the PET/CCTA data acquisition.

Author information

Author notes

  1. Andrea G. Monroy-Gonzalez and Luis Eduardo Juarez-Orozco authors contributed equally to this work.

Authors and Affiliations

  1. Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

    Andrea G. Monroy-Gonzalez MD, Issi R. Vedder MD, David Vállez García PhD, Ronald Borra MD, PhD & Riemer H. J. A. Slart MD, PhD

  2. Turku PET Centre, University of Turku, Turku, Finland

    Luis Eduardo Juarez-Orozco MD, PhD, Chunlei Han MD, PhD, Sergey V. Nesterov MD, PhD, PMP, PgMP & Juhani Knuuti MD, PhD

  3. Departments of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Piotr J. Slomka PhD

  4. Biomedical Photonic Imaging, TechMed Centre, University of Twente, Enschede, The Netherlands

    Riemer H. J. A. Slart MD, PhD

  5. Department of Physiology, National Autonomous University of Mexico, Mexico City, Mexico

    Erick Alexanderson-Rosas MD

  6. National Institute of Cardiology Ignacio Chavez, Mexico City, Mexico

    Erick Alexanderson-Rosas MD

  7. Institute of Evolutionary Physiology and Biochemistry, RAS, St. Petersburg, Russia

    Sergey V. Nesterov MD, PhD, PMP, PgMP

Authors
  1. Andrea G. Monroy-Gonzalez MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luis Eduardo Juarez-Orozco MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chunlei Han MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Issi R. Vedder MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Vállez García PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ronald Borra MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Piotr J. Slomka PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sergey V. Nesterov MD, PhD, PMP, PgMP
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Juhani Knuuti MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Riemer H. J. A. Slart MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Erick Alexanderson-Rosas MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Erick Alexanderson-Rosas MD.

Ethics declarations

Disclosure

The authors report that they have no relevant relationships to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 198 kb)

Supplementary material 2 (PPTX 1161 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Monroy-Gonzalez, A.G., Juarez-Orozco, L.E., Han, C. et al. Software reproducibility of myocardial blood flow and flow reserve quantification in ischemic heart disease: A 13N-ammonia PET study. J. Nucl. Cardiol. 27, 1225–1233 (2020). https://doi.org/10.1007/s12350-019-01620-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-019-01620-3

Keywords

Search

Navigation