A Comparison of Strategies for Summing Gated Myocardial Perfusion SPECT: Are False Negatives a Potential Problem?

Introduction: The impact of technical difficulties on the diagnostic integrity of myocardial perfusion SPECT have been well documented, however, their impact on gated myocardial perfusion SPECT has more significant implications. In theory, the generation of the standard ungated data set is just summation of all the intervals for each projection from the gated data set. The reconstruction strategy employed may be stream-lined to reduce the computational demands of gated SPECT reconstruction and, thus, may potentially rendering it less accurate than it would have been without gating.Methodology: The research design employed a retrospective repeat-measures design. Using this approach meant that a single clinical data set acted as both the control group and the experimental group. 45 rest/stress patient files were examined quantitatively with CEqual quantitation software for reconstructed ungated data and summed data post reconstruction of the gated data. For each individual study, the two methods of reconstruction were performed simultaneously as a 'batch' to ensure identical reconstruction parameters and slice orientation.Results: Compared to data reconstructed as ungated files, summation of reconstructed gated files results in; a decrease in defect extent by 20.4%, a decrease in defect severity by 13.6%, a decrease in left ventricular lumen by 19.2%, an increase in total heart diameter by 9.8% and an increase in wall thickness by 32.3%.Conclusion: Not only does the generation of perfusion data via summation of the reconstructed gated data fail to provide the anticipated relief in computational demands of gated SPECT reconstruction, but it also introduces potential false negative results for coronary artery disease. This potential problem results from over smoothing and this may be particularly problematic in detecting small or non transmural defects clinically. This potential is extended to include disease classification inaccuracies resulting from underestimation of the size and/or extent of detected defects.