Journal of Nuclear Cardiology

, Volume 17, Issue 4, pp 600–616 | Cite as

Intra- and inter-operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-82 pet and a highly automated analysis program

  • Ran Klein
  • Jennifer M. Renaud
  • Maria C. Ziadi
  • Stephanie L. Thorn
  • Andy Adler
  • Rob S. Beanlands
  • Robert A. deKemp
Original Article

Abstract

Background

Changes in myocardial blood flow between rest and stress states are commonly used to diagnose coronary artery disease. Relative myocardial perfusion imaging (MPI) is used routinely while myocardial blood flow quantification (MBF) may improve the sensitivity for detection of early disease. The ratio of flow at stress and rest (S/R) and their difference (S-R) have both been proposed as a means to detect regions with reduced myocardial flow reserve (MFR). In this study, we describe a highly automated method to calculate regional and global rest, stress, S/R, and S-R polar maps of the left ventricle myocardium.

Methods

We measured the inter- and intra-operator variability using two randomized datasets (n = 30 each) for each of two operators (novice and expert) with correlation and Bland-Altman reproducibility coefficient (RPC%) analyses.

Results

S-R MBF had less inter-operator dependent variability than S/R (RPC% = 5.0% vs 12.6%, P < .001). While there was no difference in intra-operator variability with S-R MBF (novice vs expert RPC% = 6.4% vs 5.9%, P = ns), variability was higher in the novice-operator for S/R (RPC% = 16.8% vs 8.5% respectively, P < .001), suggesting that S-R may be preferred for detecting small changes in MFR. The novice operator’s intervention pattern became more similar to that of the expert in the later dataset, emphasizing the need for adequate training and quality assurance.

Conclusion

The proposed method results in low operator-dependent variability, suitable for routine use.

Keywords

PET rubidium-82 image processing coronary blood flow operator repeatability 

Notes

Acknowledgments

RK, RSB and RAD are receiving licensing revenues and consultant fees from DraxImage. RK, JMR and RAD are receiving licensing revenues from FlowQuant.

This work is supported by the following: Canadian Institute for Health Research Operating Grants MOP-79311 and MIS-100935, Ontario Research Fund Grant RE-02-038, Heart and Stroke Foundation of Ontario Program Grant # PRG6242, Canadian Foundation for Innovation—Leading Edge Fund Grant# 11306. Ran Klein was supported in part by the Natural Sciences and Engineering Research Council—Canadian Graduate Scholarship, and by the Heart and Stroke Foundation of Ontario—Doctoral Research Award. Maria C. Ziadi is a Research Fellow supported by University of Ottawa International Fellowship Award and, the Molecular Function and Imaging Program (HSFO grant # PRG6242). Stephanie L. Thorn is supported by the Heart and Stroke Foundation of Ontario—Doctoral Scholarship. Andy Adler is supported by the Natural Sciences and Engineering Research Council. Rob S. Beanlands is a Career Investigator supported by the Heart and Stroke Foundation of Ontario.

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Copyright information

© American Society of Nuclear Cardiology 2010

Authors and Affiliations

  • Ran Klein
    • 1
    • 2
  • Jennifer M. Renaud
    • 1
  • Maria C. Ziadi
    • 1
  • Stephanie L. Thorn
    • 1
  • Andy Adler
    • 3
  • Rob S. Beanlands
    • 1
  • Robert A. deKemp
    • 1
  1. 1.University of Ottawa Heart Institute, National Cardiac PET CentreOttawaCanada
  2. 2.University of Ottawa, School of Information Technology and EngineeringOttawaCanada
  3. 3.Carleton University, Systems and Computer EngineeringOttawaCanada

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