Prognostic value of myocardial perfusion imaging in Iranian patients using total perfusion deficits: Comparison with semi-quantitative assessment

Document Type : Original Article

Authors

1 Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

2 Student Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

3 Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy

Abstract

Introduction: Considering that quantitative methods are usually more reproducible with lower inter-observer variability, the purpose of this research was to compare the prognostic value of the two quantitative method with quantitative perfusion SPECT (QPS) software.
Methods: This study was performed prospectively and included 200 participants who were referred for myocardial perfusion imaging. These participants were selected by the convenience sampling method. All patients were followed up after one year. Patients were classified as those with and without major cardiac events, including cardiac death, non-fatal myocardial infarction, open-heart surgery, abnormal angiographic findings, and unstable angina.
Results: There were 62 male (31.0%) and 138 female (69.0%) patients, ranging in age from 30 to 86 years. The results indicated that the major cardiac events were significantly higher in moderate and severe categories based on summed stress score (SSS) (P=0.024) and total perfusion deficit (TPDs) (P=0.002) scores. SSS score with TPDs score (P = 0.764), summed rest score (SRS) with TPDr score (P = 0.583) and SDS with ΔTPD (P = 0.118) were compatible for predicting major heart events within a year.
Conclusion: Total perfusion deficits obtained from QPS software is a useful method for predicting major cardiac events in patients with suspected cardiovascular disease (CVD). Predictive ability of TPD was similar to that of the semi-quantitative method with an expert interpreter's help. Moreover, this method can be helpful for CAD diagnosis and therapeutic evaluation of patients.

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References

  1. Al-Mallah MH, Sakr S, Al-Qunaibet A. Cardiorespiratory fitness and cardiovascular disease prevention: an update. Curr Atheroscler Rep. 2018;20(1):1.
  2. Joseph P, Leong D, McKee M, Anand SS, Schwalm J-D, Teo K, Mente A, Yusuf S. Reducing the global burden of cardiovascular disease, part 1: the epidemiology and risk factors. Circ Res. 2017;121(6):677-94.
  3. Stanner S, Coe S, Frayn KN. Cardiovascular disease: diet, nutrition and emerging risk factors. John Wiley & Sons; 2018.
  4. Ajay VS, Watkins DA, Prabhakaran D. Relationships among major risk factors and the burden of cardiovascular diseases, diabetes, and chronic lung disease. In: Cardiovascular, Respiratory, and Related Disorders. 3rd edition. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2017.
  5. Kazemi T, GhR SZ. The proportion of CVD from total death in Birjand, 2002-03. J Qazvin Univ Med Sci. 2005;33:73-6.
  6. Berman DS, Kang X, Gransar H, Gerlach J, Friedman JD, Hayes SW, Thomson LE, Hachamovitch R, Shaw LJ, Slomka PJ, De Yang L. 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.
  7. Xu Y, Nakazato R, Hayes S, Hachamovitch R, Cheng VY, Gransar H, Miranda-Peats R, Hyun M, Shaw LJ, Friedman J, Germano G. 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(6):1003-9.
  8. Yoda S, Nakanishi K, Tano A, Hori Y, Suzuki Y, Matsumoto N, Hirayama A. Validation of automated quantification of nuclear cardiology in Japanese patients using total perfusion deficits: comparison with visual assessment. J Cardiol. 2014;63(5):350-7.
  9. Underwood S, Godman B, Salyani S, Ogle J, Ell P. Economics of myocardial perfusion imaging in Europe—the EMPIRE Study. Eur Heart J. 1999 Jan;20(2):157-66.
  10. Chavoshi M, Fard-Esfahani A, Fallahi B, Emami-Ardekani A, Beiki D, Hassanzadeh-Rad A, Eftekhari M. Assessment of prognostic value of semiquantitative parameters on gated single photon emission computed tomography myocardial perfusion scintigraphy in a large middle eastern population. Indian J Nucl Med. Jul-Sep 2015;30(3):233-8
  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(4):433-54.
  12. Patton JA, Slomka PJ, Germano G, Berman DS. Recent technologic advances in nuclear cardiology. J Nucl Cardiol. 2007;14(4):501-13.
  13. Soman P, Parsons A, Lahiri N, Lahiri A. The prognostic value of a normal Tc-99m sestamibi SPECT study in suspected coronary artery disease. J Nucl Cardiol. 1999;6(3):252-6.
  14. Metz LD, Beattie M, Hom R, Redberg RF, Grady D, Fleischmann KE. The prognostic value of normal exercise myocardial perfusion imaging and exercise echocardiography: a meta-analysis. J Am Coll Cardiol. 2007;49(2):227-37.
  15. Shaw LJ, Hendel RC, Heller GV, Borges-Neto S, Cerqueira M, Berman DS. Prognostic estimation of coronary artery disease risk with resting perfusion abnormalities and stress ischemia on myocardial perfusion SPECT. J Nucl Cardiol. 2008;15(6):762-73.
  16. Slomka P, Xu Y, Berman D, Germano G. Quantitative analysis of perfusion studies: strengths and pitfalls. J Nucl Cardiol. 2012;19(2):338-46.
  17. Arsanjani R, Xu Y, Hayes SW, Fish M, Lemley M, Gerlach J, Dorbala S, Berman DS, Germano G, Slomka P. 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(2):221-8.
  18. Petretta M, Acampa W, Daniele S, Petretta MP, Nappi C, Assante R, Zampella E, Costanzo P, Perrone-Filardi P, Cuocolo A. Transient ischemic dilation in SPECT myocardial perfusion imaging for prediction of severe coronary artery disease in diabetic patients. J Nucl Cardiol. 2013;20(1):45-52.
  19. Berman DS, Kang X, Gransar H, Gerlach J, Friedman JD, Hayes SW, Thomson LE, Hachamovitch R, Shaw LJ, Slomka PJ, De Yang L. 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.
  20. Chang C-C, Yang M-H, Liu C-T, Chu H-L, Lin C-Y, Yen W-J, Chung CY, Ho SY, Tyan YC. Relationship between semi-quantitative parameters of thallium-201 myocardial perfusion imaging and coronary artery disease. Diagnostics. 2020;10(10):772.
  21. Yoda S, Nakanishi K, Tano A, Hori Y, Suzuki Y, Matsumoto N, Hirayama A. Usefulness of automated assessment of nuclear cardiology for prediction of major cardiac events in Japanese patients with known or suspected coronary artery disease: comparison with conventional visual assessment in a large-scale prognostic study. J Nucl Cardiol. 2014;64(5):395-400.
  22. Yoda S, Nakanishi K, Tano A, Hori Y, Suzuki Y, Matsumoto N, Hirayama A. Diagnostic value of automated quantification of nuclear cardiology in Japanese patients with single vessel coronary artery disease: comparison between Japanese and American normal databases. J Cardiol.2013;62(4):224-9.

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