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Comparison of three commercially available softwares for measuring left ventricular perfusion and function by gated SPECT myocardial perfusion imaging
Authors:Sameer Ather MD  PhD  Fahad Iqbal MD  John Gulotta MD  Wael Aljaroudi MD  Jaekyeong Heo MD  Ami E. Iskandrian MD  Fadi G. Hage MD
Affiliation:1. Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
2. Division of Cardiovascular Disease, University of Minnesota Medical Center, Minneapolis, MN, USA
3. Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
4. University of Beirut, Beirut, Lebanon
5. Section of Cardiology, Birmingham Veterans Affairs Medical Center, Birmingham, AL, USA
Abstract:

Background

The three softwares, Quantitative Perfusion SPECT (QPS), Emory Cardiac Toolbox, and 4 Dimension-Myocardial SPECT (4DM) are widely used with myocardial perfusion imaging (MPI) to determine perfusion defect size (PDS) and left ventricular (LV) function. There are limited data on the degree of agreement between these methods in quantifying the LV perfusion pattern and function.

Methods and Results

In 120 consecutive patients who had abnormal regadenoson SPECT MPI with a visually derived summed stress score ≥4, the correlation between the softwares for measurements of PDS, reversible, and fixed defects was poor to fair (Spearman’s ρ = 0.18-0.72). Overall, estimation of defect size was smaller by QPS and larger by 4DM. There was discordance among the softwares in 62% of the cases in defining PDS as small/moderate/large. The correlation between the softwares was better for measuring LVEF, volumes and mass (ρ = 0.84-0.97), and discrepant results for defining normal/mild-moderate/severe LV systolic dysfunction were prevalent in 28% of the patients.

Conclusion

There are significant differences between the softwares in measuring PDS as well as LV function, and more importantly in defining small, moderate, or large ischemic burden. These results suggest the necessity of using the same software when assessing interval changes by serial imaging.
Keywords:
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