Key result
4D-MSPECT yields ~4% higher LVEF estimates and larger ventricular volumes compared to QGS software.
Why the study?
Does 4D-MSPECT compared to QGS yield different values for end-diastolic volume, end-systolic volume, and LVEF in patients undergoing myocardial perfusion scintigraphy?
Cross-Sectional (n=148)
No
Does 4D-MSPECT compared to QGS yield different values for end-diastolic volume, end-systolic volume, and LVEF in patients undergoing myocardial perfusion scintigraphy?
Mean Difference: 4
Absolute Event Rate: 56.6% vs 52.6%
p-value: p=<0.001
Different software packages for quantifying gated-SPECT myocardial perfusion studies yield clinically relevant discrepancies in volume and LVEF measurements, which are influenced by heart size.
Discrepancies between QGS and 4D-MSPECT in LV volumes and EF are clinically relevant and heart-size dependent; leaves open need for standardized validation before interchangeable clinical use.
PURPOSE: Semiquantitative analysis of myocardial perfusion scintigraphy (MPS) has reduced inter- and intraobserver variability, and enables researchers to compare parameters in the same patient over time, or between groups of patients. There are several software packages available that are designed to process MPS data and quantify parameters. In this study the performances of two systems, quantitative gated SPECT (QGS) and 4D-MSPECT, in the processing of clinical patient data and phantom data were compared. METHODS: The clinical MPS data of 148 consecutive patients were analysed using QGS and 4D-MSPECT to determine the end-diastolic volume, end-systolic volume and left ventricular ejection fraction. Patients were divided into groups based on gender, body mass index, heart size, stressor type and defect type. The AGATE dynamic heart phantom was used to provide reference values for the left ventricular ejection fraction. RESULTS: Although the correlations were excellent (correlation coefficients 0.886 to 0.980) for all parameters, significant differences (p < 0.001) were found between the systems. Bland-Altman plots indicated that 4D-MSPECT provided overall higher values of all parameters than QGS. These differences between the systems were not significant in patients with a small heart (end-diastolic volume <70 ml). Other clinical factors had no direct influence on the relationship. Additionally, the phantom data indicated good linear responses of both systems. CONCLUSION: The discrepancies between these software packages were clinically relevant, and influenced by heart size. The possibility of such discrepancies should be taken into account when a new quantitative software system is introduced, or when multiple software systems are used in the same institution.
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Veen et al. (2010) conducted a cross-sectional in Suspected or proven coronary artery disease (n=148). 4D-MSPECT software vs. QGS software was evaluated on Left ventricular ejection fraction (LVEF) at rest (MD 4.0, p=<0.001). 4D-MSPECT software yielded significantly higher estimates for left ventricular ejection fraction, end-diastolic volume, and end-systolic volume compared to QGS software.
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