Skip to main content
SpringerLink
Log in

Quantitative analysis of perfusion studies: Strengths and pitfalls

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

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

References

  1. Germano G, Kavanagh PB, Su HT, et al. Automatic reorientation of three-dimensional, transaxial myocardial perfusion SPECT images. J Nucl Med 1995;36:1107-14.

    PubMed  CAS  Google Scholar 

  2. Faber TL, Cooke CD, Folks RD, et al. Left ventricular function and perfusion from gated SPECT perfusion images: An integrated method. J Nucl Med 1999;40:650-9.

    PubMed  CAS  Google Scholar 

  3. Slomka PJ, Nishina H, Berman DS, et al. Automated quantification of myocardial perfusion SPECT using simplified normal limits. J Nucl Cardiol 2005;12:66-77.

    Article  PubMed  Google Scholar 

  4. Van Train KF, Areeda J, Garcia EV, et al. Quantitative same-day rest-stress technetium-99m-sestamibi SPECT: Definition and validation of stress normal limits and criteria for abnormality. J Nucl Med 1993;34:1494-502.

    PubMed  Google Scholar 

  5. Tilkemeier PL, Cooke CD, Ficaro EP, Glover DK, Hansen CL, McCallister BD Jr. American Society of Nuclear Cardiology information statement: Standardized reporting matrix for radionuclide myocardial perfusion imaging. J Nucl Cardiol 2006;13:e157-71.

    Article  PubMed  Google Scholar 

  6. Berman DS, Kiat H, Friedman JD, Wang FP, van Train K, Matzer L, et al. Separate acquisition rest thallium-201/stress technetium-99m sestamibi dual-isotope myocardial perfusion single-photon emission computed tomography: A clinical validation study. J Am Coll Cardiol 1993;22:1455-1464.

    Article  PubMed  CAS  Google Scholar 

  7. Ficaro EP, Fessler JA, Shreve PD, Kritzman JN, Rose PA, Corbett JR. Simultaneous Transmission/Emission Myocardial Perfusion Tomography: Diagnostic accuracy of attenuation-corrected 99mTc-sestamibi single-photon emission computed tomography. Circulation 1996;93:463-73.

    Article  PubMed  CAS  Google Scholar 

  8. Slomka PJ, Fish MB, Lorenzo S, et al. Simplified normal limits and automated quantitative assessment for attenuation-corrected myocardial perfusion SPECT. J Nucl Cardiol 2006;13:642-51.

    Article  PubMed  Google Scholar 

  9. Santana CA, Folks RD, Garcia EV, et al. Quantitative 82Rb PET/CT: Development and validation of myocardial perfusion database. J Nucl Med 2007;15:15.

    Google Scholar 

  10. Ficaro EP, Lee BC, Kritzman JN, Corbett JR. Corridor4DM: The Michigan method for quantitative nuclear cardiology. J Nucl Cardiol 2007;14:455-65.

    Article  PubMed  Google Scholar 

  11. 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 

  12. Liu YH. Quantification of nuclear cardiac images: The Yale approach. J Nucl Cardiol 2007;14:483-91.

    Article  PubMed  Google Scholar 

  13. Garcia EV, Faber TL, Cooke CD, Folks RD, Chen J, Santana C. The increasing role of quantification in clinical nuclear cardiology: The Emory approach. J Nucl Cardiol 2007;14:420-32.

    Article  PubMed  Google Scholar 

  14. Xu Y, Hayes S, Ali I, et al. Automatic and visual reproducibility of perfusion and function measures for myocardial perfusion SPECT. J Nucl Cardiol 2010;17:1050-7.

    Article  PubMed  Google Scholar 

  15. Berman DS, Kang X, Gransar H, Gerlach J, Friedman J, Hayes S, et al. Quantitative assessment of myocardial perfusion abnormality on SPECT myocardial perfusion imaging is more reproducible than expert visual analysis. J Nucl Cardiol 2009;16(1):45-53.

    Article  PubMed  Google Scholar 

  16. Slomka PJ, Xu Y, Fish M, Gerlach J, Dorbala S, Berman DS, et al. Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease (CAD) from myocardial perfusion SPECT (MPS) in a Large Population. J Nucl Med 2009;50:215P.

    Article  Google Scholar 

  17. Hachamovitch R, Hayes SW, Friedman JD, Cohen I, Berman DS. A prognostic score for prediction of cardiac mortality risk after adenosine stress myocardial perfusion scintigraphy. J Am Coll Cardiol 2005;45:722-9.

    Article  PubMed  Google Scholar 

  18. Shaw LJ, Berman DS, Hendel RC, Borges Neto S, Min JK, Callister TQ. Prognosis by coronary computed tomographic angiography: Matched comparison with myocardial perfusion single-photon emission computed tomography. J Cardiovasc Comput Tomogr 2008;2:93-101. Epub 2008 Jan 2012.

    Article  PubMed  Google Scholar 

  19. Hachamovitch R, Kang X, Amanullah AM, et al. Prognostic implications of myocardial perfusion single-photon emission computed tomography in the elderly. Circulation 2009;120:2197-206.

    Article  PubMed  Google Scholar 

  20. Hachamovitch R, Berman DS, Shaw LJ, et al. Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: Differential stratification for risk of cardiac death and myocardial infarction. Circulation 1998;97:535-43.

    Article  PubMed  CAS  Google Scholar 

  21. Hachamovitch R, Berman DS, Kiat H, et al. Incremental prognostic value of adenosine stress myocardial perfusion single-photon emission computed tomography and impact on subsequent management in patients with or suspected of having myocardial ischemia. Am J Cardiol 1997;80:426-33.

    Article  PubMed  CAS  Google Scholar 

  22. Amanullah AM, Berman DS, Erel J, et al. Incremental prognostic value of adenosine myocardial perfusion single-photon emission computed tomography in women with suspected coronary artery disease. Am J Cardiol 1998;82:725-30.

    Article  PubMed  CAS  Google Scholar 

  23. Pazhenkottil AP, Ghadri JR, Nkoulou RN, et al. Improved outcome prediction by SPECT myocardial perfusion imaging after CT attenuation correction. J Nucl Med 2011;52:196-200.

    Article  PubMed  Google Scholar 

  24. Leslie WD, Tully SA, Yogendran MS, Ward LM, Nour KA, Metge CJ. Prognostic value of automated quantification of Tc-99m-sestamibi myocardial perfusion imaging. J Nucl Med 2005;46:204-11.

    PubMed  Google Scholar 

  25. Xu Y, Nakazato R, Hayes S, et al. Prognostic value of automated vs visual analysis for adenosine stress myocardial perfusion SPECT in patients without prior coronary artery disease: A case-control study. J Nucl Cardiol 2011;18:1003-9.

    Article  PubMed  Google Scholar 

  26. Shaw LJ, Berman DS, Maron DJ, et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: Results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial Nuclear Substudy. Circulation 2008;117:1283.

    Article  PubMed  Google Scholar 

  27. Mahmarian JJ, Cerqueira MD, Iskandrian AE, et al. Regadenoson induces comparable left ventricular perfusion defects as adenosine: A quantitative analysis from the ADVANCE MPI 2 trial. JACC Cardiovasc Imaging 2009;2:959-68.

    Article  PubMed  Google Scholar 

  28. Cerqueira MD, Nguyen P, Staehr P, Underwood SR, Iskandrian AE. Effects of age, gender, obesity, and diabetes on the efficacy and safety of the selective A2A agonist regadenoson versus adenosine in myocardial perfusion imaging integrated ADVANCE-MPI trial results. JACC Cardiovasc Imaging 2008;1:307-16.

    Article  PubMed  Google Scholar 

  29. Berman DS, Kang X, Gransar H, et al. Quantitative assessment of myocardial perfusion abnormality on SPECT myocardial perfusion imaging is more reproducible than expert visual analysis. J Nucl Cardiol 2009;16:45-53.

    Article  PubMed  Google Scholar 

  30. Slomka PJ, Nishina H, Berman DS, et al. Automatic quantification of myocardial perfusion stress-rest change: A new measure of ischemia. J Nucl Med 2004;45:183-91.

    PubMed  Google Scholar 

  31. Mazzanti M, Germano G, Kiat H, Kavanagh PB, Alexanderson E, Friedman JD, Hachamovitch R, Van Train KF, Berman DS. 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(7):1612-20.

    Article  PubMed  CAS  Google Scholar 

  32. 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 

  33. Mandour Ali MA, Bourque J, 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.

    Google Scholar 

  34. 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.

    Google Scholar 

  35. Prasad M, Slomka PJ, Fish M, et al. Improved quantification and normal limits for myocardial perfusion stress-rest change. J Nucl Med 2010;51:204-9.

    Article  PubMed  Google Scholar 

  36. Emmett L, Iwanochko RM, Freeman MR, Barolet A, Lee DS, Husain M. Reversible regional wall motion abnormalities on exercise technetium-99m-gated cardiac single photon emission computed tomography predict high-grade angiographic stenoses. J Am Coll Cardiol 2002;39:991-8.

    Article  PubMed  Google Scholar 

  37. Lima RS, Watson DD, Goode AR, et al. 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 

  38. Karimi-Ashtiani S, Fish F, Berman D, Kavanagh P, Germano G, Slomka PJ. Development of new rest-stress motion change measure for myocardial perfusion SPECT [abstract]. J Nucl Cardiol 2011;18:761.

    Google Scholar 

  39. Matsumoto N, Berman DS, Kavanagh PB, et al. Quantitative assessment of motion artifacts and validation of a new motion-correction program for myocardial perfusion SPECT. J Nucl Med 2001;42:687-94.

    PubMed  CAS  Google Scholar 

  40. Chen J, Caputlu-Wilson SF, Shi H, Galt JR, Faber TL, Garcia EV. Automated quality control of emission-transmission misalignment for attenuation correction in myocardial perfusion imaging with SPECT-CT systems. J Nucl Cardiol 2006;13:43-9.

    Article  PubMed  Google Scholar 

  41. Alessio AM, Kinahan PE, Champley KM, Caldwell JH. Attenuation-emission alignment in cardiac PET/CT based on consistency conditions. Med Phys 2010;37:1191-200.

    Article  PubMed  Google Scholar 

  42. Xu Y, Fish M, Gerlach J, et al. Combined quantitative analysis of attenuation corrected and non-corrected myocardial perfusion SPECT: Method development and clinical validation. J Nucl Cardiol 2010;17:591-9.

    Article  PubMed  Google Scholar 

  43. Hayes SW, De Lorenzo A, Hachamovitch R, et al. Prognostic implications of combined prone and supine acquisitions in patients with equivocal or abnormal supine myocardial perfusion SPECT. J Nucl Med 2003;44:1633-40.

    PubMed  Google Scholar 

  44. Nishina H, Slomka PJ, Abidov A, et al. Combined supine and prone quantitative myocardial perfusion SPECT: Method development and clinical validation in patients with no known coronary artery disease. Soc Nuclear Med 2006;47:51-8.

    Google Scholar 

  45. Nakazato R, Tamarappoo BK, Kang X, et al. Quantitative upright-supine high-speed SPECT myocardial perfusion imaging for detection of coronary artery disease: Correlation with invasive coronary angiography. J Nucl Med 2010;51:1724-31.

    Article  PubMed  Google Scholar 

  46. Nakajima K, Okuda K, Kawano M, et al. The importance of population-specific normal database for quantification of myocardial ischemia: Comparison between Japanese 360 and 180-degree databases and a US database. J Nucl Cardiol 2009;16:422-30.

    Article  PubMed  Google Scholar 

  47. Xu Y, Kavanagh P, Fish M, et al. Automated quality control for segmentation of myocardial perfusion SPECT. J Nucl Med 2009;50:1418-26.

    Article  PubMed  Google Scholar 

Download references

Acknowledgment

Cedars-Sinai Medical Center receives royalties for the licensure of software used in the quantitative assessment of function, perfusion, and viability, a portion of which is distributed to some of the authors (PJS, DB, GG) of this article.

Author information

Authors and Affiliations

  1. Departments of Imaging and Medicine, and Cedars-Sinai Heart Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building Suite A047, Los Angeles, CA, 90048, USA

    Piotr Slomka PhD, Yuan Xu PhD, Daniel Berman MD & Guido Germano PhD

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

    Piotr Slomka PhD, Daniel Berman MD & Guido Germano PhD

Authors
  1. Piotr Slomka PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuan Xu PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniel Berman MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guido Germano PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Piotr Slomka PhD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Slomka, P., Xu, Y., Berman, D. et al. Quantitative analysis of perfusion studies: Strengths and pitfalls. J. Nucl. Cardiol. 19, 338–346 (2012). https://doi.org/10.1007/s12350-011-9509-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-011-9509-2

Keywords

Search

Navigation